From ab101a6fb880eac41d88e8a07e018cd8e29f6bf6 Mon Sep 17 00:00:00 2001
From: jsl-models <74001263+jsl-models@users.noreply.github.com>
Date: Thu, 5 Sep 2024 15:18:09 +0700
Subject: [PATCH] 2024-09-03-xlmroberta_ner_base_indonesian_pipeline_id
 (#14391)

* Add model 2024-09-04-mindact_candidategeneration_deberta_v3_base_en

* Add model 2024-09-05-xlm_roberta_base_finetuned_lingala_pipeline_en

* Add model 2024-09-04-deberta_v3_xsmall_mnli_en

* Add model 2024-09-05-zhenyin_awesome_model_pipeline_en

* Add model 2024-09-04-medicalbert_en

* Add model 2024-09-04-tiny_random_bertfortokenclassification_ydshieh_en

* Add model 2024-09-05-burmese_awesome_wnut_model_jasonjche_en

* Add model 2024-09-04-roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline_es

* Add model 2024-09-05-afro_xlmr_base_finetuned_kintweetsd_pipeline_en

* Add model 2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_en

* Add model 2024-09-05-pp_wnut_model_en

* Add model 2024-09-05-distilbert_base_uncased_tokenclassification_yeji_seong_pipeline_en

* Add model 2024-09-05-tsc_classification_model_pipeline_en

* Add model 2024-09-05-lab1_true_random_en

* Add model 2024-09-05-indic_bert_finetuned_legal_try0_en

* Add model 2024-09-05-albert_emotion_sangmitra_06_pipeline_en

* Add model 2024-09-05-albert_emotion_sangmitra_06_en

* Add model 2024-09-03-dummy_model_0xeloco_pipeline_en

* Add model 2024-09-05-b_base_x2_pipeline_en

* Add model 2024-09-05-b_base_x2_en

* Add model 2024-09-05-finetuning_movie_sentiment_analysis_pipeline_en

* Add model 2024-09-05-inproceedings_recognizer_pipeline_en

* Add model 2024-09-04-argureviews_specificity_deberta_v1_en

* Add model 2024-09-05-finetuning_sentiment_model_3000_samples_gaurimm_pipeline_en

* Add model 2024-09-05-distilbert_base_uncased_finetuned_emotion_temp2_pipeline_en

* Add model 2024-09-05-imdbreviews_classification_distilbert_v02_sebasr0_en

* Add model 2024-09-05-n_distilbert_imdb_padding50model_pipeline_en

* Add model 2024-09-05-finetuning_sentiment_ditilbert_pipeline_en

* Add model 2024-09-05-finetuning_sentiment_ditilbert_en

* Add model 2024-09-05-finetuning_ift6758_hw6_sentiment_model_en

* Add model 2024-09-05-pii_model_ankitcodes_pipeline_en

* Add model 2024-09-05-arabic_ner_ace_ar

* Add model 2024-09-05-bert_finetuned_ner_clinical_plncmm_large_25_en

* Add model 2024-09-05-category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline_en

* Add model 2024-09-05-bert_ner_rubertconv_toxic_editor_ru

* Add model 2024-09-04-feelings_a6000_0_00001_pipeline_en

* Add model 2024-09-05-albert_persian_farsi_zwnj_base_v2_ner_fa

* Add model 2024-09-05-albert_persian_farsi_zwnj_base_v2_ner_pipeline_fa

* Add model 2024-09-04-distilbert_base_uncased_finetuned_squad_d5716d28_sonny_en

* Add model 2024-09-05-rubert_base_cased_conversational_ner_v3_pipeline_en

* Add model 2024-09-04-yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline_en

* Add model 2024-09-05-bert_token_classifier_reddit_ner_place_names_en

* Add model 2024-09-05-bert_based_turkish_ner_wikiann_tr

* Add model 2024-09-05-indonesian_bert_base_ner_indonlu_en

* Add model 2024-09-05-glot500_with_transliteration_average_en

* Add model 2024-09-02-deberta_v3_base_squad2_ext_v1_pipeline_en

* Add model 2024-09-05-sent_less_100000_xlm_roberta_mmar_recipe_10_base_en

* Add model 2024-09-04-sent_dziribert_ar

* Add model 2024-09-04-legal_xlm_roberta_large_xx

* Add model 2024-09-04-burmese_awesome_wnut_all_time_en

* Add model 2024-09-04-twitter_roberta_large_emotion_latest_pipeline_en

* Add model 2024-09-04-burmese_awesome_wnut_model_robinsh2023_en

* Add model 2024-09-04-cola_deberta_v3_large_pipeline_en

* Add model 2024-09-05-roberta_base_finetuned_ner_sevixdd_en

* Add model 2024-09-05-distilbert_ner_sahuh_pipeline_en

* Add model 2024-09-05-roberta_base_ner_updated_mn

* Add model 2024-09-05-afro_xlmr_base_finetuned_kintweetsc_en

* Add model 2024-09-05-roberta_base_ner_demo_sanchirjav_pipeline_mn

* Add model 2024-09-05-roberta_base_ner_demo_sanchirjav_mn

* Add model 2024-09-05-nuner_v2_fewnerd_fine_super_pipeline_en

* Add model 2024-09-05-burmese_awesome_wnut_model_honganh_en

* Add model 2024-09-05-test_ner_en

* Add model 2024-09-05-roberta_skills_ner_en

* Add model 2024-09-05-ner_meddocan_es

* Add model 2024-09-05-roberta_base_finetuned_ner_lobrien001_pipeline_en

* Add model 2024-09-05-burmese_awesome_wnut_model_donbasta_en

* Add model 2024-09-05-privacy_200k_masking_en

* Add model 2024-09-05-our_awesome_bert_model_pipeline_en

* Add model 2024-09-05-opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk_en

* Add model 2024-09-05-imdb_spoiler_distilbertorigdatasetlr3_en

* Add model 2024-09-05-albert_xxlarge_v2_disaster_twitter_v2_en

* Add model 2024-09-04-sanbert_from_scratch_pipeline_en

* Add model 2024-09-05-finance_news_classifier_kanuri_v7_ko

* Add model 2024-09-04-argureviews_specificity_deberta_v1_pipeline_en

* Add model 2024-09-05-xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline_en

* Add model 2024-09-03-sent_glot500_base_pipeline_en

* Add model 2024-09-04-distilbert_alex_pipeline_en

* Add model 2024-09-03-burmese_awesome_model_yagina_en

* Add model 2024-09-03-mariannmt_tatoeba_luxembourgish_english_pipeline_lb

* Add model 2024-09-04-mnli_microsoft_deberta_v3_large_seed_2_en

* Add model 2024-09-05-xlmr_chatgptdetect_noisy_en

* Add model 2024-09-04-uniir_sf_vit_large_patch14_336_epoch12_pipeline_en

* Add model 2024-09-05-naija_twitter_sentiment_afriberta_large_en

* Add model 2024-09-05-xlm_roberta_base_finetuned_nace_en

* Add model 2024-09-05-burmese_awesome_model_jasssz_en

* Add model 2024-09-05-distilbert_sentiment_classifier_kiel1_en

* Add model 2024-09-05-bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx

* Add model 2024-09-05-cryptocurrency_intent_search_detection_en

* Add model 2024-09-05-xml_roberta_climate_change_explicit_v01_en

* Add model 2024-09-04-clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline_en

* Add model 2024-09-05-rtmex23_pol4_cardif_pipeline_en

* Add model 2024-09-05-xlm_roberta_qa_addi_italian_xlm_r_pipeline_it

* Add model 2024-09-04-distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_en

* Add model 2024-09-03-cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline_en

* Add model 2024-09-04-dummy_model_binitha_pipeline_en

* Add model 2024-09-04-distilbert_base_cased_pii_english_en

* Add model 2024-09-04-deberta_v3_base_1107_en

* Add model 2024-09-05-bert_token_classifier_uncased_keyword_discriminator_en

* Add model 2024-09-04-mdeberta_v3_base_open_ner_pipeline_en

* Add model 2024-09-05-bangla_twoclass_sentiment_analyzer_en

* Add model 2024-09-04-xlm_roberta_base_finetuned_panx_german_joanna684_en

* Add model 2024-09-05-multilingual_e5_language_detection_xx

* Add model 2024-09-05-xml_roberta_science_subject_text_classification_pipeline_en

* Add model 2024-09-04-distilbert_base_uncased_finetuned_streamers_en

* Add model 2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_french_en

* Add model 2024-09-04-mdeberta_v3_base_harem_en

* Add model 2024-09-03-deberta_v3_base_finetuned_ai4privacy_v2_en

* Add model 2024-09-05-ibert_roberta_base_finetuned_wikineural_pipeline_en

* Add model 2024-09-05-portuguese_capitalization_punctuation_restoration_sanivert_pt

* Add model 2024-09-05-rubert_base_massive_ner_ru

* Add model 2024-09-03-xlm_roberta_base_esg_ner_en

* Add model 2024-09-03-sent_bert_large_cased_whole_word_masking_pipeline_en

* Add model 2024-09-05-camelbert_msa_qalb14_ged_13_ar

* Add model 2024-09-05-bert_base_multilingual_cased_finetuned_ner_harem_pipeline_xx

* Add model 2024-09-05-bent_pubmedbert_ner_gene_en

* Add model 2024-09-05-linkbert_en

* Add model 2024-09-05-bent_pubmedbert_ner_gene_pipeline_en

* Add model 2024-09-05-nerde_base_en

* Add model 2024-09-05-wg_bert_pipeline_en

* Add model 2024-09-05-ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline_en

* Add model 2024-09-05-gec_turkish_seq_tagger_tr

* Add model 2024-09-05-burmese_awesome_wnut_model_osquery_pipeline_en

* Add model 2024-09-05-rogec_robert_large_en

* Add model 2024-09-05-ner_fine_tuned_beto_es

* Add model 2024-09-05-burmese_awesome_model_lenatt_en

* Add model 2024-09-05-imdb_spoiler_distilbertorigdatasetlr3_pipeline_en

* Add model 2024-09-05-albert_xxlarge_v2_disaster_twitter_v2_pipeline_en

* Add model 2024-09-05-multilingual_sentiment_covid19_pipeline_xx

* Add model 2024-09-05-bge_micro_v2_esg_v2_en

* Add model 2024-09-05-bge_large_chinese_v1_6_en

* Add model 2024-09-05-bge_base_citi_dataset_detailed_9k_1_5k_e1_en

* Add model 2024-09-05-philai_bge_2et_f_again_en

* Add model 2024-09-04-deberta_v3_small_finetuned_mrpc_en

* Add model 2024-09-05-bge_small_english_v1_5_esg_pipeline_en

* Add model 2024-09-05-bge_small_english_v1_5_esg_en

* Add model 2024-09-05-bge_small_bioasq_3epochs_batch32_en

* Add model 2024-09-05-bge_base_citi_dataset_9k_1k_e1_pipeline_en

* Add model 2024-09-05-bge_base_financial_matryoshka_adarshheg_en

* Add model 2024-09-04-deberta_v3_base_finetuned_french_pipeline_en

* Add model 2024-09-05-distilbert_base_uncased_qqp_en

* Add model 2024-09-05-bge_base_financial_matryoshka_adarshheg_pipeline_en

* Add model 2024-09-05-bge_large_english_world_news_osint_v1_en

* Add model 2024-09-05-xml_roberta_climate_change_explicit_v01_pipeline_en

* Add model 2024-09-05-xlm_roberta_base_tweet_sentiment_french_pipeline_en

* Add model 2024-09-04-all_mpnet_base_v2_1_en

* Add model 2024-09-04-distilbert_hera_synthetic_pretrain_en

* Add model 2024-09-05-bge_large_english_world_news_osint_v1_pipeline_en

* Add model 2024-09-04-dummy_model_gvozdev_en

* Add model 2024-09-05-burmese_awesome_wnut_place_en

* Add model 2024-09-05-distilbert_base_uncased_finetuned_neg_en

* Add model 2024-09-05-distillbert_finetuned_ner_btc_en

* Add model 2024-09-05-burmese_awesome_wnut_model_langchain12_en

* Add model 2024-09-05-burmese_awesome_wnut_model_thypogean_pipeline_en

* Add model 2024-09-05-shopee_ner_pipeline_en

* Add model 2024-09-05-distilbert_ner_augmented_en

* Add model 2024-09-05-burmese_awesome_wnut_model_basirudin_pipeline_en

* Add model 2024-09-05-distilbert_base_uncased_celinalopga_en

* Add model 2024-09-05-context_tracking_pipeline_en

* Add model 2024-09-05-context_tracking_en

* Add model 2024-09-05-sembr2023_distilbert_base_multilingual_cased_xx

* Add model 2024-09-05-sembr2023_distilbert_base_multilingual_cased_pipeline_xx

* Add model 2024-09-05-distilbert_base_uncased_finetuned_ner_artem1981_en

* Add model 2024-09-05-trained_slovak_en

* Add model 2024-09-04-roberta_qa_base_spanish_squades_becasincentivos2_pipeline_es

* Add model 2024-09-05-rubert_base_massive_ner_pipeline_ru

* Add model 2024-09-05-test_ner_pipeline_en

* Add model 2024-09-05-nli_conventional_fine_tuning_m4faisal_pipeline_en

* Add model 2024-09-04-bmg_translation_lug_english_v2_pipeline_en

* Add model 2024-09-05-trained_baseline_en

* Add model 2024-09-04-dagpap24_deberta_base_ft_pipeline_en

* Add model 2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline_en

* Add model 2024-09-05-bert_kor_base_ko

* Add model 2024-09-05-biomednlp_biomedbert_base_uncased_abstract_fulltext_en

* Add model 2024-09-05-bert_kor_base_pipeline_ko

* Add model 2024-09-05-norwegian_bokml_bert_large_pipeline_no

* Add model 2024-09-05-rogec_robert_large_pipeline_en

* Add model 2024-09-05-distilbert_base_uncased_finetuned_emotion_temp2_en

* Add model 2024-09-05-disorbert_en

* Add model 2024-09-05-convbert_base_turkish_mc4_uncased_pipeline_tr

* Add model 2024-09-03-sent_pretrained_xlm_portuguese_e5_select_pipeline_en

* Add model 2024-09-05-adp_model_en

* Add model 2024-09-05-bge_base_financial_matryoshka_uhoffmann_pipeline_en

* Add model 2024-09-04-bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_en

* Add model 2024-09-03-distilbert_base_uncased_finetuned_imdb_aliekens_en

* Add model 2024-09-05-bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline_en

* Add model 2024-09-04-sent_bert_base_indonesian_1_5g_pipeline_id

* Add model 2024-09-05-biomednlp_biomedbert_large_uncased_abstract_pipeline_en

* Add model 2024-09-05-esg_classification_french_english_fr

* Add model 2024-09-04-dummy_model_rocksat_en

* Add model 2024-09-03-finetuning_sentiment_model_mpnet_imdb_pipeline_en

* Add model 2024-09-05-translation_english_korean_pipeline_en

* Add model 2024-09-05-philai_bge_2et_f_again_pipeline_en

* Add model 2024-09-05-sent_arbertv2_pipeline_ar

* Add model 2024-09-05-sent_bert_large_uncased_whole_word_masking_en

* Add model 2024-09-05-sent_corsican_condenser_marco_en

* Add model 2024-09-05-bge_base_financial_matryoshka_ethan_ky_pipeline_en

* Add model 2024-09-05-sent_bert_base_uncased_echr_pipeline_en

* Add model 2024-09-05-sent_bert_base_uncased_echr_en

* Add model 2024-09-05-sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline_pt

* Add model 2024-09-04-mdeberta_v3_base_mrpc_10_pipeline_en

* Add model 2024-09-02-xlm_roberta_base_finetuned_panx_german_maxfrax_en

* Add model 2024-09-05-sent_berel_finetuned_dss_maskedlm_pipeline_en

* Add model 2024-09-04-distilbert_emotion_neelams_en

* Add model 2024-09-04-roberta_base_hate_en

* Add model 2024-09-05-sent_bert_base_qarib_ar

* Add model 2024-09-05-sent_norwegian_bokml_bert_base_pipeline_no

* Add model 2024-09-05-sent_norwegian_bokml_bert_base_no

* Add model 2024-09-04-roberta_finetuned_squad_noushsuon_pipeline_en

* Add model 2024-09-04-xlmroberta_ner_tner_base_conll2003_en

* Add model 2024-09-05-sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1_pt

* Add model 2024-09-04-roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline_en

* Add model 2024-09-05-distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline_en

* Add model 2024-09-05-burmese_awesome_wnut_model_saikatkumardey_en

* Add model 2024-09-05-burmese_ner_model_mundo_go_en

* Add model 2024-09-05-ae_detection_distilbert_en

* Add model 2024-09-05-burmese_awesome_wnut_model_yuting27_en

* Add model 2024-09-05-multilingual_e5_language_detection_pipeline_xx

* Add model 2024-09-04-trustpilot_roberta_gender_pipeline_en

* Add model 2024-09-05-distilbert_base_uncased_celinalopga_pipeline_en

* Add model 2024-09-05-clip_finetuned_pipeline_en

* Add model 2024-09-05-distilbert_base_uncased_finetuned_ner_sindhujag26_en

* Add model 2024-09-05-roberta_skills_ner_pipeline_en

* Add model 2024-09-05-screenshot_fashion_clip_finetuned_v2_t1_en

* Add model 2024-09-05-clip_seed_vit_8_en

* Add model 2024-09-05-screenshot_fashion_clip_finetuned_v2_t1_pipeline_en

* Add model 2024-09-04-comfact_deberta_v2_en

* Add model 2024-09-05-biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en

* Add model 2024-09-05-bert_base_german_uncased_dbmdz_pipeline_de

* Add model 2024-09-03-slovakbert_pipeline_sk

* Add model 2024-09-05-bert_emotion_gyvertc_pipeline_en

* Add model 2024-09-03-camembert_base_toxic_french_user_prompts_pipeline_fr

* Add model 2024-09-05-timeset_ifm_en

* Add model 2024-09-05-distilbert_base_uncased_finetuned_clinc_mrwetsnow_en

* Add model 2024-09-03-autonlp_feedback1_479512837_pipeline_en

* Add model 2024-09-05-darijabert_pipeline_ar

* Add model 2024-09-05-bge_base_financial_matryoshka_uhoffmann_en

* Add model 2024-09-04-burmese_ws_extraction_model_27th_mar_pipeline_en

* Add model 2024-09-03-varta_bert_xx

* Add model 2024-09-04-setfit_sentiment_analysis_ep20_en

* Add model 2024-09-04-distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline_en

* Add model 2024-09-04-xlm_roberta_base_finetuned_panx_german_blanche_pipeline_en

* Add model 2024-09-05-clip_vit_base_patch32_demo_xiaoliy2_en

* Add model 2024-09-05-clip_large_fp16_pipeline_en

* Add model 2024-09-05-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_en

* Add model 2024-09-04-trust_merged_dataset_mdeberta_v3_20epoch_en

* Add model 2024-09-05-aift_model_en

* Add model 2024-09-03-bookmebus_sentiment_analysis_en

* Add model 2024-09-05-distilbert_lolchamps_en

* Add model 2024-09-05-distilbert_base_uncased_finetuned_imdb_zhenchuan_en

* Add model 2024-09-05-distilbert_base_uncased_finetuned_imdb_abh1na5_en

---------

Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>
---
 ...lbert_base_finetuned_recipe_modified_en.md |  86 +++++++++++++
 ...2024-09-01-albert_base_qa_2_k_fold_1_en.md |  86 +++++++++++++
 ...ier_autonlp_entity_selection_5771228_en.md | 104 +++++++++++++++
 ..._512_finetuned_squad_seed_6_pipeline_en.md |  69 ++++++++++
 ...09-01-bge_base_english_v1_5_ft_ragds_en.md |  87 +++++++++++++
 ...bge_base_financial_matryoshka_test_3_en.md |  87 +++++++++++++
 ...01-bge_bislama_encoder_20_8_pipeline_en.md |  69 ++++++++++
 ...ion_20240820_model_distilbert_0_9847_en.md |  94 ++++++++++++++
 ...24-09-01-burmese_ws_extraction_model_en.md |  94 ++++++++++++++
 ...t_sayula_popoluca_italian_2_pipeline_en.md |  70 ++++++++++
 ...024-09-01-charles_dickens_classifier_en.md |  94 ++++++++++++++
 .../2024-09-01-climate_fact_checker_en.md     |  94 ++++++++++++++
 ...4-09-01-code_prompt_similarity_model_en.md |  86 +++++++++++++
 .../2024-09-01-deberta_pii_finetuned_en.md    |  94 ++++++++++++++
 ...1-deberta_v3_large_com2_car_pipeline_en.md |  70 ++++++++++
 ...3_large_conll2003_breast_v1_pipeline_en.md |  70 ++++++++++
 ...uning_sentiment_model_3000_samples_4_en.md |  98 ++++++++++++++
 ...timent_model_3000_samples_4_pipeline_en.md |  70 ++++++++++
 ..._448_inpaint_context_length_pipeline_en.md |  70 ++++++++++
 .../2024-09-01-mongolian_roberta_base_en.md   |  94 ++++++++++++++
 ...01-openai_roberta_large_ai_detection_en.md |  94 ++++++++++++++
 ..._finetuned_newqa1_ericpeter_pipeline_en.md |  69 ++++++++++
 ...4-09-01-robertacrawlpt_base_pipeline_pt.md |  70 ++++++++++
 ...n_on_mandates_public_health_pipeline_en.md |  69 ++++++++++
 ...tter_roberta_base_2021_124m_pipeline_en.md |  70 ++++++++++
 ..._roberta_large_topic_latest_pipeline_en.md |  70 ++++++++++
 .../ahmedlone127/2024-09-01-video_llava_en.md | 120 ++++++++++++++++++
 .../2024-09-02-16_shot_twitter_en.md          |  86 +++++++++++++
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diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_base_finetuned_recipe_modified_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_base_finetuned_recipe_modified_en.md
new file mode 100644
index 00000000000000..7372222b96068b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-albert_base_finetuned_recipe_modified_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_base_finetuned_recipe_modified AlbertForQuestionAnswering from saumyasinha0510
+author: John Snow Labs
+name: albert_base_finetuned_recipe_modified
+date: 2024-09-01
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_finetuned_recipe_modified` is a English model originally trained by saumyasinha0510.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_finetuned_recipe_modified_en_5.4.2_3.0_1725193374690.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_finetuned_recipe_modified_en_5.4.2_3.0_1725193374690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_finetuned_recipe_modified","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_finetuned_recipe_modified", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_finetuned_recipe_modified|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/saumyasinha0510/Albert-base-finetuned-recipe-modified
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_k_fold_1_en.md b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_k_fold_1_en.md
new file mode 100644
index 00000000000000..167d0884b29b26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-albert_base_qa_2_k_fold_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_base_qa_2_k_fold_1 AlbertForQuestionAnswering from mateiaass
+author: John Snow Labs
+name: albert_base_qa_2_k_fold_1
+date: 2024-09-01
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_k_fold_1` is a English model originally trained by mateiaass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_1_en_5.4.2_3.0_1725193498781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_1_en_5.4.2_3.0_1725193498781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_k_fold_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_k_fold_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_qa_2_k_fold_1|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/mateiaass/albert-base-qa-2-k-fold-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_entity_selection_5771228_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_entity_selection_5771228_en.md
new file mode 100644
index 00000000000000..ef18a18d863b0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-bert_classifier_autonlp_entity_selection_5771228_en.md
@@ -0,0 +1,104 @@
+---
+layout: model
+title: English BertForSequenceClassification Cased model (from kamivao)
+author: John Snow Labs
+name: bert_classifier_autonlp_entity_selection_5771228
+date: 2024-09-01
+tags: [en, open_source, bert, sequence_classification, classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-entity_selection-5771228` is a English model originally trained by `kamivao`.
+
+## Predicted Entities
+
+`1`, `0`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_entity_selection_5771228_en_5.4.2_3.0_1725204813533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autonlp_entity_selection_5771228_en_5.4.2_3.0_1725204813533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autonlp_entity_selection_5771228","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autonlp_entity_selection_5771228","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.classify.bert.by_kamivao").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_autonlp_entity_selection_5771228|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/kamivao/autonlp-entity_selection-5771228
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline_en.md
new file mode 100644
index 00000000000000..1bcbf395efa26a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline pipeline BertForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline_en_5.4.2_3.0_1725185371351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline_en_5.4.2_3.0_1725185371351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|386.6 MB|
+
+## References
+
+https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-6
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_ft_ragds_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_ft_ragds_en.md
new file mode 100644
index 00000000000000..9ab2b1c1448fa5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_english_v1_5_ft_ragds_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_ft_ragds BGEEmbeddings from aritrasen
+author: John Snow Labs
+name: bge_base_english_v1_5_ft_ragds
+date: 2024-09-01
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_ft_ragds` is a English model originally trained by aritrasen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_ft_ragds_en_5.4.2_3.0_1725199632356.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_ft_ragds_en_5.4.2_3.0_1725199632356.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_ft_ragds","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_ft_ragds","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_ft_ragds|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|404.3 MB|
+
+## References
+
+https://huggingface.co/aritrasen/bge-base-en-v1.5-ft_ragds
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_3_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_3_en.md
new file mode 100644
index 00000000000000..6b0da1f2835c61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-bge_base_financial_matryoshka_test_3_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_test_3 BGEEmbeddings from NickyNicky
+author: John Snow Labs
+name: bge_base_financial_matryoshka_test_3
+date: 2024-09-01
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_test_3` is a English model originally trained by NickyNicky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_3_en_5.5.0_3.0_1725228334702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_test_3_en_5.5.0_3.0_1725228334702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_3","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_test_3","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_test_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/NickyNicky/bge-base-financial-matryoshka_test_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-bge_bislama_encoder_20_8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-bge_bislama_encoder_20_8_pipeline_en.md
new file mode 100644
index 00000000000000..132aadac93a6b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-bge_bislama_encoder_20_8_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_bislama_encoder_20_8_pipeline pipeline BGEEmbeddings from quangtqv
+author: John Snow Labs
+name: bge_bislama_encoder_20_8_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_bislama_encoder_20_8_pipeline` is a English model originally trained by quangtqv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_bislama_encoder_20_8_pipeline_en_5.5.0_3.0_1725228363114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_bislama_encoder_20_8_pipeline_en_5.5.0_3.0_1725228363114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_bislama_encoder_20_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_bislama_encoder_20_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_bislama_encoder_20_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|389.5 MB|
+
+## References
+
+https://huggingface.co/quangtqv/bge_bi_encoder_20_8
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-brand_classification_20240820_model_distilbert_0_9847_en.md b/docs/_posts/ahmedlone127/2024-09-01-brand_classification_20240820_model_distilbert_0_9847_en.md
new file mode 100644
index 00000000000000..abcb7672177347
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-brand_classification_20240820_model_distilbert_0_9847_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brand_classification_20240820_model_distilbert_0_9847 DistilBertForSequenceClassification from jointriple
+author: John Snow Labs
+name: brand_classification_20240820_model_distilbert_0_9847
+date: 2024-09-01
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brand_classification_20240820_model_distilbert_0_9847` is a English model originally trained by jointriple.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brand_classification_20240820_model_distilbert_0_9847_en_5.5.0_3.0_1725213570934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brand_classification_20240820_model_distilbert_0_9847_en_5.5.0_3.0_1725213570934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("brand_classification_20240820_model_distilbert_0_9847","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("brand_classification_20240820_model_distilbert_0_9847", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brand_classification_20240820_model_distilbert_0_9847|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|252.9 MB|
+
+## References
+
+https://huggingface.co/jointriple/brand_classification_20240820_model_distilbert_0_9847
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-burmese_ws_extraction_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-burmese_ws_extraction_model_en.md
new file mode 100644
index 00000000000000..e16db494364b64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-burmese_ws_extraction_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ws_extraction_model DistilBertForTokenClassification from manimaranpa07
+author: John Snow Labs
+name: burmese_ws_extraction_model
+date: 2024-09-01
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ws_extraction_model` is a English model originally trained by manimaranpa07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_en_5.4.2_3.0_1725171048932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_en_5.4.2_3.0_1725171048932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_ws_extraction_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_ws_extraction_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ws_extraction_model|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/manimaranpa07/my_Ws_extraction_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-cat_sayula_popoluca_italian_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-cat_sayula_popoluca_italian_2_pipeline_en.md
new file mode 100644
index 00000000000000..3cca569e55edd9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-cat_sayula_popoluca_italian_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cat_sayula_popoluca_italian_2_pipeline pipeline CamemBertForTokenClassification from homersimpson
+author: John Snow Labs
+name: cat_sayula_popoluca_italian_2_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_italian_2_pipeline` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_italian_2_pipeline_en_5.4.2_3.0_1725174928707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_italian_2_pipeline_en_5.4.2_3.0_1725174928707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cat_sayula_popoluca_italian_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cat_sayula_popoluca_italian_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cat_sayula_popoluca_italian_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|391.7 MB|
+
+## References
+
+https://huggingface.co/homersimpson/cat-pos-it-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-charles_dickens_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-01-charles_dickens_classifier_en.md
new file mode 100644
index 00000000000000..3304fc70a735fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-charles_dickens_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English charles_dickens_classifier DistilBertForSequenceClassification from GuillermoTBB
+author: John Snow Labs
+name: charles_dickens_classifier
+date: 2024-09-01
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`charles_dickens_classifier` is a English model originally trained by GuillermoTBB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/charles_dickens_classifier_en_5.5.0_3.0_1725214204041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/charles_dickens_classifier_en_5.5.0_3.0_1725214204041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("charles_dickens_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("charles_dickens_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|charles_dickens_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/GuillermoTBB/charles-dickens-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-climate_fact_checker_en.md b/docs/_posts/ahmedlone127/2024-09-01-climate_fact_checker_en.md
new file mode 100644
index 00000000000000..ca3fda97648919
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-climate_fact_checker_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English climate_fact_checker DistilBertForSequenceClassification from fzanartu
+author: John Snow Labs
+name: climate_fact_checker
+date: 2024-09-01
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climate_fact_checker` is a English model originally trained by fzanartu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climate_fact_checker_en_5.5.0_3.0_1725213860717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climate_fact_checker_en_5.5.0_3.0_1725213860717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("climate_fact_checker","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("climate_fact_checker", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|climate_fact_checker|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/fzanartu/climate-fact-checker
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-code_prompt_similarity_model_en.md b/docs/_posts/ahmedlone127/2024-09-01-code_prompt_similarity_model_en.md
new file mode 100644
index 00000000000000..1152c5fbf3a89e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-code_prompt_similarity_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English code_prompt_similarity_model MPNetEmbeddings from davanstrien
+author: John Snow Labs
+name: code_prompt_similarity_model
+date: 2024-09-01
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_prompt_similarity_model` is a English model originally trained by davanstrien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_prompt_similarity_model_en_5.5.0_3.0_1725225026381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_prompt_similarity_model_en_5.5.0_3.0_1725225026381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("code_prompt_similarity_model","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("code_prompt_similarity_model","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_prompt_similarity_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|380.8 MB|
+
+## References
+
+https://huggingface.co/davanstrien/code-prompt-similarity-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_pii_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_pii_finetuned_en.md
new file mode 100644
index 00000000000000..2a3d610cef88a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_pii_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_pii_finetuned DeBertaForTokenClassification from 1-13-am
+author: John Snow Labs
+name: deberta_pii_finetuned
+date: 2024-09-01
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_pii_finetuned` is a English model originally trained by 1-13-am.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_pii_finetuned_en_5.4.2_3.0_1725196195089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_pii_finetuned_en_5.4.2_3.0_1725196195089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_pii_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_pii_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_pii_finetuned|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|630.6 MB|
+
+## References
+
+https://huggingface.co/1-13-am/deberta-pii-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_car_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_car_pipeline_en.md
new file mode 100644
index 00000000000000..a873ec4124ddde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_com2_car_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_com2_car_pipeline pipeline DeBertaEmbeddings from tqfang229
+author: John Snow Labs
+name: deberta_v3_large_com2_car_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_com2_car_pipeline` is a English model originally trained by tqfang229.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_com2_car_pipeline_en_5.5.0_3.0_1725230921090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_com2_car_pipeline_en_5.5.0_3.0_1725230921090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_com2_car_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_com2_car_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_com2_car_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/tqfang229/deberta-v3-large-com2-car
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_conll2003_breast_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_conll2003_breast_v1_pipeline_en.md
new file mode 100644
index 00000000000000..520ca6d31c6bb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-deberta_v3_large_conll2003_breast_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_conll2003_breast_v1_pipeline pipeline DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: deberta_v3_large_conll2003_breast_v1_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_conll2003_breast_v1_pipeline` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_conll2003_breast_v1_pipeline_en_5.4.2_3.0_1725197862391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_conll2003_breast_v1_pipeline_en_5.4.2_3.0_1725197862391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_conll2003_breast_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_conll2003_breast_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_conll2003_breast_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/deberta-v3-large_conll2003_breast_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuning_sentiment_model_3000_samples_4_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuning_sentiment_model_3000_samples_4_en.md
new file mode 100644
index 00000000000000..2e2e39838f8887
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-finetuning_sentiment_model_3000_samples_4_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_4 DistilBertForSequenceClassification from rithwik-db
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_4
+date: 2024-09-01
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_4` is a English model originally trained by rithwik-db.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_4_en_5.5.0_3.0_1725213867773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_4_en_5.5.0_3.0_1725213867773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_4","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_4","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/rithwik-db/finetuning-sentiment-model-3000-samples-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuning_sentiment_model_3000_samples_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuning_sentiment_model_3000_samples_4_pipeline_en.md
new file mode 100644
index 00000000000000..e4ab62bcb14b17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-finetuning_sentiment_model_3000_samples_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_4_pipeline pipeline DistilBertForSequenceClassification from mamledes
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_4_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_4_pipeline` is a English model originally trained by mamledes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_4_pipeline_en_5.5.0_3.0_1725213883084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_4_pipeline_en_5.5.0_3.0_1725213883084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mamledes/finetuning-sentiment-model-3000-samples_4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-mariobert_448_inpaint_context_length_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-mariobert_448_inpaint_context_length_pipeline_en.md
new file mode 100644
index 00000000000000..8b9b23fb2a7629
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-mariobert_448_inpaint_context_length_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mariobert_448_inpaint_context_length_pipeline pipeline RoBertaEmbeddings from shyamsn97
+author: John Snow Labs
+name: mariobert_448_inpaint_context_length_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariobert_448_inpaint_context_length_pipeline` is a English model originally trained by shyamsn97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mariobert_448_inpaint_context_length_pipeline_en_5.4.2_3.0_1725165506113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariobert_448_inpaint_context_length_pipeline_en_5.4.2_3.0_1725165506113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mariobert_448_inpaint_context_length_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mariobert_448_inpaint_context_length_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mariobert_448_inpaint_context_length_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|305.6 MB|
+
+## References
+
+https://huggingface.co/shyamsn97/MarioBert-448-inpaint-context-length
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-mongolian_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-mongolian_roberta_base_en.md
new file mode 100644
index 00000000000000..a12445bf46dce9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-mongolian_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mongolian_roberta_base RoBertaEmbeddings from bayartsogt
+author: John Snow Labs
+name: mongolian_roberta_base
+date: 2024-09-01
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mongolian_roberta_base` is a English model originally trained by bayartsogt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mongolian_roberta_base_en_5.4.2_3.0_1725186043913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mongolian_roberta_base_en_5.4.2_3.0_1725186043913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("mongolian_roberta_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("mongolian_roberta_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mongolian_roberta_base|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/bayartsogt/mongolian-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-openai_roberta_large_ai_detection_en.md b/docs/_posts/ahmedlone127/2024-09-01-openai_roberta_large_ai_detection_en.md
new file mode 100644
index 00000000000000..ecd33ea70f9e47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-openai_roberta_large_ai_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English openai_roberta_large_ai_detection RoBertaForSequenceClassification from Varun53
+author: John Snow Labs
+name: openai_roberta_large_ai_detection
+date: 2024-09-01
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`openai_roberta_large_ai_detection` is a English model originally trained by Varun53.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/openai_roberta_large_ai_detection_en_5.4.2_3.0_1725167615989.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/openai_roberta_large_ai_detection_en_5.4.2_3.0_1725167615989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("openai_roberta_large_ai_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("openai_roberta_large_ai_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|openai_roberta_large_ai_detection|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Varun53/openai-roberta-large-AI-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline_en.md
new file mode 100644
index 00000000000000..9d0adf62a3fa0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline pipeline RoBertaForQuestionAnswering from EricPeter
+author: John Snow Labs
+name: roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline` is a English model originally trained by EricPeter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline_en_5.4.2_3.0_1725206437848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline_en_5.4.2_3.0_1725206437848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad2_finetuned_newqa1_ericpeter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/EricPeter/roberta-base-squad2-finetuned-newqa1
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-robertacrawlpt_base_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-01-robertacrawlpt_base_pipeline_pt.md
new file mode 100644
index 00000000000000..e4c9f3e9b85e58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-robertacrawlpt_base_pipeline_pt.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Portuguese robertacrawlpt_base_pipeline pipeline RoBertaEmbeddings from eduagarcia
+author: John Snow Labs
+name: robertacrawlpt_base_pipeline
+date: 2024-09-01
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robertacrawlpt_base_pipeline` is a Portuguese model originally trained by eduagarcia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robertacrawlpt_base_pipeline_pt_5.4.2_3.0_1725191856259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robertacrawlpt_base_pipeline_pt_5.4.2_3.0_1725191856259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("robertacrawlpt_base_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robertacrawlpt_base_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robertacrawlpt_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|296.9 MB|
+
+## References
+
+https://huggingface.co/eduagarcia/RoBERTaCrawlPT-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-setfit_model_misinformation_on_mandates_public_health_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-setfit_model_misinformation_on_mandates_public_health_pipeline_en.md
new file mode 100644
index 00000000000000..9ed3c308f33f98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-setfit_model_misinformation_on_mandates_public_health_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_model_misinformation_on_mandates_public_health_pipeline pipeline MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_misinformation_on_mandates_public_health_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_misinformation_on_mandates_public_health_pipeline` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_misinformation_on_mandates_public_health_pipeline_en_5.5.0_3.0_1725224983324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_misinformation_on_mandates_public_health_pipeline_en_5.5.0_3.0_1725224983324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("setfit_model_misinformation_on_mandates_public_health_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_model_misinformation_on_mandates_public_health_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_misinformation_on_mandates_public_health_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit-model-Misinformation-on-Mandates-Public-Health
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_2021_124m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_2021_124m_pipeline_en.md
new file mode 100644
index 00000000000000..8d0223f0dab8a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_base_2021_124m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_2021_124m_pipeline pipeline RoBertaEmbeddings from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_2021_124m_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_2021_124m_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_2021_124m_pipeline_en_5.4.2_3.0_1725187327371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_2021_124m_pipeline_en_5.4.2_3.0_1725187327371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_base_2021_124m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_2021_124m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_2021_124m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_latest_pipeline_en.md
new file mode 100644
index 00000000000000..f39b8da9d42681
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-twitter_roberta_large_topic_latest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_large_topic_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_large_topic_latest_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_topic_latest_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_topic_latest_pipeline_en_5.5.0_3.0_1725212210052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_topic_latest_pipeline_en_5.5.0_3.0_1725212210052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_large_topic_latest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_large_topic_latest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_large_topic_latest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-large-topic-latest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-video_llava_en.md b/docs/_posts/ahmedlone127/2024-09-01-video_llava_en.md
new file mode 100644
index 00000000000000..c449a6f26577a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-video_llava_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English video_llava CLIPForZeroShotClassification from AnasMohamed
+author: John Snow Labs
+name: video_llava
+date: 2024-09-01
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`video_llava` is a English model originally trained by AnasMohamed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/video_llava_en_5.5.0_3.0_1725226678339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/video_llava_en_5.5.0_3.0_1725226678339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("video_llava","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("video_llava","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|video_llava|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/AnasMohamed/video-llava
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-16_shot_twitter_en.md b/docs/_posts/ahmedlone127/2024-09-02-16_shot_twitter_en.md
new file mode 100644
index 00000000000000..6f79713138b224
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-16_shot_twitter_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 16_shot_twitter MPNetEmbeddings from Nhat1904
+author: John Snow Labs
+name: 16_shot_twitter
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`16_shot_twitter` is a English model originally trained by Nhat1904.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/16_shot_twitter_en_5.5.0_3.0_1725313665094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/16_shot_twitter_en_5.5.0_3.0_1725313665094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("16_shot_twitter","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("16_shot_twitter","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|16_shot_twitter|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Nhat1904/16-shot-twitter
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-16_shot_twitter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-16_shot_twitter_pipeline_en.md
new file mode 100644
index 00000000000000..e9bcc1166a9832
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-16_shot_twitter_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 16_shot_twitter_pipeline pipeline MPNetEmbeddings from Nhat1904
+author: John Snow Labs
+name: 16_shot_twitter_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`16_shot_twitter_pipeline` is a English model originally trained by Nhat1904.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/16_shot_twitter_pipeline_en_5.5.0_3.0_1725313685643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/16_shot_twitter_pipeline_en_5.5.0_3.0_1725313685643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("16_shot_twitter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("16_shot_twitter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|16_shot_twitter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Nhat1904/16-shot-twitter
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-4_datasets_fake_news_with_balanced_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-4_datasets_fake_news_with_balanced_pipeline_en.md
new file mode 100644
index 00000000000000..1f82039f1ec845
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-4_datasets_fake_news_with_balanced_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 4_datasets_fake_news_with_balanced_pipeline pipeline DistilBertForSequenceClassification from littlepinhorse
+author: John Snow Labs
+name: 4_datasets_fake_news_with_balanced_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`4_datasets_fake_news_with_balanced_pipeline` is a English model originally trained by littlepinhorse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/4_datasets_fake_news_with_balanced_pipeline_en_5.5.0_3.0_1725305874827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/4_datasets_fake_news_with_balanced_pipeline_en_5.5.0_3.0_1725305874827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("4_datasets_fake_news_with_balanced_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("4_datasets_fake_news_with_balanced_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|4_datasets_fake_news_with_balanced_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/littlepinhorse/4_datasets_fake_news_with_balanced
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-adlhw1qa_roberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-02-adlhw1qa_roberta_large_en.md
new file mode 100644
index 00000000000000..f00686680cf868
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-adlhw1qa_roberta_large_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English adlhw1qa_roberta_large BertForQuestionAnswering from wanling1212
+author: John Snow Labs
+name: adlhw1qa_roberta_large
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adlhw1qa_roberta_large` is a English model originally trained by wanling1212.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adlhw1qa_roberta_large_en_5.5.0_3.0_1725312445885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adlhw1qa_roberta_large_en_5.5.0_3.0_1725312445885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("adlhw1qa_roberta_large","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("adlhw1qa_roberta_large", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adlhw1qa_roberta_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/wanling1212/ADLHW1QA_roberta_large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-afro_xlmr_mini_finetuned_kintweetsb_en.md b/docs/_posts/ahmedlone127/2024-09-02-afro_xlmr_mini_finetuned_kintweetsb_en.md
new file mode 100644
index 00000000000000..58cd2db4deb45c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-afro_xlmr_mini_finetuned_kintweetsb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afro_xlmr_mini_finetuned_kintweetsb XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: afro_xlmr_mini_finetuned_kintweetsb
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_mini_finetuned_kintweetsb` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_kintweetsb_en_5.5.0_3.0_1725271671365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_kintweetsb_en_5.5.0_3.0_1725271671365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_mini_finetuned_kintweetsb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_mini_finetuned_kintweetsb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_mini_finetuned_kintweetsb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|443.1 MB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-mini-finetuned-kintweetsB
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_batch_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_batch_1_en.md
new file mode 100644
index 00000000000000..0125b62bfabf16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_1_batch_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_base_qa_1_batch_1 AlbertForQuestionAnswering from mateiaass
+author: John Snow Labs
+name: albert_base_qa_1_batch_1
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_1_batch_1` is a English model originally trained by mateiaass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_batch_1_en_5.5.0_3.0_1725310118678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_1_batch_1_en_5.5.0_3.0_1725310118678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_1_batch_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_1_batch_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_qa_1_batch_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/mateiaass/albert-base-qa-1-batch-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_k_fold_4_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_k_fold_4_en.md
new file mode 100644
index 00000000000000..79fae916594fd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_k_fold_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_base_qa_2_k_fold_4 AlbertForQuestionAnswering from mateiaass
+author: John Snow Labs
+name: albert_base_qa_2_k_fold_4
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_k_fold_4` is a English model originally trained by mateiaass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_4_en_5.5.0_3.0_1725309749743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_4_en_5.5.0_3.0_1725309749743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_k_fold_4","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_k_fold_4", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_qa_2_k_fold_4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/mateiaass/albert-base-qa-2-k-fold-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_k_fold_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_k_fold_4_pipeline_en.md
new file mode 100644
index 00000000000000..a67a34151fcf38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_k_fold_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English albert_base_qa_2_k_fold_4_pipeline pipeline AlbertForQuestionAnswering from mateiaass
+author: John Snow Labs
+name: albert_base_qa_2_k_fold_4_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_k_fold_4_pipeline` is a English model originally trained by mateiaass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_4_pipeline_en_5.5.0_3.0_1725309752120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_4_pipeline_en_5.5.0_3.0_1725309752120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_qa_2_k_fold_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_qa_2_k_fold_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_qa_2_k_fold_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/mateiaass/albert-base-qa-2-k-fold-4
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_lr_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_lr_1_en.md
new file mode 100644
index 00000000000000..daea51aa8f1d34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_base_qa_2_lr_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_base_qa_2_lr_1 AlbertForQuestionAnswering from mateiaass
+author: John Snow Labs
+name: albert_base_qa_2_lr_1
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_lr_1` is a English model originally trained by mateiaass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_lr_1_en_5.5.0_3.0_1725309657617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_lr_1_en_5.5.0_3.0_1725309657617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_lr_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_2_lr_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_qa_2_lr_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/mateiaass/albert-base-qa-2-lr-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_finetuned_subjqa_chennaiqa_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_finetuned_subjqa_chennaiqa_en.md
new file mode 100644
index 00000000000000..0db1d9bf95b2f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_finetuned_subjqa_chennaiqa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_finetuned_subjqa_chennaiqa AlbertForQuestionAnswering from aditi2212
+author: John Snow Labs
+name: albert_finetuned_subjqa_chennaiqa
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_finetuned_subjqa_chennaiqa` is a English model originally trained by aditi2212.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_finetuned_subjqa_chennaiqa_en_5.5.0_3.0_1725310024515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_finetuned_subjqa_chennaiqa_en_5.5.0_3.0_1725310024515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_finetuned_subjqa_chennaiqa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_finetuned_subjqa_chennaiqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_finetuned_subjqa_chennaiqa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/aditi2212/albert-finetuned-subjqa-ChennaiQA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_finetuned_subjqa_chennaiqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_finetuned_subjqa_chennaiqa_pipeline_en.md
new file mode 100644
index 00000000000000..752b2fed231f22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_finetuned_subjqa_chennaiqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English albert_finetuned_subjqa_chennaiqa_pipeline pipeline AlbertForQuestionAnswering from aditi2212
+author: John Snow Labs
+name: albert_finetuned_subjqa_chennaiqa_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_finetuned_subjqa_chennaiqa_pipeline` is a English model originally trained by aditi2212.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_finetuned_subjqa_chennaiqa_pipeline_en_5.5.0_3.0_1725310026923.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_finetuned_subjqa_chennaiqa_pipeline_en_5.5.0_3.0_1725310026923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_finetuned_subjqa_chennaiqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_finetuned_subjqa_chennaiqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_finetuned_subjqa_chennaiqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/aditi2212/albert-finetuned-subjqa-ChennaiQA
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-02-albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline_fa.md
new file mode 100644
index 00000000000000..bb295d61424844
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline_fa.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Persian albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline pipeline AlbertForSequenceClassification from m3hrdadfi
+author: John Snow Labs
+name: albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline
+date: 2024-09-02
+tags: [fa, open_source, pipeline, onnx]
+task: Text Classification
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline` is a Persian model originally trained by m3hrdadfi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline_fa_5.5.0_3.0_1725279149531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline_fa_5.5.0_3.0_1725279149531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_persian_farsi_base_v2_sentiment_deepsentipers_binary_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|68.6 MB|
+
+## References
+
+https://huggingface.co/m3hrdadfi/albert-fa-base-v2-sentiment-deepsentipers-binary
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_persian_poetry_fa.md b/docs/_posts/ahmedlone127/2024-09-02-albert_persian_poetry_fa.md
new file mode 100644
index 00000000000000..a0682d50cd376f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_persian_poetry_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian albert_persian_poetry AlbertEmbeddings from mitra-mir
+author: John Snow Labs
+name: albert_persian_poetry
+date: 2024-09-02
+tags: [fa, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_persian_poetry` is a Persian model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_persian_poetry_fa_5.5.0_3.0_1725306632468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_persian_poetry_fa_5.5.0_3.0_1725306632468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("albert_persian_poetry","fa") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("albert_persian_poetry","fa") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_persian_poetry|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|fa|
+|Size:|41.9 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/ALBERT-Persian-Poetry
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_poa_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_poa_en.md
new file mode 100644
index 00000000000000..9003186550268d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_poa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_poa AlbertForQuestionAnswering from sabrinah
+author: John Snow Labs
+name: albert_poa
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_poa` is a English model originally trained by sabrinah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_poa_en_5.5.0_3.0_1725309657395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_poa_en_5.5.0_3.0_1725309657395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_poa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_poa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_poa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/sabrinah/ALBERT-PoA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_poa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-albert_poa_pipeline_en.md
new file mode 100644
index 00000000000000..20c34c211322fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_poa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English albert_poa_pipeline pipeline AlbertForQuestionAnswering from sabrinah
+author: John Snow Labs
+name: albert_poa_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_poa_pipeline` is a English model originally trained by sabrinah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_poa_pipeline_en_5.5.0_3.0_1725309659771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_poa_pipeline_en_5.5.0_3.0_1725309659771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_poa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_poa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_poa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/sabrinah/ALBERT-PoA
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_qa_turkish_squad_tr.md b/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_qa_turkish_squad_tr.md
new file mode 100644
index 00000000000000..8b89314f0c05e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-albert_turkish_qa_turkish_squad_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish albert_turkish_qa_turkish_squad AlbertForQuestionAnswering from anilguven
+author: John Snow Labs
+name: albert_turkish_qa_turkish_squad
+date: 2024-09-02
+tags: [tr, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_turkish_qa_turkish_squad` is a Turkish model originally trained by anilguven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_turkish_qa_turkish_squad_tr_5.5.0_3.0_1725310051122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_turkish_qa_turkish_squad_tr_5.5.0_3.0_1725310051122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_turkish_qa_turkish_squad","tr") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_turkish_qa_turkish_squad", "tr")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_turkish_qa_turkish_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|42.9 MB|
+
+## References
+
+https://huggingface.co/anilguven/albert_tr_qa_turkish_squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-alberta_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-02-alberta_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..4f0588a58e1787
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-alberta_finetuned_squadv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English alberta_finetuned_squadv2 AlbertForQuestionAnswering from quocviethere
+author: John Snow Labs
+name: alberta_finetuned_squadv2
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alberta_finetuned_squadv2` is a English model originally trained by quocviethere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alberta_finetuned_squadv2_en_5.5.0_3.0_1725310015735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alberta_finetuned_squadv2_en_5.5.0_3.0_1725310015735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("alberta_finetuned_squadv2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("alberta_finetuned_squadv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|alberta_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/quocviethere/alberta-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-alberta_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-alberta_finetuned_squadv2_pipeline_en.md
new file mode 100644
index 00000000000000..20ef5ebd33a034
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-alberta_finetuned_squadv2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English alberta_finetuned_squadv2_pipeline pipeline AlbertForQuestionAnswering from quocviethere
+author: John Snow Labs
+name: alberta_finetuned_squadv2_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alberta_finetuned_squadv2_pipeline` is a English model originally trained by quocviethere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alberta_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725310018165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alberta_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725310018165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("alberta_finetuned_squadv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("alberta_finetuned_squadv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|alberta_finetuned_squadv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/quocviethere/alberta-finetuned-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_128_20_mnsr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_128_20_mnsr_pipeline_en.md
new file mode 100644
index 00000000000000..aacf1bfde27dcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_128_20_mnsr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_128_20_mnsr_pipeline pipeline MPNetEmbeddings from ronanki
+author: John Snow Labs
+name: all_mpnet_base_128_20_mnsr_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_128_20_mnsr_pipeline` is a English model originally trained by ronanki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_128_20_mnsr_pipeline_en_5.5.0_3.0_1725314238129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_128_20_mnsr_pipeline_en_5.5.0_3.0_1725314238129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_mpnet_base_128_20_mnsr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_128_20_mnsr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_128_20_mnsr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/ronanki/all_mpnet_base_128_20_MNSR
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_fine_tuned_5_textbook_grobid_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_fine_tuned_5_textbook_grobid_en.md
new file mode 100644
index 00000000000000..b56b792fbbe045
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_fine_tuned_5_textbook_grobid_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_fine_tuned_5_textbook_grobid MPNetEmbeddings from AhmetAytar
+author: John Snow Labs
+name: all_mpnet_base_v2_fine_tuned_5_textbook_grobid
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_fine_tuned_5_textbook_grobid` is a English model originally trained by AhmetAytar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_5_textbook_grobid_en_5.5.0_3.0_1725281029102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_5_textbook_grobid_en_5.5.0_3.0_1725281029102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_fine_tuned_5_textbook_grobid","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_fine_tuned_5_textbook_grobid","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_fine_tuned_5_textbook_grobid|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|929.3 KB|
+
+## References
+
+https://huggingface.co/AhmetAytar/all-mpnet-base-v2-fine-tuned_5_textbook_grobid
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_sts_romaniox_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_sts_romaniox_pipeline_en.md
new file mode 100644
index 00000000000000..47aa72a819915f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-all_mpnet_base_v2_sts_romaniox_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_sts_romaniox_pipeline pipeline MPNetEmbeddings from Romaniox
+author: John Snow Labs
+name: all_mpnet_base_v2_sts_romaniox_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_sts_romaniox_pipeline` is a English model originally trained by Romaniox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_sts_romaniox_pipeline_en_5.5.0_3.0_1725280578000.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_sts_romaniox_pipeline_en_5.5.0_3.0_1725280578000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_sts_romaniox_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_sts_romaniox_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_sts_romaniox_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/Romaniox/all-mpnet-base-v2-sts
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-applicruiter_model_en.md b/docs/_posts/ahmedlone127/2024-09-02-applicruiter_model_en.md
new file mode 100644
index 00000000000000..97e7ea8cf10f53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-applicruiter_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English applicruiter_model MPNetEmbeddings from spencerkifell
+author: John Snow Labs
+name: applicruiter_model
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`applicruiter_model` is a English model originally trained by spencerkifell.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/applicruiter_model_en_5.5.0_3.0_1725313841835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/applicruiter_model_en_5.5.0_3.0_1725313841835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("applicruiter_model","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("applicruiter_model","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|applicruiter_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/spencerkifell/applicruiter-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-applicruiter_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-applicruiter_model_pipeline_en.md
new file mode 100644
index 00000000000000..88c253111cb9b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-applicruiter_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English applicruiter_model_pipeline pipeline MPNetEmbeddings from spencerkifell
+author: John Snow Labs
+name: applicruiter_model_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`applicruiter_model_pipeline` is a English model originally trained by spencerkifell.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/applicruiter_model_pipeline_en_5.5.0_3.0_1725313863599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/applicruiter_model_pipeline_en_5.5.0_3.0_1725313863599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("applicruiter_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("applicruiter_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|applicruiter_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/spencerkifell/applicruiter-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-ascle_english_spanish_ufal_marianmt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-ascle_english_spanish_ufal_marianmt_pipeline_en.md
new file mode 100644
index 00000000000000..1b37e487341b40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-ascle_english_spanish_ufal_marianmt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ascle_english_spanish_ufal_marianmt_pipeline pipeline MarianTransformer from li-lab
+author: John Snow Labs
+name: ascle_english_spanish_ufal_marianmt_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ascle_english_spanish_ufal_marianmt_pipeline` is a English model originally trained by li-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ascle_english_spanish_ufal_marianmt_pipeline_en_5.5.0_3.0_1725295347860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ascle_english_spanish_ufal_marianmt_pipeline_en_5.5.0_3.0_1725295347860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ascle_english_spanish_ufal_marianmt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ascle_english_spanish_ufal_marianmt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ascle_english_spanish_ufal_marianmt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.2 MB|
+
+## References
+
+https://huggingface.co/li-lab/ascle-en-es-UFAL-MarianMT
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_klue_tc_base_multilingual_cased_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_klue_tc_base_multilingual_cased_en.md
new file mode 100644
index 00000000000000..744c04d0de2bcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_klue_tc_base_multilingual_cased_en.md
@@ -0,0 +1,99 @@
+---
+layout: model
+title: English BertForSequenceClassification Base Cased model (from seongju)
+author: John Snow Labs
+name: bert_classifier_klue_tc_base_multilingual_cased
+date: 2024-09-02
+tags: [bert, sequence_classification, classification, open_source, en, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `klue-tc-bert-base-multilingual-cased` is a English model originally trained by `seongju`.
+
+## Predicted Entities
+
+`경제`, `사회`, `생활문화`, `IT과학`, `세계`, `스포츠`, `정치`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_klue_tc_base_multilingual_cased_en_5.5.0_3.0_1725293586085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_klue_tc_base_multilingual_cased_en_5.5.0_3.0_1725293586085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_klue_tc_base_multilingual_cased","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_klue_tc_base_multilingual_cased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded))
+
+val data = Seq("PUT YOUR STRING HERE").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_klue_tc_base_multilingual_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|667.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/seongju/klue-tc-bert-base-multilingual-cased
+- https://klue-benchmark.com/tasks/66/overview/description
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub1_pipeline_en.md
new file mode 100644
index 00000000000000..82b7094cf424f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sanskrit_saskta_sub1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_sanskrit_saskta_sub1_pipeline pipeline BertForSequenceClassification from researchaccount
+author: John Snow Labs
+name: bert_classifier_sanskrit_saskta_sub1_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub1_pipeline` is a English model originally trained by researchaccount.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub1_pipeline_en_5.5.0_3.0_1725293383758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub1_pipeline_en_5.5.0_3.0_1725293383758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_classifier_sanskrit_saskta_sub1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_sanskrit_saskta_sub1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sanskrit_saskta_sub1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|610.9 MB|
+
+## References
+
+https://huggingface.co/researchaccount/sa_sub1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_384_a_12_wnli_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_384_a_12_wnli_en.md
new file mode 100644
index 00000000000000..08a98a87723164
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_384_a_12_wnli_en.md
@@ -0,0 +1,111 @@
+---
+layout: model
+title: English BertForSequenceClassification Cased model (from course5i)
+author: John Snow Labs
+name: bert_classifier_sead_l_6_h_384_a_12_wnli
+date: 2024-09-02
+tags: [en, open_source, bert, sequence_classification, classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `SEAD-L-6_H-384_A-12-wnli` is a English model originally trained by `course5i`.
+
+## Predicted Entities
+
+`0`, `1`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_wnli_en_5.5.0_3.0_1725293789811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_wnli_en_5.5.0_3.0_1725293789811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_384_a_12_wnli","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_384_a_12_wnli","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.classify.bert.wnli_glue.6l_384d_a12a").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sead_l_6_h_384_a_12_wnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|84.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/course5i/SEAD-L-6_H-384_A-12-wnli
+- https://arxiv.org/abs/1910.01108
+- https://arxiv.org/abs/1909.10351
+- https://arxiv.org/abs/2002.10957
+- https://arxiv.org/abs/1810.04805
+- https://arxiv.org/abs/1804.07461
+- https://arxiv.org/abs/1905.00537
+- https://www.adasci.org/journals/lattice-35309407/?volumes=true&open=621a3b18edc4364e8a96cb63
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline_en.md
new file mode 100644
index 00000000000000..f23b8d2c9baa32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline pipeline BertForSequenceClassification from course5i
+author: John Snow Labs
+name: bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline` is a English model originally trained by course5i.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline_en_5.5.0_3.0_1725293794620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline_en_5.5.0_3.0_1725293794620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sead_l_6_h_384_a_12_wnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.2 MB|
+
+## References
+
+https://huggingface.co/course5i/SEAD-L-6_H-384_A-12-wnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_en.md
new file mode 100644
index 00000000000000..be2262914f7764
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined DistilBertForSequenceClassification from ArafatBHossain
+author: John Snow Labs
+name: bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined` is a English model originally trained by ArafatBHossain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_en_5.5.0_3.0_1725305877268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_en_5.5.0_3.0_1725305877268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ArafatBHossain/bert-distilled-multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0.8_refined
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline_en.md
new file mode 100644
index 00000000000000..7c3f32699e17be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline pipeline DistilBertForSequenceClassification from ArafatBHossain
+author: John Snow Labs
+name: bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline` is a English model originally trained by ArafatBHossain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline_en_5.5.0_3.0_1725305890555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline_en_5.5.0_3.0_1725305890555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_distilled_multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0_8_refined_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ArafatBHossain/bert-distilled-multi_teacher_model_flip_twitter_sentiment_epoch7_alpha0.8_refined
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_finetuned_cuad_legalbert1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_finetuned_cuad_legalbert1_pipeline_en.md
new file mode 100644
index 00000000000000..8bd8cc30471300
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_finetuned_cuad_legalbert1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_cuad_legalbert1_pipeline pipeline BertForQuestionAnswering from Jasu
+author: John Snow Labs
+name: bert_finetuned_cuad_legalbert1_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_cuad_legalbert1_pipeline` is a English model originally trained by Jasu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_cuad_legalbert1_pipeline_en_5.5.0_3.0_1725312874086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_cuad_legalbert1_pipeline_en_5.5.0_3.0_1725312874086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_cuad_legalbert1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_cuad_legalbert1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_cuad_legalbert1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/Jasu/bert-finetuned-cuad-legalbert1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_italian_uncased_question_answering_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-02-bert_italian_uncased_question_answering_pipeline_it.md
new file mode 100644
index 00000000000000..7ad0b9615dbfd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_italian_uncased_question_answering_pipeline_it.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Italian bert_italian_uncased_question_answering_pipeline pipeline BertForQuestionAnswering from osiria
+author: John Snow Labs
+name: bert_italian_uncased_question_answering_pipeline
+date: 2024-09-02
+tags: [it, open_source, pipeline, onnx]
+task: Question Answering
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_italian_uncased_question_answering_pipeline` is a Italian model originally trained by osiria.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_italian_uncased_question_answering_pipeline_it_5.5.0_3.0_1725312710398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_italian_uncased_question_answering_pipeline_it_5.5.0_3.0_1725312710398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_italian_uncased_question_answering_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_italian_uncased_question_answering_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_italian_uncased_question_answering_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/osiria/bert-italian-uncased-question-answering
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_mini_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_mini_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..4e5f0ce0a4f1f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_mini_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_mini_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_mini_uncased_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_uncased_pipeline_en_5.5.0_3.0_1725318491784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_uncased_pipeline_en_5.5.0_3.0_1725318491784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_mini_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_mini_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_mini_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|41.9 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-mini-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_persian_farsi_zwnj_base_fa.md b/docs/_posts/ahmedlone127/2024-09-02-bert_persian_farsi_zwnj_base_fa.md
new file mode 100644
index 00000000000000..159913320f5b11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_persian_farsi_zwnj_base_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian bert_persian_farsi_zwnj_base BertEmbeddings from HooshvareLab
+author: John Snow Labs
+name: bert_persian_farsi_zwnj_base
+date: 2024-09-02
+tags: [fa, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_persian_farsi_zwnj_base` is a Persian model originally trained by HooshvareLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_persian_farsi_zwnj_base_fa_5.5.0_3.0_1725315007160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_persian_farsi_zwnj_base_fa_5.5.0_3.0_1725315007160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_persian_farsi_zwnj_base","fa") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_persian_farsi_zwnj_base","fa") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_persian_farsi_zwnj_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|fa|
+|Size:|441.6 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/bert-fa-zwnj-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_persian_farsi_zwnj_base_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-02-bert_persian_farsi_zwnj_base_pipeline_fa.md
new file mode 100644
index 00000000000000..e38360a3ee020b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_persian_farsi_zwnj_base_pipeline_fa.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Persian bert_persian_farsi_zwnj_base_pipeline pipeline BertEmbeddings from HooshvareLab
+author: John Snow Labs
+name: bert_persian_farsi_zwnj_base_pipeline
+date: 2024-09-02
+tags: [fa, open_source, pipeline, onnx]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_persian_farsi_zwnj_base_pipeline` is a Persian model originally trained by HooshvareLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_persian_farsi_zwnj_base_pipeline_fa_5.5.0_3.0_1725315029161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_persian_farsi_zwnj_base_pipeline_fa_5.5.0_3.0_1725315029161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_persian_farsi_zwnj_base_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_persian_farsi_zwnj_base_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_persian_farsi_zwnj_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|441.6 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/bert-fa-zwnj-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_qa_wskhanh_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bert_qa_wskhanh_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..2eddf93fb3fa17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_qa_wskhanh_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_qa_wskhanh_finetuned_squad_pipeline pipeline BertForQuestionAnswering from wskhanh
+author: John Snow Labs
+name: bert_qa_wskhanh_finetuned_squad_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_wskhanh_finetuned_squad_pipeline` is a English model originally trained by wskhanh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_wskhanh_finetuned_squad_pipeline_en_5.5.0_3.0_1725312757887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_wskhanh_finetuned_squad_pipeline_en_5.5.0_3.0_1725312757887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_qa_wskhanh_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_qa_wskhanh_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_wskhanh_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/wskhanh/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_sequence_classifier_rubert_sentiment_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-02-bert_sequence_classifier_rubert_sentiment_pipeline_ru.md
new file mode 100644
index 00000000000000..541e60efbd38f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_sequence_classifier_rubert_sentiment_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian bert_sequence_classifier_rubert_sentiment_pipeline pipeline BertForSequenceClassification from blanchefort
+author: John Snow Labs
+name: bert_sequence_classifier_rubert_sentiment_pipeline
+date: 2024-09-02
+tags: [ru, open_source, pipeline, onnx]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_rubert_sentiment_pipeline` is a Russian model originally trained by blanchefort.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_rubert_sentiment_pipeline_ru_5.5.0_3.0_1725293904409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_rubert_sentiment_pipeline_ru_5.5.0_3.0_1725293904409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_sequence_classifier_rubert_sentiment_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_sequence_classifier_rubert_sentiment_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_sequence_classifier_rubert_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|664.5 MB|
+
+## References
+
+https://huggingface.co/blanchefort/rubert-base-cased-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bert_squad_portuguese_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-02-bert_squad_portuguese_pipeline_pt.md
new file mode 100644
index 00000000000000..f973de5b69ae99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bert_squad_portuguese_pipeline_pt.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Portuguese bert_squad_portuguese_pipeline pipeline BertForQuestionAnswering from rhaymison
+author: John Snow Labs
+name: bert_squad_portuguese_pipeline
+date: 2024-09-02
+tags: [pt, open_source, pipeline, onnx]
+task: Question Answering
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad_portuguese_pipeline` is a Portuguese model originally trained by rhaymison.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_portuguese_pipeline_pt_5.5.0_3.0_1725313145411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_portuguese_pipeline_pt_5.5.0_3.0_1725313145411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_squad_portuguese_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_squad_portuguese_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_squad_portuguese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/rhaymison/bert-squad-portuguese
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_32_42_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_32_42_pipeline_en.md
new file mode 100644
index 00000000000000..cb1489ad09a7c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-best_model_yelp_polarity_32_42_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English best_model_yelp_polarity_32_42_pipeline pipeline AlbertForSequenceClassification from simonycl
+author: John Snow Labs
+name: best_model_yelp_polarity_32_42_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_yelp_polarity_32_42_pipeline` is a English model originally trained by simonycl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_32_42_pipeline_en_5.5.0_3.0_1725301250208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_32_42_pipeline_en_5.5.0_3.0_1725301250208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("best_model_yelp_polarity_32_42_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("best_model_yelp_polarity_32_42_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|best_model_yelp_polarity_32_42_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/simonycl/best_model-yelp_polarity-32-42
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_trivia_anchor_positive_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_trivia_anchor_positive_pipeline_en.md
new file mode 100644
index 00000000000000..51631df3b034d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_trivia_anchor_positive_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_english_trivia_anchor_positive_pipeline pipeline BGEEmbeddings from SepKeyPro
+author: John Snow Labs
+name: bge_base_english_trivia_anchor_positive_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_trivia_anchor_positive_pipeline` is a English model originally trained by SepKeyPro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_trivia_anchor_positive_pipeline_en_5.5.0_3.0_1725240955809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_trivia_anchor_positive_pipeline_en_5.5.0_3.0_1725240955809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_english_trivia_anchor_positive_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_english_trivia_anchor_positive_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_trivia_anchor_positive_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.3 MB|
+
+## References
+
+https://huggingface.co/SepKeyPro/bge-base-en-trivia-anchor-positive
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_en.md
new file mode 100644
index 00000000000000..3a2502ec2db97c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_klej_dyk BGEEmbeddings from ve88ifz2
+author: John Snow Labs
+name: bge_base_english_v1_5_klej_dyk
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_klej_dyk` is a English model originally trained by ve88ifz2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_klej_dyk_en_5.5.0_3.0_1725241954932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_klej_dyk_en_5.5.0_3.0_1725241954932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_klej_dyk","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_klej_dyk","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_klej_dyk|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|385.5 MB|
+
+## References
+
+https://huggingface.co/ve88ifz2/bge-base-en-v1.5-klej-dyk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_v0_2_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_v0_2_en.md
new file mode 100644
index 00000000000000..9c2f83ecdc1e4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_english_v1_5_klej_dyk_v0_2_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_klej_dyk_v0_2 BGEEmbeddings from ve88ifz2
+author: John Snow Labs
+name: bge_base_english_v1_5_klej_dyk_v0_2
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_klej_dyk_v0_2` is a English model originally trained by ve88ifz2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_klej_dyk_v0_2_en_5.5.0_3.0_1725242094780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_klej_dyk_v0_2_en_5.5.0_3.0_1725242094780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_klej_dyk_v0_2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_klej_dyk_v0_2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_klej_dyk_v0_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|385.6 MB|
+
+## References
+
+https://huggingface.co/ve88ifz2/bge-base-en-v1.5-klej-dyk-v0.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_naruke_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_naruke_en.md
new file mode 100644
index 00000000000000..231ae715bec5b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_financial_matryoshka_naruke_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_naruke BGEEmbeddings from Naruke
+author: John Snow Labs
+name: bge_base_financial_matryoshka_naruke
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_naruke` is a English model originally trained by Naruke.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_naruke_en_5.5.0_3.0_1725263201322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_naruke_en_5.5.0_3.0_1725263201322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_naruke","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_naruke","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_naruke|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.0 MB|
+
+## References
+
+https://huggingface.co/Naruke/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_mbpp_processed_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_mbpp_processed_en.md
new file mode 100644
index 00000000000000..038799a625306e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_mbpp_processed_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_mbpp_processed BGEEmbeddings from Nutanix
+author: John Snow Labs
+name: bge_base_mbpp_processed
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_mbpp_processed` is a English model originally trained by Nutanix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_mbpp_processed_en_5.5.0_3.0_1725262870686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_mbpp_processed_en_5.5.0_3.0_1725262870686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_mbpp_processed","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_mbpp_processed","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_mbpp_processed|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|377.8 MB|
+
+## References
+
+https://huggingface.co/Nutanix/bge-base-mbpp-processed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v17_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v17_pipeline_en.md
new file mode 100644
index 00000000000000..154eb6a97060e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v17_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_securiti_dataset_1_v17_pipeline pipeline BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_securiti_dataset_1_v17_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v17_pipeline` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v17_pipeline_en_5.5.0_3.0_1725241957827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v17_pipeline_en_5.5.0_3.0_1725241957827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_securiti_dataset_1_v17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|384.3 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v17
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v22_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v22_pipeline_en.md
new file mode 100644
index 00000000000000..964724030a8783
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bge_base_securiti_dataset_1_v22_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_securiti_dataset_1_v22_pipeline pipeline BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_securiti_dataset_1_v22_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v22_pipeline` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v22_pipeline_en_5.5.0_3.0_1725263507229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v22_pipeline_en_5.5.0_3.0_1725263507229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v22_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v22_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_securiti_dataset_1_v22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|384.8 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v22
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bge_large_chatbot_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-02-bge_large_chatbot_matryoshka_en.md
new file mode 100644
index 00000000000000..9f22f6d2c817e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bge_large_chatbot_matryoshka_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_large_chatbot_matryoshka BGEEmbeddings from MANMEET75
+author: John Snow Labs
+name: bge_large_chatbot_matryoshka
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_chatbot_matryoshka` is a English model originally trained by MANMEET75.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_chatbot_matryoshka_en_5.5.0_3.0_1725241364948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_chatbot_matryoshka_en_5.5.0_3.0_1725241364948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_large_chatbot_matryoshka","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_large_chatbot_matryoshka","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_large_chatbot_matryoshka|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/MANMEET75/bge-large-Chatbot-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bias_model_title_en.md b/docs/_posts/ahmedlone127/2024-09-02-bias_model_title_en.md
new file mode 100644
index 00000000000000..60b12af2d4adf5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bias_model_title_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bias_model_title DistilBertForSequenceClassification from najeebY
+author: John Snow Labs
+name: bias_model_title
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_model_title` is a English model originally trained by najeebY.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_model_title_en_5.5.0_3.0_1725291893476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_model_title_en_5.5.0_3.0_1725291893476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bias_model_title","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bias_model_title", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_model_title|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/najeebY/bias_model_title
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bias_model_title_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-bias_model_title_pipeline_en.md
new file mode 100644
index 00000000000000..20e0335b838c07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bias_model_title_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bias_model_title_pipeline pipeline DistilBertForSequenceClassification from najeebY
+author: John Snow Labs
+name: bias_model_title_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_model_title_pipeline` is a English model originally trained by najeebY.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_model_title_pipeline_en_5.5.0_3.0_1725291906658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_model_title_pipeline_en_5.5.0_3.0_1725291906658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bias_model_title_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bias_model_title_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_model_title_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/najeebY/bias_model_title
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bsc_bio_ehr_spanish_cantemist_es.md b/docs/_posts/ahmedlone127/2024-09-02-bsc_bio_ehr_spanish_cantemist_es.md
new file mode 100644
index 00000000000000..a74098fbf5276b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bsc_bio_ehr_spanish_cantemist_es.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Castilian, Spanish bsc_bio_ehr_spanish_cantemist RoBertaForSequenceClassification from IIC
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_cantemist
+date: 2024-09-02
+tags: [roberta, es, open_source, sequence_classification, onnx]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_cantemist` is a Castilian, Spanish model originally trained by IIC.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_cantemist_es_5.5.0_3.0_1725311478160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_cantemist_es_5.5.0_3.0_1725311478160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = RoBertaForSequenceClassification.pretrained("bsc_bio_ehr_spanish_cantemist","es")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("bsc_bio_ehr_spanish_cantemist","es")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_cantemist|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|434.8 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/IIC/bsc-bio-ehr-es-cantemist
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-bulbert_chitanka_model_pipeline_bg.md b/docs/_posts/ahmedlone127/2024-09-02-bulbert_chitanka_model_pipeline_bg.md
new file mode 100644
index 00000000000000..533bb8a70828b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-bulbert_chitanka_model_pipeline_bg.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Bulgarian bulbert_chitanka_model_pipeline pipeline BertEmbeddings from mor40
+author: John Snow Labs
+name: bulbert_chitanka_model_pipeline
+date: 2024-09-02
+tags: [bg, open_source, pipeline, onnx]
+task: Embeddings
+language: bg
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bulbert_chitanka_model_pipeline` is a Bulgarian model originally trained by mor40.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bulbert_chitanka_model_pipeline_bg_5.5.0_3.0_1725318533532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bulbert_chitanka_model_pipeline_bg_5.5.0_3.0_1725318533532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bulbert_chitanka_model_pipeline", lang = "bg")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bulbert_chitanka_model_pipeline", lang = "bg")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bulbert_chitanka_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bg|
+|Size:|306.1 MB|
+
+## References
+
+https://huggingface.co/mor40/BulBERT-chitanka-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_cptkorsche_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_cptkorsche_pipeline_en.md
new file mode 100644
index 00000000000000..88bb824d06102e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_cptkorsche_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_cptkorsche_pipeline pipeline DistilBertForSequenceClassification from CptKorsche
+author: John Snow Labs
+name: burmese_awesome_model_cptkorsche_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_cptkorsche_pipeline` is a English model originally trained by CptKorsche.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_cptkorsche_pipeline_en_5.5.0_3.0_1725291874216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_cptkorsche_pipeline_en_5.5.0_3.0_1725291874216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_cptkorsche_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_cptkorsche_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_cptkorsche_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/CptKorsche/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_lukiccc_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_lukiccc_en.md
new file mode 100644
index 00000000000000..39f4fbaa7d9296
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_model_lukiccc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_lukiccc DistilBertForSequenceClassification from Lukiccc
+author: John Snow Labs
+name: burmese_awesome_model_lukiccc
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lukiccc` is a English model originally trained by Lukiccc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lukiccc_en_5.5.0_3.0_1725291769249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lukiccc_en_5.5.0_3.0_1725291769249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lukiccc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lukiccc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lukiccc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lukiccc/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_shivakanthreddy_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_shivakanthreddy_en.md
new file mode 100644
index 00000000000000..7660f70aea2073
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_opus_books_model_shivakanthreddy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_shivakanthreddy MarianTransformer from shivakanthreddy
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_shivakanthreddy
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_shivakanthreddy` is a English model originally trained by shivakanthreddy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_shivakanthreddy_en_5.5.0_3.0_1725295420394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_shivakanthreddy_en_5.5.0_3.0_1725295420394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("burmese_awesome_opus_books_model_shivakanthreddy","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("burmese_awesome_opus_books_model_shivakanthreddy","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_shivakanthreddy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.2 MB|
+
+## References
+
+https://huggingface.co/shivakanthreddy/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_ameer_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_ameer_en.md
new file mode 100644
index 00000000000000..153bfbbf8d5a7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_setfit_model_ameer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_ameer MPNetEmbeddings from ameerak
+author: John Snow Labs
+name: burmese_awesome_setfit_model_ameer
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_ameer` is a English model originally trained by ameerak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_ameer_en_5.5.0_3.0_1725280640370.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_ameer_en_5.5.0_3.0_1725280640370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_ameer","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_ameer","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_ameer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/ameerak/my-awesome-setfit-model-ameer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_arunaramm7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_arunaramm7_pipeline_en.md
new file mode 100644
index 00000000000000..9a03cad6151664
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_arunaramm7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_arunaramm7_pipeline pipeline DistilBertForTokenClassification from arunaramm7
+author: John Snow Labs
+name: burmese_awesome_wnut_model_arunaramm7_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_arunaramm7_pipeline` is a English model originally trained by arunaramm7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_arunaramm7_pipeline_en_5.5.0_3.0_1725267659615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_arunaramm7_pipeline_en_5.5.0_3.0_1725267659615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_arunaramm7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_arunaramm7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_arunaramm7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/arunaramm7/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_costadomar_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_costadomar_en.md
new file mode 100644
index 00000000000000..dc68434e2ca554
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_costadomar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_costadomar DistilBertForTokenClassification from costadomar
+author: John Snow Labs
+name: burmese_awesome_wnut_model_costadomar
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_costadomar` is a English model originally trained by costadomar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_costadomar_en_5.5.0_3.0_1725268035268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_costadomar_en_5.5.0_3.0_1725268035268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_costadomar","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_costadomar", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_costadomar|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/costadomar/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_mohamedfasil_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_mohamedfasil_en.md
new file mode 100644
index 00000000000000..d578c4f2be7348
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_awesome_wnut_model_mohamedfasil_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_mohamedfasil DistilBertForTokenClassification from Mohamedfasil
+author: John Snow Labs
+name: burmese_awesome_wnut_model_mohamedfasil
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_mohamedfasil` is a English model originally trained by Mohamedfasil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_mohamedfasil_en_5.5.0_3.0_1725267533265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_mohamedfasil_en_5.5.0_3.0_1725267533265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_mohamedfasil","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_mohamedfasil", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_mohamedfasil|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Mohamedfasil/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_great_model_haltincay_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_great_model_haltincay_pipeline_en.md
new file mode 100644
index 00000000000000..e5be8f193d0391
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_great_model_haltincay_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_great_model_haltincay_pipeline pipeline DistilBertForSequenceClassification from haltincay
+author: John Snow Labs
+name: burmese_great_model_haltincay_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_great_model_haltincay_pipeline` is a English model originally trained by haltincay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_great_model_haltincay_pipeline_en_5.5.0_3.0_1725291624640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_great_model_haltincay_pipeline_en_5.5.0_3.0_1725291624640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_great_model_haltincay_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_great_model_haltincay_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_great_model_haltincay_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/haltincay/my_great_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_nepal_bhasa_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_nepal_bhasa_ner_pipeline_en.md
new file mode 100644
index 00000000000000..71423ceac4aadd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_nepal_bhasa_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_nepal_bhasa_ner_pipeline pipeline DistilBertForTokenClassification from hcy5561
+author: John Snow Labs
+name: burmese_nepal_bhasa_ner_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_nepal_bhasa_ner_pipeline` is a English model originally trained by hcy5561.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_nepal_bhasa_ner_pipeline_en_5.5.0_3.0_1725267719445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_nepal_bhasa_ner_pipeline_en_5.5.0_3.0_1725267719445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_nepal_bhasa_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_nepal_bhasa_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_nepal_bhasa_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/hcy5561/my_new_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_setfit_model_rajistics_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_setfit_model_rajistics_en.md
new file mode 100644
index 00000000000000..38071f4d0818e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_setfit_model_rajistics_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_setfit_model_rajistics MPNetEmbeddings from rajistics
+author: John Snow Labs
+name: burmese_setfit_model_rajistics
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_setfit_model_rajistics` is a English model originally trained by rajistics.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_setfit_model_rajistics_en_5.5.0_3.0_1725281107644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_setfit_model_rajistics_en_5.5.0_3.0_1725281107644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_setfit_model_rajistics","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_setfit_model_rajistics","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_setfit_model_rajistics|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/rajistics/my-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_setfit_model_rajistics_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_setfit_model_rajistics_pipeline_en.md
new file mode 100644
index 00000000000000..3d0bda27731ff5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_setfit_model_rajistics_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_setfit_model_rajistics_pipeline pipeline MPNetEmbeddings from rajistics
+author: John Snow Labs
+name: burmese_setfit_model_rajistics_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_setfit_model_rajistics_pipeline` is a English model originally trained by rajistics.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_setfit_model_rajistics_pipeline_en_5.5.0_3.0_1725281128728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_setfit_model_rajistics_pipeline_en_5.5.0_3.0_1725281128728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_setfit_model_rajistics_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_setfit_model_rajistics_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_setfit_model_rajistics_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/rajistics/my-setfit-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-burmese_test_repo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-burmese_test_repo_pipeline_en.md
new file mode 100644
index 00000000000000..26a66c6e35e496
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-burmese_test_repo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_test_repo_pipeline pipeline CamemBertEmbeddings from martindevoto
+author: John Snow Labs
+name: burmese_test_repo_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_test_repo_pipeline` is a English model originally trained by martindevoto.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_test_repo_pipeline_en_5.5.0_3.0_1725302578071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_test_repo_pipeline_en_5.5.0_3.0_1725302578071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_test_repo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_test_repo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_test_repo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/martindevoto/my-test-repo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-category_cleaning_clip_clip_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-category_cleaning_clip_clip_finetuned_en.md
new file mode 100644
index 00000000000000..a1d8bd84091087
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-category_cleaning_clip_clip_finetuned_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English category_cleaning_clip_clip_finetuned CLIPForZeroShotClassification from kpalczewski-displate
+author: John Snow Labs
+name: category_cleaning_clip_clip_finetuned
+date: 2024-09-02
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`category_cleaning_clip_clip_finetuned` is a English model originally trained by kpalczewski-displate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/category_cleaning_clip_clip_finetuned_en_5.5.0_3.0_1725275204153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/category_cleaning_clip_clip_finetuned_en_5.5.0_3.0_1725275204153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("category_cleaning_clip_clip_finetuned","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("category_cleaning_clip_clip_finetuned","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|category_cleaning_clip_clip_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|567.3 MB|
+
+## References
+
+https://huggingface.co/kpalczewski-displate/category-cleaning-clip-clip-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-checkpoint_23200_en.md b/docs/_posts/ahmedlone127/2024-09-02-checkpoint_23200_en.md
new file mode 100644
index 00000000000000..78f5b6360cb37d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-checkpoint_23200_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English checkpoint_23200 XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: checkpoint_23200
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkpoint_23200` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoint_23200_en_5.5.0_3.0_1725270917213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoint_23200_en_5.5.0_3.0_1725270917213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("checkpoint_23200","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("checkpoint_23200","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|checkpoint_23200|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-23200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-choubert_2_fr.md b/docs/_posts/ahmedlone127/2024-09-02-choubert_2_fr.md
new file mode 100644
index 00000000000000..ee031515fc96dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-choubert_2_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French choubert_2 CamemBertEmbeddings from ChouBERT
+author: John Snow Labs
+name: choubert_2
+date: 2024-09-02
+tags: [fr, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`choubert_2` is a French model originally trained by ChouBERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/choubert_2_fr_5.5.0_3.0_1725319943780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/choubert_2_fr_5.5.0_3.0_1725319943780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("choubert_2","fr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("choubert_2","fr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|choubert_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|fr|
+|Size:|412.9 MB|
+
+## References
+
+https://huggingface.co/ChouBERT/ChouBERT-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-choubert_2_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-choubert_2_pipeline_fr.md
new file mode 100644
index 00000000000000..19d0b69ecce848
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-choubert_2_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French choubert_2_pipeline pipeline CamemBertEmbeddings from ChouBERT
+author: John Snow Labs
+name: choubert_2_pipeline
+date: 2024-09-02
+tags: [fr, open_source, pipeline, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`choubert_2_pipeline` is a French model originally trained by ChouBERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/choubert_2_pipeline_fr_5.5.0_3.0_1725319964760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/choubert_2_pipeline_fr_5.5.0_3.0_1725319964760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("choubert_2_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("choubert_2_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|choubert_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|412.9 MB|
+
+## References
+
+https://huggingface.co/ChouBERT/ChouBERT-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-choubert_8_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-choubert_8_pipeline_fr.md
new file mode 100644
index 00000000000000..02b13875b9e5ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-choubert_8_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French choubert_8_pipeline pipeline CamemBertEmbeddings from ChouBERT
+author: John Snow Labs
+name: choubert_8_pipeline
+date: 2024-09-02
+tags: [fr, open_source, pipeline, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`choubert_8_pipeline` is a French model originally trained by ChouBERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/choubert_8_pipeline_fr_5.5.0_3.0_1725319749931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/choubert_8_pipeline_fr_5.5.0_3.0_1725319749931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("choubert_8_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("choubert_8_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|choubert_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|412.9 MB|
+
+## References
+
+https://huggingface.co/ChouBERT/ChouBERT-8
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-classifier_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-classifier_camembert_pipeline_en.md
new file mode 100644
index 00000000000000..400a67c601139e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-classifier_camembert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English classifier_camembert_pipeline pipeline CamemBertForSequenceClassification from DioulaD
+author: John Snow Labs
+name: classifier_camembert_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier_camembert_pipeline` is a English model originally trained by DioulaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier_camembert_pipeline_en_5.5.0_3.0_1725299002377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier_camembert_pipeline_en_5.5.0_3.0_1725299002377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("classifier_camembert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("classifier_camembert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classifier_camembert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|389.2 MB|
+
+## References
+
+https://huggingface.co/DioulaD/classifier-camembert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_samim2024_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_samim2024_en.md
new file mode 100644
index 00000000000000..9b3d0583aea53c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-clip_samim2024_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_samim2024 CLIPForZeroShotClassification from samim2024
+author: John Snow Labs
+name: clip_samim2024
+date: 2024-09-02
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_samim2024` is a English model originally trained by samim2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_samim2024_en_5.5.0_3.0_1725257214287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_samim2024_en_5.5.0_3.0_1725257214287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_samim2024","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_samim2024","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_samim2024|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/samim2024/clip
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_demo_fluffypotato_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_demo_fluffypotato_pipeline_en.md
new file mode 100644
index 00000000000000..a80b3b055e6301
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_base_patch32_demo_fluffypotato_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_base_patch32_demo_fluffypotato_pipeline pipeline CLIPForZeroShotClassification from fluffypotato
+author: John Snow Labs
+name: clip_vit_base_patch32_demo_fluffypotato_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_fluffypotato_pipeline` is a English model originally trained by fluffypotato.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_fluffypotato_pipeline_en_5.5.0_3.0_1725275318450.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_fluffypotato_pipeline_en_5.5.0_3.0_1725275318450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_base_patch32_demo_fluffypotato_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_base_patch32_demo_fluffypotato_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_demo_fluffypotato_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/fluffypotato/clip-vit-base-patch32-demo
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..d0b49c372e12d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-clip_vit_large_patch14_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_large_patch14_finetuned_pipeline pipeline CLIPForZeroShotClassification from vinluvie
+author: John Snow Labs
+name: clip_vit_large_patch14_finetuned_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_finetuned_pipeline` is a English model originally trained by vinluvie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_finetuned_pipeline_en_5.5.0_3.0_1725275338409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_finetuned_pipeline_en_5.5.0_3.0_1725275338409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_large_patch14_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_large_patch14_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_large_patch14_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/vinluvie/clip-vit-large-patch14-finetuned
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-conflibert_scr_uncased_snowood1_en.md b/docs/_posts/ahmedlone127/2024-09-02-conflibert_scr_uncased_snowood1_en.md
new file mode 100644
index 00000000000000..65b8e15ff0efab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-conflibert_scr_uncased_snowood1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English conflibert_scr_uncased_snowood1 BertEmbeddings from snowood1
+author: John Snow Labs
+name: conflibert_scr_uncased_snowood1
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conflibert_scr_uncased_snowood1` is a English model originally trained by snowood1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conflibert_scr_uncased_snowood1_en_5.5.0_3.0_1725318530371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conflibert_scr_uncased_snowood1_en_5.5.0_3.0_1725318530371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("conflibert_scr_uncased_snowood1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("conflibert_scr_uncased_snowood1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conflibert_scr_uncased_snowood1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/snowood1/ConfliBERT-scr-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-conflibert_scr_uncased_snowood1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-conflibert_scr_uncased_snowood1_pipeline_en.md
new file mode 100644
index 00000000000000..18bb0e7f2c5215
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-conflibert_scr_uncased_snowood1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English conflibert_scr_uncased_snowood1_pipeline pipeline BertEmbeddings from snowood1
+author: John Snow Labs
+name: conflibert_scr_uncased_snowood1_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conflibert_scr_uncased_snowood1_pipeline` is a English model originally trained by snowood1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conflibert_scr_uncased_snowood1_pipeline_en_5.5.0_3.0_1725318550991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conflibert_scr_uncased_snowood1_pipeline_en_5.5.0_3.0_1725318550991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("conflibert_scr_uncased_snowood1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("conflibert_scr_uncased_snowood1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conflibert_scr_uncased_snowood1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/snowood1/ConfliBERT-scr-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l6_mmarcofr_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l6_mmarcofr_pipeline_fr.md
new file mode 100644
index 00000000000000..76661235d6dc8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-crossencoder_camembert_l6_mmarcofr_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French crossencoder_camembert_l6_mmarcofr_pipeline pipeline CamemBertForSequenceClassification from antoinelouis
+author: John Snow Labs
+name: crossencoder_camembert_l6_mmarcofr_pipeline
+date: 2024-09-02
+tags: [fr, open_source, pipeline, onnx]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_l6_mmarcofr_pipeline` is a French model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l6_mmarcofr_pipeline_fr_5.5.0_3.0_1725299130880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l6_mmarcofr_pipeline_fr_5.5.0_3.0_1725299130880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("crossencoder_camembert_l6_mmarcofr_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("crossencoder_camembert_l6_mmarcofr_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crossencoder_camembert_l6_mmarcofr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|255.3 MB|
+
+## References
+
+https://huggingface.co/antoinelouis/crossencoder-camembert-L6-mmarcoFR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline_en.md
new file mode 100644
index 00000000000000..aae1c21ed05c7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline pipeline CamemBertForTokenClassification from Easter-Island
+author: John Snow Labs
+name: dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline` is a English model originally trained by Easter-Island.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline_en_5.5.0_3.0_1725266965733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline_en_5.5.0_3.0_1725266965733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbg_myriade_10k_mots_all_sens_multilabel_3phrases_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Easter-Island/dbg_myriade_10k_mots_all_sens_multilabel_3phrases
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_finetuned_squad2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_finetuned_squad2_pipeline_en.md
new file mode 100644
index 00000000000000..46aa37e69955d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_finetuned_squad2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_squad2_pipeline pipeline DeBertaForQuestionAnswering from IProject-10
+author: John Snow Labs
+name: deberta_v3_base_finetuned_squad2_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_squad2_pipeline` is a English model originally trained by IProject-10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_squad2_pipeline_en_5.5.0_3.0_1725240223671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_squad2_pipeline_en_5.5.0_3.0_1725240223671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_finetuned_squad2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_squad2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_squad2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|658.8 MB|
+
+## References
+
+https://huggingface.co/IProject-10/deberta-v3-base-finetuned-squad2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DeBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_mnli_uf_ner_1019_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_mnli_uf_ner_1019_v1_en.md
new file mode 100644
index 00000000000000..9edc9a3c6f452c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_mnli_uf_ner_1019_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_mnli_uf_ner_1019_v1 DeBertaForSequenceClassification from mariolinml
+author: John Snow Labs
+name: deberta_v3_base_mnli_uf_ner_1019_v1
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mnli_uf_ner_1019_v1` is a English model originally trained by mariolinml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_uf_ner_1019_v1_en_5.5.0_3.0_1725283185783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_uf_ner_1019_v1_en_5.5.0_3.0_1725283185783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_mnli_uf_ner_1019_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_mnli_uf_ner_1019_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_mnli_uf_ner_1019_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|639.0 MB|
+
+## References
+
+https://huggingface.co/mariolinml/deberta-v3-base_mnli_uf_ner_1019_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_ext_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_ext_v1_pipeline_en.md
new file mode 100644
index 00000000000000..3fa9b54f8c9cdb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_base_squad2_ext_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deberta_v3_base_squad2_ext_v1_pipeline pipeline DeBertaForQuestionAnswering from sjrhuschlee
+author: John Snow Labs
+name: deberta_v3_base_squad2_ext_v1_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_squad2_ext_v1_pipeline` is a English model originally trained by sjrhuschlee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_ext_v1_pipeline_en_5.5.0_3.0_1725268510592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_squad2_ext_v1_pipeline_en_5.5.0_3.0_1725268510592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_squad2_ext_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_squad2_ext_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_squad2_ext_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|686.9 MB|
+
+## References
+
+https://huggingface.co/sjrhuschlee/deberta-v3-base-squad2-ext-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DeBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_8_7_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_8_7_en.md
new file mode 100644
index 00000000000000..d351091db9cec1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large__sst2__train_8_7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_7 DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_7
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_7` is a English model originally trained by SetFit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_7_en_5.5.0_3.0_1725282186779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_7_en_5.5.0_3.0_1725282186779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_7|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_reram_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_reram_qa_pipeline_en.md
new file mode 100644
index 00000000000000..8d37116d285cf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_reram_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deberta_v3_large_reram_qa_pipeline pipeline DeBertaForQuestionAnswering from GuakGuak
+author: John Snow Labs
+name: deberta_v3_large_reram_qa_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_reram_qa_pipeline` is a English model originally trained by GuakGuak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_reram_qa_pipeline_en_5.5.0_3.0_1725240419173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_reram_qa_pipeline_en_5.5.0_3.0_1725240419173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_reram_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_reram_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_reram_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/GuakGuak/deberta-v3-large-reram-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- DeBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_navteca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_navteca_pipeline_en.md
new file mode 100644
index 00000000000000..ee7210d12827f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_large_squad2_navteca_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deberta_v3_large_squad2_navteca_pipeline pipeline DeBertaForQuestionAnswering from navteca
+author: John Snow Labs
+name: deberta_v3_large_squad2_navteca_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_squad2_navteca_pipeline` is a English model originally trained by navteca.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_navteca_pipeline_en_5.5.0_3.0_1725240044396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_squad2_navteca_pipeline_en_5.5.0_3.0_1725240044396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_squad2_navteca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_squad2_navteca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_squad2_navteca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/navteca/deberta-v3-large-squad2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DeBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_xsmall_squad2_fungi_en.md b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_xsmall_squad2_fungi_en.md
new file mode 100644
index 00000000000000..36cdd7179fa9f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-deberta_v3_xsmall_squad2_fungi_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English deberta_v3_xsmall_squad2_fungi DeBertaForQuestionAnswering from fungi
+author: John Snow Labs
+name: deberta_v3_xsmall_squad2_fungi
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, deberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_squad2_fungi` is a English model originally trained by fungi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_squad2_fungi_en_5.5.0_3.0_1725268878887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_squad2_fungi_en_5.5.0_3.0_1725268878887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_xsmall_squad2_fungi","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DeBertaForQuestionAnswering.pretrained("deberta_v3_xsmall_squad2_fungi", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_squad2_fungi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|244.4 MB|
+
+## References
+
+https://huggingface.co/fungi/deberta-v3-xsmall-squad2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline_en.md
new file mode 100644
index 00000000000000..c34cbb570ec614
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline pipeline DistilBertForSequenceClassification from LeBruse
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline` is a English model originally trained by LeBruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline_en_5.5.0_3.0_1725305537593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline_en_5.5.0_3.0_1725305537593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_english_sarcasm_1_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-english-sarcasm-1.0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_dataset_pipeline_en.md
new file mode 100644
index 00000000000000..4e3363ba49bb9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_dataset_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_dataset_pipeline pipeline DistilBertForSequenceClassification from agoor97
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_dataset_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_dataset_pipeline` is a English model originally trained by agoor97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_dataset_pipeline_en_5.5.0_3.0_1725305634340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_dataset_pipeline_en_5.5.0_3.0_1725305634340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_dataset_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_dataset_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_dataset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/agoor97/distilbert-base-uncased-finetuned-emotions-dataset
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline_en.md
new file mode 100644
index 00000000000000..ac353cd747a914
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline pipeline DistilBertForSequenceClassification from JakeClark
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline` is a English model originally trained by JakeClark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline_en_5.5.0_3.0_1725292337536.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline_en_5.5.0_3.0_1725292337536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_jakeclark_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JakeClark/distilbert-base-uncased-finetuned-emotions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_keitharogo_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_keitharogo_en.md
new file mode 100644
index 00000000000000..0cd575836f8d4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_keitharogo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_keitharogo DistilBertForTokenClassification from KeithArogo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_keitharogo
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_keitharogo` is a English model originally trained by KeithArogo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_keitharogo_en_5.5.0_3.0_1725267657542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_keitharogo_en_5.5.0_3.0_1725267657542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_keitharogo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_keitharogo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_keitharogo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/KeithArogo/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_senthil2002_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_senthil2002_en.md
new file mode 100644
index 00000000000000..6586a2d7548222
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_finetuned_ner_senthil2002_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_senthil2002 DistilBertForTokenClassification from senthil2002
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_senthil2002
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_senthil2002` is a English model originally trained by senthil2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_senthil2002_en_5.5.0_3.0_1725267771999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_senthil2002_en_5.5.0_3.0_1725267771999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_senthil2002","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_senthil2002", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_senthil2002|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/senthil2002/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_travel_zphr_0st_refine_ck10_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_travel_zphr_0st_refine_ck10_en.md
new file mode 100644
index 00000000000000..ad1907c6cd88bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_base_uncased_travel_zphr_0st_refine_ck10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_travel_zphr_0st_refine_ck10 DistilBertForSequenceClassification from tom192180
+author: John Snow Labs
+name: distilbert_base_uncased_travel_zphr_0st_refine_ck10
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_travel_zphr_0st_refine_ck10` is a English model originally trained by tom192180.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_travel_zphr_0st_refine_ck10_en_5.5.0_3.0_1725305698258.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_travel_zphr_0st_refine_ck10_en_5.5.0_3.0_1725305698258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_travel_zphr_0st_refine_ck10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_travel_zphr_0st_refine_ck10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_travel_zphr_0st_refine_ck10|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tom192180/distilbert-base-uncased_travel_zphr_0st_refine_ck10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_emotion_narapuram_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_emotion_narapuram_pipeline_en.md
new file mode 100644
index 00000000000000..9da7dc5231493d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_emotion_narapuram_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_emotion_narapuram_pipeline pipeline DistilBertForSequenceClassification from Narapuram
+author: John Snow Labs
+name: distilbert_emotion_narapuram_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_narapuram_pipeline` is a English model originally trained by Narapuram.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_narapuram_pipeline_en_5.5.0_3.0_1725292178488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_narapuram_pipeline_en_5.5.0_3.0_1725292178488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_emotion_narapuram_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_emotion_narapuram_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_narapuram_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Narapuram/distilbert-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_fine_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_fine_pipeline_en.md
new file mode 100644
index 00000000000000..5b9c457ce66ad5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_fine_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_fine_pipeline pipeline DistilBertForSequenceClassification from michael0218
+author: John Snow Labs
+name: distilbert_fine_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_fine_pipeline` is a English model originally trained by michael0218.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_fine_pipeline_en_5.5.0_3.0_1725306066838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_fine_pipeline_en_5.5.0_3.0_1725306066838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_fine_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_fine_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_fine_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/michael0218/distilbert_fine
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emotion_hemanthkotaprolu_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emotion_hemanthkotaprolu_en.md
new file mode 100644
index 00000000000000..15e3c3fe38dc8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emotion_hemanthkotaprolu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_emotion_hemanthkotaprolu DistilBertForSequenceClassification from hemanthkotaprolu
+author: John Snow Labs
+name: distilbert_finetuned_emotion_hemanthkotaprolu
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_emotion_hemanthkotaprolu` is a English model originally trained by hemanthkotaprolu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_emotion_hemanthkotaprolu_en_5.5.0_3.0_1725292102615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_emotion_hemanthkotaprolu_en_5.5.0_3.0_1725292102615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_emotion_hemanthkotaprolu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_emotion_hemanthkotaprolu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_emotion_hemanthkotaprolu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hemanthkotaprolu/distilbert-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emowoz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emowoz_pipeline_en.md
new file mode 100644
index 00000000000000..4285fb7c6f709a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_finetuned_emowoz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_emowoz_pipeline pipeline DistilBertForSequenceClassification from mh0122
+author: John Snow Labs
+name: distilbert_finetuned_emowoz_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_emowoz_pipeline` is a English model originally trained by mh0122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_emowoz_pipeline_en_5.5.0_3.0_1725292132007.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_emowoz_pipeline_en_5.5.0_3.0_1725292132007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_emowoz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_emowoz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_emowoz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mh0122/distilbert-finetuned-emowoz
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_finer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_finer_pipeline_en.md
new file mode 100644
index 00000000000000..19234b5cd98e7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_ner_finer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_finer_pipeline pipeline DistilBertForTokenClassification from jishnunair
+author: John Snow Labs
+name: distilbert_ner_finer_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_finer_pipeline` is a English model originally trained by jishnunair.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_finer_pipeline_en_5.5.0_3.0_1725267908870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_finer_pipeline_en_5.5.0_3.0_1725267908870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_finer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_finer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_finer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.6 MB|
+
+## References
+
+https://huggingface.co/jishnunair/distilBert_NER_finer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_nsfw_appropriate_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_nsfw_appropriate_en.md
new file mode 100644
index 00000000000000..42e2c98f09c8a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_nsfw_appropriate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_nsfw_appropriate DistilBertForSequenceClassification from mboachie
+author: John Snow Labs
+name: distilbert_nsfw_appropriate
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_nsfw_appropriate` is a English model originally trained by mboachie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_nsfw_appropriate_en_5.5.0_3.0_1725291959367.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_nsfw_appropriate_en_5.5.0_3.0_1725291959367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_nsfw_appropriate","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_nsfw_appropriate", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_nsfw_appropriate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mboachie/distilbert_nsfw_appropriate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_phish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_phish_pipeline_en.md
new file mode 100644
index 00000000000000..57aaa2281b09ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_phish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_phish_pipeline pipeline DistilBertForSequenceClassification from bgspaditya
+author: John Snow Labs
+name: distilbert_phish_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_phish_pipeline` is a English model originally trained by bgspaditya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_phish_pipeline_en_5.5.0_3.0_1725291952455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_phish_pipeline_en_5.5.0_3.0_1725291952455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_phish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_phish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_phish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/bgspaditya/distilbert-phish
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline_en.md
new file mode 100644
index 00000000000000..be01be127f3015
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline pipeline DistilBertForSequenceClassification from joeddav
+author: John Snow Labs
+name: distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline` is a English model originally trained by joeddav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline_en_5.5.0_3.0_1725292304041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline_en_5.5.0_3.0_1725292304041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sequence_classifier_distilbert_base_uncased_agnews_student_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/joeddav/distilbert-base-uncased-agnews-student
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilcamembert_french_legal_fr.md b/docs/_posts/ahmedlone127/2024-09-02-distilcamembert_french_legal_fr.md
new file mode 100644
index 00000000000000..4fc8da3bbb9d1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilcamembert_french_legal_fr.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: French Legal DistilCamemBert Embeddings Model
+author: John Snow Labs
+name: distilcamembert_french_legal
+date: 2024-09-02
+tags: [open_source, camembert_embeddings, camembertformaskedlm, fr, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `legal-distilcamembert` is a French model originally trained by `maastrichtlawtech`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilcamembert_french_legal_fr_5.5.0_3.0_1725320859149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilcamembert_french_legal_fr_5.5.0_3.0_1725320859149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("distilcamembert_french_legal","fr") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("embeddings") \
+    .setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["J'adore Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("distilcamembert_french_legal","fr")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("embeddings")
+    .setCaseSensitive(True)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("J'adore Spark NLP").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilcamembert_french_legal|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|fr|
+|Size:|253.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/maastrichtlawtech/legal-distilcamembert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-distilcamembert_french_legal_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-distilcamembert_french_legal_pipeline_fr.md
new file mode 100644
index 00000000000000..89aab384e7ff5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-distilcamembert_french_legal_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French distilcamembert_french_legal_pipeline pipeline CamemBertEmbeddings from maastrichtlawtech
+author: John Snow Labs
+name: distilcamembert_french_legal_pipeline
+date: 2024-09-02
+tags: [fr, open_source, pipeline, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilcamembert_french_legal_pipeline` is a French model originally trained by maastrichtlawtech.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilcamembert_french_legal_pipeline_fr_5.5.0_3.0_1725320870896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilcamembert_french_legal_pipeline_fr_5.5.0_3.0_1725320870896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilcamembert_french_legal_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilcamembert_french_legal_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilcamembert_french_legal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|253.5 MB|
+
+## References
+
+https://huggingface.co/maastrichtlawtech/legal-distilcamembert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_camembert_pipeline_en.md
new file mode 100644
index 00000000000000..d50a1754224b95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_camembert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_camembert_pipeline pipeline CamemBertEmbeddings from vonewman
+author: John Snow Labs
+name: dummy_camembert_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_camembert_pipeline` is a English model originally trained by vonewman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_camembert_pipeline_en_5.5.0_3.0_1725302075675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_camembert_pipeline_en_5.5.0_3.0_1725302075675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_camembert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_camembert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_camembert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/vonewman/dummy-camembert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_jukerhd_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_jukerhd_en.md
new file mode 100644
index 00000000000000..66ed93d46a9ef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_jukerhd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_jukerhd CamemBertEmbeddings from jukerhd
+author: John Snow Labs
+name: dummy_jukerhd
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_jukerhd` is a English model originally trained by jukerhd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_jukerhd_en_5.5.0_3.0_1725302289550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_jukerhd_en_5.5.0_3.0_1725302289550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_jukerhd","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_jukerhd","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_jukerhd|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jukerhd/dummy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_jukerhd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_jukerhd_pipeline_en.md
new file mode 100644
index 00000000000000..442f2b715cc41b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_jukerhd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_jukerhd_pipeline pipeline CamemBertEmbeddings from jukerhd
+author: John Snow Labs
+name: dummy_jukerhd_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_jukerhd_pipeline` is a English model originally trained by jukerhd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_jukerhd_pipeline_en_5.5.0_3.0_1725302368531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_jukerhd_pipeline_en_5.5.0_3.0_1725302368531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_jukerhd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_jukerhd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_jukerhd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jukerhd/dummy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model2_dennyaw_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model2_dennyaw_en.md
new file mode 100644
index 00000000000000..b3e2dd0232aa38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model2_dennyaw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model2_dennyaw CamemBertEmbeddings from dennyaw
+author: John Snow Labs
+name: dummy_model2_dennyaw
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model2_dennyaw` is a English model originally trained by dennyaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model2_dennyaw_en_5.5.0_3.0_1725300477232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model2_dennyaw_en_5.5.0_3.0_1725300477232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model2_dennyaw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model2_dennyaw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model2_dennyaw|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/dennyaw/dummy-model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model2_dennyaw_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model2_dennyaw_pipeline_en.md
new file mode 100644
index 00000000000000..82d65363dc0b25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model2_dennyaw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model2_dennyaw_pipeline pipeline CamemBertEmbeddings from dennyaw
+author: John Snow Labs
+name: dummy_model2_dennyaw_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model2_dennyaw_pipeline` is a English model originally trained by dennyaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model2_dennyaw_pipeline_en_5.5.0_3.0_1725300556200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model2_dennyaw_pipeline_en_5.5.0_3.0_1725300556200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model2_dennyaw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model2_dennyaw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model2_dennyaw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/dennyaw/dummy-model2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_adam1224_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_adam1224_en.md
new file mode 100644
index 00000000000000..20759a14249e73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_adam1224_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_adam1224 CamemBertEmbeddings from adam1224
+author: John Snow Labs
+name: dummy_model_adam1224
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_adam1224` is a English model originally trained by adam1224.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_adam1224_en_5.5.0_3.0_1725320228664.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_adam1224_en_5.5.0_3.0_1725320228664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_adam1224","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_adam1224","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_adam1224|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/adam1224/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_akshatupadhyay_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_akshatupadhyay_en.md
new file mode 100644
index 00000000000000..5af6405640de80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_akshatupadhyay_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_akshatupadhyay CamemBertEmbeddings from akshatupadhyay
+author: John Snow Labs
+name: dummy_model_akshatupadhyay
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_akshatupadhyay` is a English model originally trained by akshatupadhyay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_akshatupadhyay_en_5.5.0_3.0_1725299631997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_akshatupadhyay_en_5.5.0_3.0_1725299631997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_akshatupadhyay","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_akshatupadhyay","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_akshatupadhyay|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/akshatupadhyay/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_alirezatalakoobi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_alirezatalakoobi_pipeline_en.md
new file mode 100644
index 00000000000000..cce8feeb190394
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_alirezatalakoobi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_alirezatalakoobi_pipeline pipeline CamemBertEmbeddings from alirezatalakoobi
+author: John Snow Labs
+name: dummy_model_alirezatalakoobi_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_alirezatalakoobi_pipeline` is a English model originally trained by alirezatalakoobi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_alirezatalakoobi_pipeline_en_5.5.0_3.0_1725300339762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_alirezatalakoobi_pipeline_en_5.5.0_3.0_1725300339762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_alirezatalakoobi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_alirezatalakoobi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_alirezatalakoobi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/alirezatalakoobi/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ameer05_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ameer05_pipeline_en.md
new file mode 100644
index 00000000000000..be9eb0ec90ee31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ameer05_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_ameer05_pipeline pipeline CamemBertEmbeddings from Ameer05
+author: John Snow Labs
+name: dummy_model_ameer05_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ameer05_pipeline` is a English model originally trained by Ameer05.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ameer05_pipeline_en_5.5.0_3.0_1725297954711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ameer05_pipeline_en_5.5.0_3.0_1725297954711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_ameer05_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_ameer05_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ameer05_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Ameer05/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankitkupadhyay_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankitkupadhyay_en.md
new file mode 100644
index 00000000000000..49aa9ddb68e881
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_ankitkupadhyay_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_ankitkupadhyay CamemBertEmbeddings from ankitkupadhyay
+author: John Snow Labs
+name: dummy_model_ankitkupadhyay
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ankitkupadhyay` is a English model originally trained by ankitkupadhyay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ankitkupadhyay_en_5.5.0_3.0_1725302441035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ankitkupadhyay_en_5.5.0_3.0_1725302441035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_ankitkupadhyay","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ankitkupadhyay","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ankitkupadhyay|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ankitkupadhyay/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_arushi151_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_arushi151_en.md
new file mode 100644
index 00000000000000..54235dd5e8956f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_arushi151_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_arushi151 CamemBertEmbeddings from Arushi151
+author: John Snow Labs
+name: dummy_model_arushi151
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_arushi151` is a English model originally trained by Arushi151.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_arushi151_en_5.5.0_3.0_1725300463834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_arushi151_en_5.5.0_3.0_1725300463834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_arushi151","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_arushi151","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_arushi151|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Arushi151/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_aryangupta_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_aryangupta_en.md
new file mode 100644
index 00000000000000..4124c09bbe4d9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_aryangupta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_aryangupta CamemBertEmbeddings from aryangupta
+author: John Snow Labs
+name: dummy_model_aryangupta
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_aryangupta` is a English model originally trained by aryangupta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_aryangupta_en_5.5.0_3.0_1725320403207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_aryangupta_en_5.5.0_3.0_1725320403207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_aryangupta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_aryangupta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_aryangupta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/aryangupta/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_aryangupta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_aryangupta_pipeline_en.md
new file mode 100644
index 00000000000000..030ad39923aff6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_aryangupta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_aryangupta_pipeline pipeline CamemBertEmbeddings from aryangupta
+author: John Snow Labs
+name: dummy_model_aryangupta_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_aryangupta_pipeline` is a English model originally trained by aryangupta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_aryangupta_pipeline_en_5.5.0_3.0_1725320480992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_aryangupta_pipeline_en_5.5.0_3.0_1725320480992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_aryangupta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_aryangupta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_aryangupta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/aryangupta/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bucktrends_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bucktrends_pipeline_fr.md
new file mode 100644
index 00000000000000..685df171a90581
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_bucktrends_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French dummy_model_bucktrends_pipeline pipeline CamemBertEmbeddings from bucktrends
+author: John Snow Labs
+name: dummy_model_bucktrends_pipeline
+date: 2024-09-02
+tags: [fr, open_source, pipeline, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bucktrends_pipeline` is a French model originally trained by bucktrends.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_bucktrends_pipeline_fr_5.5.0_3.0_1725298016261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bucktrends_pipeline_fr_5.5.0_3.0_1725298016261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_bucktrends_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_bucktrends_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_bucktrends_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/bucktrends/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_heartlocket_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_heartlocket_en.md
new file mode 100644
index 00000000000000..2ae7a0d81a3d85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_heartlocket_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_heartlocket CamemBertEmbeddings from heartlocket
+author: John Snow Labs
+name: dummy_model_heartlocket
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_heartlocket` is a English model originally trained by heartlocket.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_heartlocket_en_5.5.0_3.0_1725296870686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_heartlocket_en_5.5.0_3.0_1725296870686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_heartlocket","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_heartlocket","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_heartlocket|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/heartlocket/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jbern29_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jbern29_en.md
new file mode 100644
index 00000000000000..f6b1a41b9ab654
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jbern29_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jbern29 CamemBertEmbeddings from JBERN29
+author: John Snow Labs
+name: dummy_model_jbern29
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jbern29` is a English model originally trained by JBERN29.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jbern29_en_5.5.0_3.0_1725299511707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jbern29_en_5.5.0_3.0_1725299511707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jbern29","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jbern29","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jbern29|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/JBERN29/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jeeday_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jeeday_pipeline_en.md
new file mode 100644
index 00000000000000..b60351b6102abb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jeeday_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jeeday_pipeline pipeline CamemBertEmbeddings from JeeDay
+author: John Snow Labs
+name: dummy_model_jeeday_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jeeday_pipeline` is a English model originally trained by JeeDay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jeeday_pipeline_en_5.5.0_3.0_1725299825373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jeeday_pipeline_en_5.5.0_3.0_1725299825373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jeeday_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jeeday_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jeeday_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/JeeDay/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_joe8zhang_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_joe8zhang_pipeline_en.md
new file mode 100644
index 00000000000000..7a026aca86fdc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_joe8zhang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_joe8zhang_pipeline pipeline CamemBertEmbeddings from joe8zhang
+author: John Snow Labs
+name: dummy_model_joe8zhang_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_joe8zhang_pipeline` is a English model originally trained by joe8zhang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_joe8zhang_pipeline_en_5.5.0_3.0_1725300771794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_joe8zhang_pipeline_en_5.5.0_3.0_1725300771794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_joe8zhang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_joe8zhang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_joe8zhang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/joe8zhang/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jwchung_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jwchung_pipeline_en.md
new file mode 100644
index 00000000000000..969cdededd4782
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_jwchung_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jwchung_pipeline pipeline CamemBertEmbeddings from jwchung
+author: John Snow Labs
+name: dummy_model_jwchung_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jwchung_pipeline` is a English model originally trained by jwchung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jwchung_pipeline_en_5.5.0_3.0_1725297594870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jwchung_pipeline_en_5.5.0_3.0_1725297594870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jwchung_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jwchung_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jwchung_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jwchung/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kasper7953_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kasper7953_en.md
new file mode 100644
index 00000000000000..8a36be1e6ce773
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kasper7953_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_kasper7953 CamemBertEmbeddings from Kasper7953
+author: John Snow Labs
+name: dummy_model_kasper7953
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kasper7953` is a English model originally trained by Kasper7953.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kasper7953_en_5.5.0_3.0_1725299982970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kasper7953_en_5.5.0_3.0_1725299982970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_kasper7953","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_kasper7953","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kasper7953|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Kasper7953/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kasper7953_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kasper7953_pipeline_en.md
new file mode 100644
index 00000000000000..54a159d894dbb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kasper7953_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_kasper7953_pipeline pipeline CamemBertEmbeddings from Kasper7953
+author: John Snow Labs
+name: dummy_model_kasper7953_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kasper7953_pipeline` is a English model originally trained by Kasper7953.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kasper7953_pipeline_en_5.5.0_3.0_1725300062524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kasper7953_pipeline_en_5.5.0_3.0_1725300062524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_kasper7953_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_kasper7953_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kasper7953_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Kasper7953/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kprashanth_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kprashanth_en.md
new file mode 100644
index 00000000000000..eb2c466d5e5511
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_kprashanth_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_kprashanth CamemBertEmbeddings from KPrashanth
+author: John Snow Labs
+name: dummy_model_kprashanth
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kprashanth` is a English model originally trained by KPrashanth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kprashanth_en_5.5.0_3.0_1725300555511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kprashanth_en_5.5.0_3.0_1725300555511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_kprashanth","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_kprashanth","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kprashanth|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/KPrashanth/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lucianodeben_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lucianodeben_en.md
new file mode 100644
index 00000000000000..afd14242cb351e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_lucianodeben_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_lucianodeben CamemBertEmbeddings from LucianoDeben
+author: John Snow Labs
+name: dummy_model_lucianodeben
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lucianodeben` is a English model originally trained by LucianoDeben.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lucianodeben_en_5.5.0_3.0_1725319793291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lucianodeben_en_5.5.0_3.0_1725319793291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_lucianodeben","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_lucianodeben","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lucianodeben|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/LucianoDeben/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_marisming_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_marisming_en.md
new file mode 100644
index 00000000000000..11f883b7353867
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_marisming_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_marisming CamemBertEmbeddings from marisming
+author: John Snow Labs
+name: dummy_model_marisming
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_marisming` is a English model originally trained by marisming.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_marisming_en_5.5.0_3.0_1725297206578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_marisming_en_5.5.0_3.0_1725297206578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_marisming","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_marisming","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_marisming|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/marisming/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_matthewvedder_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_matthewvedder_en.md
new file mode 100644
index 00000000000000..39c8ab5f048c5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_matthewvedder_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_matthewvedder CamemBertEmbeddings from MatthewVedder
+author: John Snow Labs
+name: dummy_model_matthewvedder
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_matthewvedder` is a English model originally trained by MatthewVedder.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_matthewvedder_en_5.5.0_3.0_1725302885917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_matthewvedder_en_5.5.0_3.0_1725302885917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_matthewvedder","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_matthewvedder","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_matthewvedder|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/MatthewVedder/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mbearss_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mbearss_en.md
new file mode 100644
index 00000000000000..8effe5ff84e4b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mbearss_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_mbearss CamemBertEmbeddings from mbearss
+author: John Snow Labs
+name: dummy_model_mbearss
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_mbearss` is a English model originally trained by mbearss.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_mbearss_en_5.5.0_3.0_1725296404061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_mbearss_en_5.5.0_3.0_1725296404061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_mbearss","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_mbearss","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_mbearss|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mbearss/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mindnetml_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mindnetml_pipeline_en.md
new file mode 100644
index 00000000000000..dc75ada2110ef4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_mindnetml_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_mindnetml_pipeline pipeline CamemBertEmbeddings from MindNetML
+author: John Snow Labs
+name: dummy_model_mindnetml_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_mindnetml_pipeline` is a English model originally trained by MindNetML.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_mindnetml_pipeline_en_5.5.0_3.0_1725303192676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_mindnetml_pipeline_en_5.5.0_3.0_1725303192676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_mindnetml_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_mindnetml_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_mindnetml_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/MindNetML/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_omenndt_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_omenndt_en.md
new file mode 100644
index 00000000000000..09a0ada3c382c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_omenndt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_omenndt CamemBertEmbeddings from OmenNDT
+author: John Snow Labs
+name: dummy_model_omenndt
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_omenndt` is a English model originally trained by OmenNDT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_omenndt_en_5.5.0_3.0_1725302650423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_omenndt_en_5.5.0_3.0_1725302650423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_omenndt","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_omenndt","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_omenndt|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/OmenNDT/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pawankumar_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pawankumar_pipeline_en.md
new file mode 100644
index 00000000000000..eb4145c01f5876
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_pawankumar_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_pawankumar_pipeline pipeline CamemBertEmbeddings from pawankumar
+author: John Snow Labs
+name: dummy_model_pawankumar_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pawankumar_pipeline` is a English model originally trained by pawankumar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pawankumar_pipeline_en_5.5.0_3.0_1725300045805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pawankumar_pipeline_en_5.5.0_3.0_1725300045805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_pawankumar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_pawankumar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_pawankumar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/pawankumar/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamsonn_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamsonn_en.md
new file mode 100644
index 00000000000000..ed845cc558d775
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamsonn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_phamsonn CamemBertEmbeddings from phamsonn
+author: John Snow Labs
+name: dummy_model_phamsonn
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_phamsonn` is a English model originally trained by phamsonn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_phamsonn_en_5.5.0_3.0_1725320786763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_phamsonn_en_5.5.0_3.0_1725320786763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_phamsonn","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_phamsonn","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_phamsonn|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/phamsonn/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamsonn_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamsonn_pipeline_en.md
new file mode 100644
index 00000000000000..8a5f315578626b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_phamsonn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_phamsonn_pipeline pipeline CamemBertEmbeddings from phamsonn
+author: John Snow Labs
+name: dummy_model_phamsonn_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_phamsonn_pipeline` is a English model originally trained by phamsonn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_phamsonn_pipeline_en_5.5.0_3.0_1725320866280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_phamsonn_pipeline_en_5.5.0_3.0_1725320866280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_phamsonn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_phamsonn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_phamsonn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/phamsonn/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_tpanza_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_tpanza_en.md
new file mode 100644
index 00000000000000..288c236efd50c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_tpanza_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_tpanza CamemBertEmbeddings from tpanza
+author: John Snow Labs
+name: dummy_model_tpanza
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_tpanza` is a English model originally trained by tpanza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_tpanza_en_5.5.0_3.0_1725320674700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_tpanza_en_5.5.0_3.0_1725320674700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_tpanza","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_tpanza","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_tpanza|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/tpanza/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_wangst_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_wangst_en.md
new file mode 100644
index 00000000000000..edfc3c370d437e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_wangst_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_wangst CamemBertEmbeddings from wangst
+author: John Snow Labs
+name: dummy_model_wangst
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_wangst` is a English model originally trained by wangst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_wangst_en_5.5.0_3.0_1725303253869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_wangst_en_5.5.0_3.0_1725303253869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_wangst","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_wangst","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_wangst|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/wangst/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zonepg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zonepg_pipeline_en.md
new file mode 100644
index 00000000000000..6e0b87dc750500
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummy_model_zonepg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_zonepg_pipeline pipeline CamemBertEmbeddings from ZonePG
+author: John Snow Labs
+name: dummy_model_zonepg_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_zonepg_pipeline` is a English model originally trained by ZonePG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_zonepg_pipeline_en_5.5.0_3.0_1725296488149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_zonepg_pipeline_en_5.5.0_3.0_1725296488149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_zonepg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_zonepg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_zonepg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ZonePG/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummymodel_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummymodel_en.md
new file mode 100644
index 00000000000000..2f7e58bf21128c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummymodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummymodel CamemBertEmbeddings from 3JI0
+author: John Snow Labs
+name: dummymodel
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummymodel` is a English model originally trained by 3JI0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummymodel_en_5.5.0_3.0_1725300304155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummymodel_en_5.5.0_3.0_1725300304155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummymodel","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummymodel","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummymodel|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/3JI0/dummyModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-dummymodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-dummymodel_pipeline_en.md
new file mode 100644
index 00000000000000..aa788a7dbeb3e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-dummymodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummymodel_pipeline pipeline CamemBertEmbeddings from 3JI0
+author: John Snow Labs
+name: dummymodel_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummymodel_pipeline` is a English model originally trained by 3JI0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummymodel_pipeline_en_5.5.0_3.0_1725300383103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummymodel_pipeline_en_5.5.0_3.0_1725300383103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummymodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummymodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummymodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/3JI0/dummyModel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_1000_pipeline_en.md
new file mode 100644
index 00000000000000..096c26152b4e2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-e2m_dataset_tags_1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English e2m_dataset_tags_1000_pipeline pipeline MarianTransformer from mekaneeky
+author: John Snow Labs
+name: e2m_dataset_tags_1000_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e2m_dataset_tags_1000_pipeline` is a English model originally trained by mekaneeky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e2m_dataset_tags_1000_pipeline_en_5.5.0_3.0_1725303914596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e2m_dataset_tags_1000_pipeline_en_5.5.0_3.0_1725303914596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e2m_dataset_tags_1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e2m_dataset_tags_1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e2m_dataset_tags_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.7 MB|
+
+## References
+
+https://huggingface.co/mekaneeky/e2m-dataset-tags-1000
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-e5_90k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-e5_90k_pipeline_en.md
new file mode 100644
index 00000000000000..b3603c64ae7338
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-e5_90k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_90k_pipeline pipeline E5Embeddings from heka-ai
+author: John Snow Labs
+name: e5_90k_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_90k_pipeline` is a English model originally trained by heka-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_90k_pipeline_en_5.5.0_3.0_1725259768776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_90k_pipeline_en_5.5.0_3.0_1725259768776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_90k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_90k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_90k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|401.2 MB|
+
+## References
+
+https://huggingface.co/heka-ai/e5-90k
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-elon_musk_detector_en.md b/docs/_posts/ahmedlone127/2024-09-02-elon_musk_detector_en.md
new file mode 100644
index 00000000000000..80aedb24f60997
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-elon_musk_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English elon_musk_detector DistilBertForSequenceClassification from kix-intl
+author: John Snow Labs
+name: elon_musk_detector
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`elon_musk_detector` is a English model originally trained by kix-intl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/elon_musk_detector_en_5.5.0_3.0_1725292334186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/elon_musk_detector_en_5.5.0_3.0_1725292334186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("elon_musk_detector","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("elon_musk_detector", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|elon_musk_detector|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kix-intl/elon-musk-detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-elon_musk_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-elon_musk_detector_pipeline_en.md
new file mode 100644
index 00000000000000..1837a1ae7ed3ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-elon_musk_detector_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English elon_musk_detector_pipeline pipeline DistilBertForSequenceClassification from kix-intl
+author: John Snow Labs
+name: elon_musk_detector_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`elon_musk_detector_pipeline` is a English model originally trained by kix-intl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/elon_musk_detector_pipeline_en_5.5.0_3.0_1725292347160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/elon_musk_detector_pipeline_en_5.5.0_3.0_1725292347160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("elon_musk_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("elon_musk_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|elon_musk_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kix-intl/elon-musk-detector
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-emotion_bot_1000_en.md b/docs/_posts/ahmedlone127/2024-09-02-emotion_bot_1000_en.md
new file mode 100644
index 00000000000000..873c47d044684c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-emotion_bot_1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emotion_bot_1000 DistilBertForSequenceClassification from rrpetroff
+author: John Snow Labs
+name: emotion_bot_1000
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_bot_1000` is a English model originally trained by rrpetroff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_bot_1000_en_5.5.0_3.0_1725306141093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_bot_1000_en_5.5.0_3.0_1725306141093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("emotion_bot_1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("emotion_bot_1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_bot_1000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rrpetroff/emotion-bot-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-enccr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-enccr_pipeline_en.md
new file mode 100644
index 00000000000000..24b1a55e221c17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-enccr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English enccr_pipeline pipeline RoBertaForSequenceClassification from AntoineGourru
+author: John Snow Labs
+name: enccr_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enccr_pipeline` is a English model originally trained by AntoineGourru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/enccr_pipeline_en_5.5.0_3.0_1725277017847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enccr_pipeline_en_5.5.0_3.0_1725277017847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("enccr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("enccr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enccr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|417.0 MB|
+
+## References
+
+https://huggingface.co/AntoineGourru/Enccr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-eng_hin_translator_en.md b/docs/_posts/ahmedlone127/2024-09-02-eng_hin_translator_en.md
new file mode 100644
index 00000000000000..ea34b827b63192
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-eng_hin_translator_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English eng_hin_translator MarianTransformer from Vasanth
+author: John Snow Labs
+name: eng_hin_translator
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eng_hin_translator` is a English model originally trained by Vasanth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eng_hin_translator_en_5.5.0_3.0_1725244102427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eng_hin_translator_en_5.5.0_3.0_1725244102427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("eng_hin_translator","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("eng_hin_translator","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eng_hin_translator|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|522.8 MB|
+
+## References
+
+https://huggingface.co/Vasanth/eng-hin-translator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_arabic_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_arabic_model_pipeline_en.md
new file mode 100644
index 00000000000000..0fca108d96a29b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-english_arabic_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_arabic_model_pipeline pipeline MarianTransformer from BoghdadyJR
+author: John Snow Labs
+name: english_arabic_model_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_arabic_model_pipeline` is a English model originally trained by BoghdadyJR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_arabic_model_pipeline_en_5.5.0_3.0_1725294669762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_arabic_model_pipeline_en_5.5.0_3.0_1725294669762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_arabic_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_arabic_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_arabic_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.7 MB|
+
+## References
+
+https://huggingface.co/BoghdadyJR/en-ar-model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_ganda_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_ganda_en.md
new file mode 100644
index 00000000000000..dea3678690d5f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-english_ganda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_ganda MarianTransformer from AI-Lab-Makerere
+author: John Snow Labs
+name: english_ganda
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_ganda` is a English model originally trained by AI-Lab-Makerere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_ganda_en_5.5.0_3.0_1725243713062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_ganda_en_5.5.0_3.0_1725243713062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_ganda","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_ganda","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_ganda|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|530.3 MB|
+
+## References
+
+https://huggingface.co/AI-Lab-Makerere/en_lg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_hebrew_modern_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_hebrew_modern_base_pipeline_en.md
new file mode 100644
index 00000000000000..8a7c80ee63ac5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-english_hebrew_modern_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_hebrew_modern_base_pipeline pipeline MarianTransformer from orendar
+author: John Snow Labs
+name: english_hebrew_modern_base_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_hebrew_modern_base_pipeline` is a English model originally trained by orendar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_hebrew_modern_base_pipeline_en_5.5.0_3.0_1725295848436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_hebrew_modern_base_pipeline_en_5.5.0_3.0_1725295848436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_hebrew_modern_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_hebrew_modern_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_hebrew_modern_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|352.5 MB|
+
+## References
+
+https://huggingface.co/orendar/en_he_base
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_italian_marianmt_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_italian_marianmt_en.md
new file mode 100644
index 00000000000000..5b80ef47c55aed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_italian_marianmt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_italian_marianmt MarianTransformer from vvn
+author: John Snow Labs
+name: english_tonga_tonga_islands_italian_marianmt
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_italian_marianmt` is a English model originally trained by vvn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_italian_marianmt_en_5.5.0_3.0_1725303892928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_italian_marianmt_en_5.5.0_3.0_1725303892928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_tonga_tonga_islands_italian_marianmt","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_italian_marianmt","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_italian_marianmt|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|623.3 MB|
+
+## References
+
+https://huggingface.co/vvn/en-to-it-marianmt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_italian_marianmt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_italian_marianmt_pipeline_en.md
new file mode 100644
index 00000000000000..0c0c1d66a09847
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-english_tonga_tonga_islands_italian_marianmt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_italian_marianmt_pipeline pipeline MarianTransformer from vvn
+author: John Snow Labs
+name: english_tonga_tonga_islands_italian_marianmt_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_italian_marianmt_pipeline` is a English model originally trained by vvn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_italian_marianmt_pipeline_en_5.5.0_3.0_1725303925532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_italian_marianmt_pipeline_en_5.5.0_3.0_1725303925532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_italian_marianmt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_italian_marianmt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_italian_marianmt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|623.8 MB|
+
+## References
+
+https://huggingface.co/vvn/en-to-it-marianmt
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-enviduediligence_ner_en.md b/docs/_posts/ahmedlone127/2024-09-02-enviduediligence_ner_en.md
new file mode 100644
index 00000000000000..e132001c73c7fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-enviduediligence_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English enviduediligence_ner DistilBertForTokenClassification from d4data
+author: John Snow Labs
+name: enviduediligence_ner
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enviduediligence_ner` is a English model originally trained by d4data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/enviduediligence_ner_en_5.5.0_3.0_1725267794434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enviduediligence_ner_en_5.5.0_3.0_1725267794434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("enviduediligence_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("enviduediligence_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enviduediligence_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/d4data/EnviDueDiligence_NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-enviduediligence_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-enviduediligence_ner_pipeline_en.md
new file mode 100644
index 00000000000000..46750531337f58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-enviduediligence_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English enviduediligence_ner_pipeline pipeline DistilBertForTokenClassification from d4data
+author: John Snow Labs
+name: enviduediligence_ner_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enviduediligence_ner_pipeline` is a English model originally trained by d4data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/enviduediligence_ner_pipeline_en_5.5.0_3.0_1725267808120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enviduediligence_ner_pipeline_en_5.5.0_3.0_1725267808120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("enviduediligence_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("enviduediligence_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enviduediligence_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/d4data/EnviDueDiligence_NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-environmentalbert_biodiversity_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-environmentalbert_biodiversity_pipeline_en.md
new file mode 100644
index 00000000000000..930fee1bef2d63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-environmentalbert_biodiversity_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English environmentalbert_biodiversity_pipeline pipeline RoBertaForSequenceClassification from ESGBERT
+author: John Snow Labs
+name: environmentalbert_biodiversity_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`environmentalbert_biodiversity_pipeline` is a English model originally trained by ESGBERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/environmentalbert_biodiversity_pipeline_en_5.5.0_3.0_1725277670513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/environmentalbert_biodiversity_pipeline_en_5.5.0_3.0_1725277670513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("environmentalbert_biodiversity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("environmentalbert_biodiversity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|environmentalbert_biodiversity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.0 MB|
+
+## References
+
+https://huggingface.co/ESGBERT/EnvironmentalBERT-biodiversity
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big7_pipeline_en.md
new file mode 100644
index 00000000000000..29ea208bcd8f3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-feel_italian_finetuned_pro_emit_big7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English feel_italian_finetuned_pro_emit_big7_pipeline pipeline CamemBertForSequenceClassification from lupobricco
+author: John Snow Labs
+name: feel_italian_finetuned_pro_emit_big7_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feel_italian_finetuned_pro_emit_big7_pipeline` is a English model originally trained by lupobricco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big7_pipeline_en_5.5.0_3.0_1725298794718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_big7_pipeline_en_5.5.0_3.0_1725298794718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("feel_italian_finetuned_pro_emit_big7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("feel_italian_finetuned_pro_emit_big7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|feel_italian_finetuned_pro_emit_big7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/lupobricco/feel_it_finetuned_pro_emit_big7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-fewshot_qa_002_20230613_003_exp2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fewshot_qa_002_20230613_003_exp2_pipeline_en.md
new file mode 100644
index 00000000000000..8434ca9074354f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-fewshot_qa_002_20230613_003_exp2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fewshot_qa_002_20230613_003_exp2_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: fewshot_qa_002_20230613_003_exp2_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fewshot_qa_002_20230613_003_exp2_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230613_003_exp2_pipeline_en_5.5.0_3.0_1725254632405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230613_003_exp2_pipeline_en_5.5.0_3.0_1725254632405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fewshot_qa_002_20230613_003_exp2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fewshot_qa_002_20230613_003_exp2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fewshot_qa_002_20230613_003_exp2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|880.4 MB|
+
+## References
+
+https://huggingface.co/intanm/fewshot-qa-002-20230613-003-exp2
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-fin_camembert_base_fr.md b/docs/_posts/ahmedlone127/2024-09-02-fin_camembert_base_fr.md
new file mode 100644
index 00000000000000..8586f1b4349ecb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-fin_camembert_base_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French fin_camembert_base CamemBertEmbeddings from Ngawang
+author: John Snow Labs
+name: fin_camembert_base
+date: 2024-09-02
+tags: [fr, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fin_camembert_base` is a French model originally trained by Ngawang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fin_camembert_base_fr_5.5.0_3.0_1725320041542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fin_camembert_base_fr_5.5.0_3.0_1725320041542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("fin_camembert_base","fr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("fin_camembert_base","fr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fin_camembert_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|fr|
+|Size:|412.6 MB|
+
+## References
+
+https://huggingface.co/Ngawang/fin_camembert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_base_raw_pdf_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_base_raw_pdf_v1_en.md
new file mode 100644
index 00000000000000..ffc10c8efe5aa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_base_raw_pdf_v1_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English fine_tuned_bge_base_raw_pdf_v1 BGEEmbeddings from kr-manish
+author: John Snow Labs
+name: fine_tuned_bge_base_raw_pdf_v1
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bge_base_raw_pdf_v1` is a English model originally trained by kr-manish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_base_raw_pdf_v1_en_5.5.0_3.0_1725241473042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_base_raw_pdf_v1_en_5.5.0_3.0_1725241473042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("fine_tuned_bge_base_raw_pdf_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("fine_tuned_bge_base_raw_pdf_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_bge_base_raw_pdf_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|376.9 MB|
+
+## References
+
+https://huggingface.co/kr-manish/fine-tuned-bge-base-raw_pdf-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_base_raw_pdf_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_base_raw_pdf_v1_pipeline_en.md
new file mode 100644
index 00000000000000..e9940e3c5ba888
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_bge_base_raw_pdf_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_bge_base_raw_pdf_v1_pipeline pipeline BGEEmbeddings from kr-manish
+author: John Snow Labs
+name: fine_tuned_bge_base_raw_pdf_v1_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bge_base_raw_pdf_v1_pipeline` is a English model originally trained by kr-manish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_base_raw_pdf_v1_pipeline_en_5.5.0_3.0_1725241507895.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_base_raw_pdf_v1_pipeline_en_5.5.0_3.0_1725241507895.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_bge_base_raw_pdf_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_bge_base_raw_pdf_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_bge_base_raw_pdf_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|376.9 MB|
+
+## References
+
+https://huggingface.co/kr-manish/fine-tuned-bge-base-raw_pdf-v1
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_united_airlines_twitter_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_united_airlines_twitter_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..c02176616680c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-fine_tuned_united_airlines_twitter_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_united_airlines_twitter_sentiment_analysis DistilBertForSequenceClassification from Kayyyy27
+author: John Snow Labs
+name: fine_tuned_united_airlines_twitter_sentiment_analysis
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_united_airlines_twitter_sentiment_analysis` is a English model originally trained by Kayyyy27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_united_airlines_twitter_sentiment_analysis_en_5.5.0_3.0_1725306087997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_united_airlines_twitter_sentiment_analysis_en_5.5.0_3.0_1725306087997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("fine_tuned_united_airlines_twitter_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("fine_tuned_united_airlines_twitter_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_united_airlines_twitter_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Kayyyy27/fine-tuned-United_Airlines_Twitter_Sentiment_Analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_classification_model_pipeline_en.md
new file mode 100644
index 00000000000000..5f3efc41adee39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_classification_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_classification_model_pipeline pipeline DistilBertForSequenceClassification from Mr-Vicky-01
+author: John Snow Labs
+name: finetuned_classification_model_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_classification_model_pipeline` is a English model originally trained by Mr-Vicky-01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_classification_model_pipeline_en_5.5.0_3.0_1725305649494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_classification_model_pipeline_en_5.5.0_3.0_1725305649494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_classification_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_classification_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_classification_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Mr-Vicky-01/finetuned_classification_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_model_vitaminnie_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_model_vitaminnie_en.md
new file mode 100644
index 00000000000000..a0e59c25e79b94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_model_vitaminnie_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_model_vitaminnie MarianTransformer from vitaminnie
+author: John Snow Labs
+name: finetuned_model_vitaminnie
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_model_vitaminnie` is a English model originally trained by vitaminnie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_model_vitaminnie_en_5.5.0_3.0_1725303679618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_model_vitaminnie_en_5.5.0_3.0_1725303679618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("finetuned_model_vitaminnie","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("finetuned_model_vitaminnie","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_model_vitaminnie|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.9 MB|
+
+## References
+
+https://huggingface.co/vitaminnie/finetuned-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_model_vitaminnie_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_model_vitaminnie_pipeline_en.md
new file mode 100644
index 00000000000000..8597d5e1011584
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_model_vitaminnie_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_model_vitaminnie_pipeline pipeline MarianTransformer from vitaminnie
+author: John Snow Labs
+name: finetuned_model_vitaminnie_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_model_vitaminnie_pipeline` is a English model originally trained by vitaminnie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_model_vitaminnie_pipeline_en_5.5.0_3.0_1725303712762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_model_vitaminnie_pipeline_en_5.5.0_3.0_1725303712762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_model_vitaminnie_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_model_vitaminnie_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_model_vitaminnie_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.5 MB|
+
+## References
+
+https://huggingface.co/vitaminnie/finetuned-model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline_en.md
new file mode 100644
index 00000000000000..014d8c79a26472
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline pipeline MarianTransformer from Varsha00
+author: John Snow Labs
+name: finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline` is a English model originally trained by Varsha00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline_en_5.5.0_3.0_1725295657331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline_en_5.5.0_3.0_1725295657331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_opusmt_english_tonga_tonga_islands_hindi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.6 MB|
+
+## References
+
+https://huggingface.co/Varsha00/finetuned-opusmt-en-to-hi
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_emotion_model_dearkarina_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_emotion_model_dearkarina_en.md
new file mode 100644
index 00000000000000..20f45a5bf3ea9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_emotion_model_dearkarina_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_emotion_model_dearkarina DistilBertForSequenceClassification from dearkarina
+author: John Snow Labs
+name: finetuning_emotion_model_dearkarina
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_emotion_model_dearkarina` is a English model originally trained by dearkarina.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_dearkarina_en_5.5.0_3.0_1725291799331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_dearkarina_en_5.5.0_3.0_1725291799331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_emotion_model_dearkarina","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_emotion_model_dearkarina", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_emotion_model_dearkarina|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dearkarina/finetuning-emotion-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_thp99_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_thp99_en.md
new file mode 100644
index 00000000000000..a0189a63367ac1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_thp99_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_thp99 DistilBertForSequenceClassification from ThP99
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_thp99
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_thp99` is a English model originally trained by ThP99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_thp99_en_5.5.0_3.0_1725305986622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_thp99_en_5.5.0_3.0_1725305986622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_thp99","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_thp99", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_thp99|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ThP99/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline_en.md
new file mode 100644
index 00000000000000..452e9255aad5f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline pipeline DistilBertForSequenceClassification from vishalpanda10
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline` is a English model originally trained by vishalpanda10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline_en_5.5.0_3.0_1725305720892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline_en_5.5.0_3.0_1725305720892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_vishalpanda10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vishalpanda10/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3004_samples_vaishu23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3004_samples_vaishu23_pipeline_en.md
new file mode 100644
index 00000000000000..2aa6f702db46e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_3004_samples_vaishu23_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3004_samples_vaishu23_pipeline pipeline DistilBertForSequenceClassification from vaishu23
+author: John Snow Labs
+name: finetuning_sentiment_model_3004_samples_vaishu23_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3004_samples_vaishu23_pipeline` is a English model originally trained by vaishu23.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3004_samples_vaishu23_pipeline_en_5.5.0_3.0_1725305815991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3004_samples_vaishu23_pipeline_en_5.5.0_3.0_1725305815991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3004_samples_vaishu23_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3004_samples_vaishu23_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3004_samples_vaishu23_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vaishu23/finetuning-sentiment-model-3004-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_hw6_en.md b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_hw6_en.md
new file mode 100644
index 00000000000000..2258bbaed01741
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-finetuning_sentiment_model_hw6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_hw6 DistilBertForSequenceClassification from anosognosie
+author: John Snow Labs
+name: finetuning_sentiment_model_hw6
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_hw6` is a English model originally trained by anosognosie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_hw6_en_5.5.0_3.0_1725305962479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_hw6_en_5.5.0_3.0_1725305962479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_hw6","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_hw6", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_hw6|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/anosognosie/finetuning-sentiment-model-hw6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_en.md b/docs/_posts/ahmedlone127/2024-09-02-frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_en.md
new file mode 100644
index 00000000000000..2b5aa58d269490
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_en.md
@@ -0,0 +1,66 @@
+---
+layout: model
+title: English frpile_gpl_test_pipeline_all_mpnet_base_v2_14000 pipeline MPNetEmbeddings from DragosGorduza
+author: John Snow Labs
+name: frpile_gpl_test_pipeline_all_mpnet_base_v2_14000
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frpile_gpl_test_pipeline_all_mpnet_base_v2_14000` is a English model originally trained by DragosGorduza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_en_5.5.0_3.0_1725313996527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frpile_gpl_test_pipeline_all_mpnet_base_v2_14000_en_5.5.0_3.0_1725313996527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("frpile_gpl_test_pipeline_all_mpnet_base_v2_14000", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("frpile_gpl_test_pipeline_all_mpnet_base_v2_14000", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|frpile_gpl_test_pipeline_all_mpnet_base_v2_14000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/DragosGorduza/FRPile_GPL_test_pipeline_all-mpnet-base-v2_14000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-gal_sayula_popoluca_portuguese_5_en.md b/docs/_posts/ahmedlone127/2024-09-02-gal_sayula_popoluca_portuguese_5_en.md
new file mode 100644
index 00000000000000..a6666188559326
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-gal_sayula_popoluca_portuguese_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gal_sayula_popoluca_portuguese_5 XlmRoBertaForTokenClassification from homersimpson
+author: John Snow Labs
+name: gal_sayula_popoluca_portuguese_5
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gal_sayula_popoluca_portuguese_5` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gal_sayula_popoluca_portuguese_5_en_5.5.0_3.0_1725316762422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gal_sayula_popoluca_portuguese_5_en_5.5.0_3.0_1725316762422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("gal_sayula_popoluca_portuguese_5","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("gal_sayula_popoluca_portuguese_5", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gal_sayula_popoluca_portuguese_5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|387.7 MB|
+
+## References
+
+https://huggingface.co/homersimpson/gal-pos-pt-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-gal_sayula_popoluca_portuguese_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-gal_sayula_popoluca_portuguese_5_pipeline_en.md
new file mode 100644
index 00000000000000..39bbacffa35026
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-gal_sayula_popoluca_portuguese_5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English gal_sayula_popoluca_portuguese_5_pipeline pipeline XlmRoBertaForTokenClassification from homersimpson
+author: John Snow Labs
+name: gal_sayula_popoluca_portuguese_5_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gal_sayula_popoluca_portuguese_5_pipeline` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gal_sayula_popoluca_portuguese_5_pipeline_en_5.5.0_3.0_1725316788790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gal_sayula_popoluca_portuguese_5_pipeline_en_5.5.0_3.0_1725316788790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gal_sayula_popoluca_portuguese_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gal_sayula_popoluca_portuguese_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gal_sayula_popoluca_portuguese_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.7 MB|
+
+## References
+
+https://huggingface.co/homersimpson/gal-pos-pt-5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-github_samples_tclassifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-github_samples_tclassifier_pipeline_en.md
new file mode 100644
index 00000000000000..2990633bd09073
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-github_samples_tclassifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English github_samples_tclassifier_pipeline pipeline DistilBertForSequenceClassification from h1alexbel
+author: John Snow Labs
+name: github_samples_tclassifier_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`github_samples_tclassifier_pipeline` is a English model originally trained by h1alexbel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/github_samples_tclassifier_pipeline_en_5.5.0_3.0_1725292224374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/github_samples_tclassifier_pipeline_en_5.5.0_3.0_1725292224374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("github_samples_tclassifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("github_samples_tclassifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|github_samples_tclassifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/h1alexbel/github-samples-tclassifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_en.md b/docs/_posts/ahmedlone127/2024-09-02-helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_en.md
new file mode 100644
index 00000000000000..26682037a974eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune MarianTransformer from MikolajDeja
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune` is a English model originally trained by MikolajDeja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_en_5.5.0_3.0_1725244092855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune_en_5.5.0_3.0_1725244092855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_polish_english_yhavinga_ccmatrix_finetune|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|529.3 MB|
+
+## References
+
+https://huggingface.co/MikolajDeja/Helsinki-NLP-opus-mt-pl-en-yhavinga-ccmatrix-finetune
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-helsinki_translation_english_moroccan_arabic_en.md b/docs/_posts/ahmedlone127/2024-09-02-helsinki_translation_english_moroccan_arabic_en.md
new file mode 100644
index 00000000000000..1e23a675ac7fc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-helsinki_translation_english_moroccan_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_translation_english_moroccan_arabic MarianTransformer from lachkarsalim
+author: John Snow Labs
+name: helsinki_translation_english_moroccan_arabic
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_translation_english_moroccan_arabic` is a English model originally trained by lachkarsalim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_translation_english_moroccan_arabic_en_5.5.0_3.0_1725294936066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_translation_english_moroccan_arabic_en_5.5.0_3.0_1725294936066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_translation_english_moroccan_arabic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_translation_english_moroccan_arabic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_translation_english_moroccan_arabic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/lachkarsalim/Helsinki-translation-English_Moroccan-Arabic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-hh_labeler_en.md b/docs/_posts/ahmedlone127/2024-09-02-hh_labeler_en.md
new file mode 100644
index 00000000000000..9e2de0c0307073
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-hh_labeler_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hh_labeler DistilBertForSequenceClassification from davidgaofc
+author: John Snow Labs
+name: hh_labeler
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hh_labeler` is a English model originally trained by davidgaofc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hh_labeler_en_5.5.0_3.0_1725291815997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hh_labeler_en_5.5.0_3.0_1725291815997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("hh_labeler","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("hh_labeler", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hh_labeler|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/davidgaofc/hh-labeler
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-hinglish_bert_en.md b/docs/_posts/ahmedlone127/2024-09-02-hinglish_bert_en.md
new file mode 100644
index 00000000000000..6aab18ca4d5cca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-hinglish_bert_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English hinglish_bert BertEmbeddings from meghanabhange
+author: John Snow Labs
+name: hinglish_bert
+date: 2024-09-02
+tags: [bert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hinglish_bert` is a English model originally trained by meghanabhange.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hinglish_bert_en_5.5.0_3.0_1725318403731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hinglish_bert_en_5.5.0_3.0_1725318403731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =BertEmbeddings.pretrained("hinglish_bert","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = BertEmbeddings 
+    .pretrained("hinglish_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hinglish_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/meghanabhange/Hinglish-Bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-immensa_embeddings_en.md b/docs/_posts/ahmedlone127/2024-09-02-immensa_embeddings_en.md
new file mode 100644
index 00000000000000..652991619f71c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-immensa_embeddings_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English immensa_embeddings MPNetEmbeddings from engineai
+author: John Snow Labs
+name: immensa_embeddings
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`immensa_embeddings` is a English model originally trained by engineai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/immensa_embeddings_en_5.5.0_3.0_1725313538416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/immensa_embeddings_en_5.5.0_3.0_1725313538416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("immensa_embeddings","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("immensa_embeddings","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|immensa_embeddings|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/engineai/immensa_embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-indodistilbertweet_en.md b/docs/_posts/ahmedlone127/2024-09-02-indodistilbertweet_en.md
new file mode 100644
index 00000000000000..f8933d7b6287dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-indodistilbertweet_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indodistilbertweet RoBertaForSequenceClassification from dafqi
+author: John Snow Labs
+name: indodistilbertweet
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indodistilbertweet` is a English model originally trained by dafqi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indodistilbertweet_en_5.5.0_3.0_1725277731981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indodistilbertweet_en_5.5.0_3.0_1725277731981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("indodistilbertweet","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("indodistilbertweet", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indodistilbertweet|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|467.7 MB|
+
+## References
+
+https://huggingface.co/dafqi/indoDistilBertweet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-indonesian_emotion_distilbert_base_cased_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-indonesian_emotion_distilbert_base_cased_finetuned_en.md
new file mode 100644
index 00000000000000..cfe43634e0a8a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-indonesian_emotion_distilbert_base_cased_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indonesian_emotion_distilbert_base_cased_finetuned DistilBertForSequenceClassification from AptaArkana
+author: John Snow Labs
+name: indonesian_emotion_distilbert_base_cased_finetuned
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_emotion_distilbert_base_cased_finetuned` is a English model originally trained by AptaArkana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_emotion_distilbert_base_cased_finetuned_en_5.5.0_3.0_1725306136654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_emotion_distilbert_base_cased_finetuned_en_5.5.0_3.0_1725306136654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("indonesian_emotion_distilbert_base_cased_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("indonesian_emotion_distilbert_base_cased_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_emotion_distilbert_base_cased_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/AptaArkana/indonesian-emotion-distilbert-base-cased-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-indonesian_sentiment_distilbert_base_cased_en.md b/docs/_posts/ahmedlone127/2024-09-02-indonesian_sentiment_distilbert_base_cased_en.md
new file mode 100644
index 00000000000000..0409274f3c3224
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-indonesian_sentiment_distilbert_base_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indonesian_sentiment_distilbert_base_cased DistilBertForSequenceClassification from AptaArkana
+author: John Snow Labs
+name: indonesian_sentiment_distilbert_base_cased
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_sentiment_distilbert_base_cased` is a English model originally trained by AptaArkana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_sentiment_distilbert_base_cased_en_5.5.0_3.0_1725305830237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_sentiment_distilbert_base_cased_en_5.5.0_3.0_1725305830237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("indonesian_sentiment_distilbert_base_cased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("indonesian_sentiment_distilbert_base_cased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_sentiment_distilbert_base_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/AptaArkana/indonesian_sentiment_distilbert_base_cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-indonesian_sentiment_distilbert_base_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-indonesian_sentiment_distilbert_base_cased_pipeline_en.md
new file mode 100644
index 00000000000000..ccaddb215b80bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-indonesian_sentiment_distilbert_base_cased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indonesian_sentiment_distilbert_base_cased_pipeline pipeline DistilBertForSequenceClassification from AptaArkana
+author: John Snow Labs
+name: indonesian_sentiment_distilbert_base_cased_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_sentiment_distilbert_base_cased_pipeline` is a English model originally trained by AptaArkana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_sentiment_distilbert_base_cased_pipeline_en_5.5.0_3.0_1725305857067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_sentiment_distilbert_base_cased_pipeline_en_5.5.0_3.0_1725305857067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indonesian_sentiment_distilbert_base_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indonesian_sentiment_distilbert_base_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_sentiment_distilbert_base_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/AptaArkana/indonesian_sentiment_distilbert_base_cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline_en.md
new file mode 100644
index 00000000000000..11eb45e4fa703b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline pipeline MarianTransformer from context-mt
+author: John Snow Labs
+name: iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline` is a English model originally trained by context-mt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline_en_5.5.0_3.0_1725295795916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline_en_5.5.0_3.0_1725295795916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iwslt17_marian_big_target_ctx4_cwd0_english_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/context-mt/iwslt17-marian-big-target-ctx4-cwd0-en-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-kie_semantics_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-kie_semantics_pipeline_en.md
new file mode 100644
index 00000000000000..6864e83a42bdb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-kie_semantics_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kie_semantics_pipeline pipeline DistilBertForSequenceClassification from oulmokhtar
+author: John Snow Labs
+name: kie_semantics_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kie_semantics_pipeline` is a English model originally trained by oulmokhtar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kie_semantics_pipeline_en_5.5.0_3.0_1725291615259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kie_semantics_pipeline_en_5.5.0_3.0_1725291615259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kie_semantics_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kie_semantics_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kie_semantics_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/oulmokhtar/kie-semantics
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_tchoudh8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_tchoudh8_pipeline_en.md
new file mode 100644
index 00000000000000..f899ccc00eafa1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-lab1_finetuning_tchoudh8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lab1_finetuning_tchoudh8_pipeline pipeline MarianTransformer from tchoudh8
+author: John Snow Labs
+name: lab1_finetuning_tchoudh8_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_tchoudh8_pipeline` is a English model originally trained by tchoudh8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab1_finetuning_tchoudh8_pipeline_en_5.5.0_3.0_1725304117257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_tchoudh8_pipeline_en_5.5.0_3.0_1725304117257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lab1_finetuning_tchoudh8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lab1_finetuning_tchoudh8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_finetuning_tchoudh8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.8 MB|
+
+## References
+
+https://huggingface.co/tchoudh8/lab1_finetuning
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-02-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_en.md
new file mode 100644
index 00000000000000..89280e79445f84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English learn_hf_food_not_food_text_classifier_distilbert_base_uncased DistilBertForSequenceClassification from mrdbourke
+author: John Snow Labs
+name: learn_hf_food_not_food_text_classifier_distilbert_base_uncased
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learn_hf_food_not_food_text_classifier_distilbert_base_uncased` is a English model originally trained by mrdbourke.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_en_5.5.0_3.0_1725292349116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_en_5.5.0_3.0_1725292349116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("learn_hf_food_not_food_text_classifier_distilbert_base_uncased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("learn_hf_food_not_food_text_classifier_distilbert_base_uncased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|learn_hf_food_not_food_text_classifier_distilbert_base_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mrdbourke/learn_hf_food_not_food_text_classifier-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-lenu_finnish_en.md b/docs/_posts/ahmedlone127/2024-09-02-lenu_finnish_en.md
new file mode 100644
index 00000000000000..9bf1913ef8ecd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-lenu_finnish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lenu_finnish BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_finnish
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_finnish` is a English model originally trained by Sociovestix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_finnish_en_5.5.0_3.0_1725293298918.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_finnish_en_5.5.0_3.0_1725293298918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("lenu_finnish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_finnish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_finnish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|467.0 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_FI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-less_100000_xlm_roberta_mmar_recipe_10_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-less_100000_xlm_roberta_mmar_recipe_10_base_pipeline_en.md
new file mode 100644
index 00000000000000..d1b9086f93d71c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-less_100000_xlm_roberta_mmar_recipe_10_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English less_100000_xlm_roberta_mmar_recipe_10_base_pipeline pipeline XlmRoBertaEmbeddings from CennetOguz
+author: John Snow Labs
+name: less_100000_xlm_roberta_mmar_recipe_10_base_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`less_100000_xlm_roberta_mmar_recipe_10_base_pipeline` is a English model originally trained by CennetOguz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/less_100000_xlm_roberta_mmar_recipe_10_base_pipeline_en_5.5.0_3.0_1725271212541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/less_100000_xlm_roberta_mmar_recipe_10_base_pipeline_en_5.5.0_3.0_1725271212541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("less_100000_xlm_roberta_mmar_recipe_10_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("less_100000_xlm_roberta_mmar_recipe_10_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|less_100000_xlm_roberta_mmar_recipe_10_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/CennetOguz/less_100000_xlm_roberta_mmar_recipe_10_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-lugatitdistilbert_tr.md b/docs/_posts/ahmedlone127/2024-09-02-lugatitdistilbert_tr.md
new file mode 100644
index 00000000000000..7ee8f610ce9ae1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-lugatitdistilbert_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish lugatitdistilbert DistilBertForSequenceClassification from LugatitTurk
+author: John Snow Labs
+name: lugatitdistilbert
+date: 2024-09-02
+tags: [tr, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lugatitdistilbert` is a Turkish model originally trained by LugatitTurk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lugatitdistilbert_tr_5.5.0_3.0_1725292016266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lugatitdistilbert_tr_5.5.0_3.0_1725292016266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("lugatitdistilbert","tr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("lugatitdistilbert", "tr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lugatitdistilbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|tr|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/LugatitTurk/LugatitDistilBert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_arabic_coref_exp_en.md b/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_arabic_coref_exp_en.md
new file mode 100644
index 00000000000000..4a182d3259a23f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_arabic_coref_exp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_coref_english_arabic_coref_exp MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_arabic_coref_exp
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_arabic_coref_exp` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_coref_exp_en_5.5.0_3.0_1725294648481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_coref_exp_en_5.5.0_3.0_1725294648481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_coref_english_arabic_coref_exp","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_coref_english_arabic_coref_exp","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_arabic_coref_exp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.8 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_ar_coref_exp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_arabic_coref_exp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_arabic_coref_exp_pipeline_en.md
new file mode 100644
index 00000000000000..370857d4cbd318
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-maltese_coref_english_arabic_coref_exp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English maltese_coref_english_arabic_coref_exp_pipeline pipeline MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_arabic_coref_exp_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_arabic_coref_exp_pipeline` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_coref_exp_pipeline_en_5.5.0_3.0_1725294682508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_coref_exp_pipeline_en_5.5.0_3.0_1725294682508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("maltese_coref_english_arabic_coref_exp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("maltese_coref_english_arabic_coref_exp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_arabic_coref_exp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|529.3 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_ar_coref_exp
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-maltese_en.md b/docs/_posts/ahmedlone127/2024-09-02-maltese_en.md
new file mode 100644
index 00000000000000..21916ea594cb85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-maltese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese MarianTransformer from HVD2407
+author: John Snow Labs
+name: maltese
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese` is a English model originally trained by HVD2407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_en_5.5.0_3.0_1725304971965.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_en_5.5.0_3.0_1725304971965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|522.3 MB|
+
+## References
+
+https://huggingface.co/HVD2407/mt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_en.md
new file mode 100644
index 00000000000000..0fc0f867be1a05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399 MarianTransformer from cys12399
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399` is a English model originally trained by cys12399.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_en_5.5.0_3.0_1725304551353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_en_5.5.0_3.0_1725304551353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.2 MB|
+
+## References
+
+https://huggingface.co/cys12399/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline_en.md
new file mode 100644
index 00000000000000..6fcca3c5b2ff18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline pipeline MarianTransformer from cys12399
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline` is a English model originally trained by cys12399.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline_en_5.5.0_3.0_1725304577583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline_en_5.5.0_3.0_1725304577583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_cys12399_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.8 MB|
+
+## References
+
+https://huggingface.co/cys12399/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_en.md
new file mode 100644
index 00000000000000..d907a4bdcf5887
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo MarianTransformer from sertemo
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo` is a English model originally trained by sertemo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_en_5.5.0_3.0_1725303726694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_en_5.5.0_3.0_1725303726694.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/sertemo/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline_en.md
new file mode 100644
index 00000000000000..4464b4264279f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline pipeline MarianTransformer from sertemo
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline` is a English model originally trained by sertemo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline_en_5.5.0_3.0_1725303752921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline_en_5.5.0_3.0_1725303752921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_sertemo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/sertemo/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_en.md
new file mode 100644
index 00000000000000..64c2f768006288
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh MarianTransformer from zihoh
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh` is a English model originally trained by zihoh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_en_5.5.0_3.0_1725304061687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh_en_5.5.0_3.0_1725304061687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_zihoh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.3 MB|
+
+## References
+
+https://huggingface.co/zihoh/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_en.md b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_en.md
new file mode 100644
index 00000000000000..29357cccf84099
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb MarianTransformer from sephinroth
+author: John Snow Labs
+name: marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb` is a English model originally trained by sephinroth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_en_5.5.0_3.0_1725305116917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb_en_5.5.0_3.0_1725305116917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kftt_japanese_tonga_tonga_islands_english_wandb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|515.2 MB|
+
+## References
+
+https://huggingface.co/sephinroth/marian-finetuned-kftt-ja-to-en-wandb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-marianmt_tatoeba_ruen_en.md b/docs/_posts/ahmedlone127/2024-09-02-marianmt_tatoeba_ruen_en.md
new file mode 100644
index 00000000000000..00074c3580068a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-marianmt_tatoeba_ruen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marianmt_tatoeba_ruen MarianTransformer from DeepPavlov
+author: John Snow Labs
+name: marianmt_tatoeba_ruen
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_tatoeba_ruen` is a English model originally trained by DeepPavlov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_tatoeba_ruen_en_5.5.0_3.0_1725295255041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_tatoeba_ruen_en_5.5.0_3.0_1725295255041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marianmt_tatoeba_ruen","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marianmt_tatoeba_ruen","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marianmt_tatoeba_ruen|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|527.7 MB|
+
+## References
+
+https://huggingface.co/DeepPavlov/marianmt-tatoeba-ruen
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_squad2_sjrhuschlee_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_squad2_sjrhuschlee_en.md
new file mode 100644
index 00000000000000..dedd8a2a02b76f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_v3_base_squad2_sjrhuschlee_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mdeberta_v3_base_squad2_sjrhuschlee DeBertaForQuestionAnswering from sjrhuschlee
+author: John Snow Labs
+name: mdeberta_v3_base_squad2_sjrhuschlee
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, deberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_squad2_sjrhuschlee` is a English model originally trained by sjrhuschlee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_squad2_sjrhuschlee_en_5.5.0_3.0_1725268756540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_squad2_sjrhuschlee_en_5.5.0_3.0_1725268756540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_squad2_sjrhuschlee","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_squad2_sjrhuschlee", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_squad2_sjrhuschlee|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|854.1 MB|
+
+## References
+
+https://huggingface.co/sjrhuschlee/mdeberta-v3-base-squad2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_en.md
new file mode 100644
index 00000000000000..76e50b63303040
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0 DeBertaForQuestionAnswering from pgajo
+author: John Snow Labs
+name: mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, deberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0` is a English model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_en_5.5.0_3.0_1725269395147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0_en_5.5.0_3.0_1725269395147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u0_s1_tingredient_p0_75_drop1_mdeberta_e4_dev98_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|817.4 MB|
+
+## References
+
+https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U0_S1_Tingredient_P0.75_DROP1_mdeberta_E4_DEV98.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en.md b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en.md
new file mode 100644
index 00000000000000..85268c4e4b4d26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0 DeBertaForQuestionAnswering from pgajo
+author: John Snow Labs
+name: mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, deberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0` is a English model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en_5.5.0_3.0_1725240458067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0_en_5.5.0_3.0_1725240458067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_xlwa_english_italian_ew_tatar_pe_u1_s0_drop1_mdeberta_e2_dev100_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|818.7 MB|
+
+## References
+
+https://huggingface.co/pgajo/mdeberta-xlwa-en-it_EW-TT-PE_U1_S0_DROP1_mdeberta_E2_DEV100.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-memo_final_en.md b/docs/_posts/ahmedlone127/2024-09-02-memo_final_en.md
new file mode 100644
index 00000000000000..c8e875babc4b20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-memo_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English memo_final XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: memo_final
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_final` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_final_en_5.5.0_3.0_1725270351488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_final_en_5.5.0_3.0_1725270351488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("memo_final","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("memo_final","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_final|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-memo_model_3500_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-memo_model_3500_pipeline_en.md
new file mode 100644
index 00000000000000..28e50c3bfa8536
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-memo_model_3500_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English memo_model_3500_pipeline pipeline XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: memo_model_3500_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_model_3500_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_model_3500_pipeline_en_5.5.0_3.0_1725270813380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_model_3500_pipeline_en_5.5.0_3.0_1725270813380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("memo_model_3500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("memo_model_3500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_model_3500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_model_3500
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mformer_fairness_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mformer_fairness_pipeline_en.md
new file mode 100644
index 00000000000000..0133f07eb71e01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mformer_fairness_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mformer_fairness_pipeline pipeline RoBertaForSequenceClassification from joshnguyen
+author: John Snow Labs
+name: mformer_fairness_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mformer_fairness_pipeline` is a English model originally trained by joshnguyen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mformer_fairness_pipeline_en_5.5.0_3.0_1725238112026.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mformer_fairness_pipeline_en_5.5.0_3.0_1725238112026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mformer_fairness_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mformer_fairness_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mformer_fairness_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.8 MB|
+
+## References
+
+https://huggingface.co/joshnguyen/mformer-fairness
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-misinformation_trainer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-misinformation_trainer_pipeline_en.md
new file mode 100644
index 00000000000000..b2e5504fd86b8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-misinformation_trainer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English misinformation_trainer_pipeline pipeline DistilBertForSequenceClassification from AIUs3r0
+author: John Snow Labs
+name: misinformation_trainer_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`misinformation_trainer_pipeline` is a English model originally trained by AIUs3r0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/misinformation_trainer_pipeline_en_5.5.0_3.0_1725292069592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/misinformation_trainer_pipeline_en_5.5.0_3.0_1725292069592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("misinformation_trainer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("misinformation_trainer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|misinformation_trainer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AIUs3r0/Misinformation_Trainer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mix2_english_japanese_helsinki_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mix2_english_japanese_helsinki_pipeline_en.md
new file mode 100644
index 00000000000000..754d97719b6811
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mix2_english_japanese_helsinki_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mix2_english_japanese_helsinki_pipeline pipeline MarianTransformer from twieland
+author: John Snow Labs
+name: mix2_english_japanese_helsinki_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix2_english_japanese_helsinki_pipeline` is a English model originally trained by twieland.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mix2_english_japanese_helsinki_pipeline_en_5.5.0_3.0_1725304560511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix2_english_japanese_helsinki_pipeline_en_5.5.0_3.0_1725304560511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mix2_english_japanese_helsinki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mix2_english_japanese_helsinki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mix2_english_japanese_helsinki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|434.8 MB|
+
+## References
+
+https://huggingface.co/twieland/MIX2_en-ja_helsinki
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline_en.md
new file mode 100644
index 00000000000000..8b5887d605b02b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline pipeline BertForQuestionAnswering from mrm8488
+author: John Snow Labs
+name: mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline_en_5.5.0_3.0_1725312622294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline_en_5.5.0_3.0_1725312622294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mobilebert_uncased_finetuned_squadv1_mrm8488_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|92.5 MB|
+
+## References
+
+https://huggingface.co/mrm8488/mobilebert-uncased-finetuned-squadv1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-model_3_edges_beloiual_en.md b/docs/_posts/ahmedlone127/2024-09-02-model_3_edges_beloiual_en.md
new file mode 100644
index 00000000000000..5854030906556c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-model_3_edges_beloiual_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_3_edges_beloiual DistilBertForTokenClassification from beloiual
+author: John Snow Labs
+name: model_3_edges_beloiual
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_3_edges_beloiual` is a English model originally trained by beloiual.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_3_edges_beloiual_en_5.5.0_3.0_1725267399913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_3_edges_beloiual_en_5.5.0_3.0_1725267399913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("model_3_edges_beloiual","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("model_3_edges_beloiual", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_3_edges_beloiual|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/beloiual/model_3_edges
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-model_rikvc_es.md b/docs/_posts/ahmedlone127/2024-09-02-model_rikvc_es.md
new file mode 100644
index 00000000000000..013166f8ac7b79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-model_rikvc_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish model_rikvc CamemBertEmbeddings from ovieyra21
+author: John Snow Labs
+name: model_rikvc
+date: 2024-09-02
+tags: [es, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_rikvc` is a Castilian, Spanish model originally trained by ovieyra21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_rikvc_es_5.5.0_3.0_1725320708465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_rikvc_es_5.5.0_3.0_1725320708465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("model_rikvc","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("model_rikvc","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_rikvc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|es|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ovieyra21/model-rikvc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_pipeline_en.md
new file mode 100644
index 00000000000000..690f742089b21d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_nli_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_base_nli_pipeline pipeline MPNetEmbeddings from tomaarsen
+author: John Snow Labs
+name: mpnet_base_nli_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_nli_pipeline` is a English model originally trained by tomaarsen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_pipeline_en_5.5.0_3.0_1725258466814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_pipeline_en_5.5.0_3.0_1725258466814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mpnet_base_nli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_base_nli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_nli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.4 MB|
+
+## References
+
+https://huggingface.co/tomaarsen/mpnet-base-nli
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_v2_ukgov_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_v2_ukgov_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..ac4516f5f78726
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mpnet_base_v2_ukgov_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_base_v2_ukgov_finetuned_pipeline pipeline MPNetEmbeddings from AndreasThinks
+author: John Snow Labs
+name: mpnet_base_v2_ukgov_finetuned_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_v2_ukgov_finetuned_pipeline` is a English model originally trained by AndreasThinks.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_v2_ukgov_finetuned_pipeline_en_5.5.0_3.0_1725313999086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_v2_ukgov_finetuned_pipeline_en_5.5.0_3.0_1725313999086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mpnet_base_v2_ukgov_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_base_v2_ukgov_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_v2_ukgov_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/AndreasThinks/mpnet-base-v2-ukgov-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mrc_xlmr_base_dsc_en.md b/docs/_posts/ahmedlone127/2024-09-02-mrc_xlmr_base_dsc_en.md
new file mode 100644
index 00000000000000..76bde9f29d476f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mrc_xlmr_base_dsc_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mrc_xlmr_base_dsc XlmRoBertaForQuestionAnswering from MiuN2k3
+author: John Snow Labs
+name: mrc_xlmr_base_dsc
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mrc_xlmr_base_dsc` is a English model originally trained by MiuN2k3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mrc_xlmr_base_dsc_en_5.5.0_3.0_1725253989638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mrc_xlmr_base_dsc_en_5.5.0_3.0_1725253989638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("mrc_xlmr_base_dsc","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("mrc_xlmr_base_dsc", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mrc_xlmr_base_dsc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|815.8 MB|
+
+## References
+
+https://huggingface.co/MiuN2k3/mrc-xlmr-base-dsc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mrpc_microsoft_deberta_v3_base_seed_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-mrpc_microsoft_deberta_v3_base_seed_1_en.md
new file mode 100644
index 00000000000000..f8b9056fea8272
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mrpc_microsoft_deberta_v3_base_seed_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mrpc_microsoft_deberta_v3_base_seed_1 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: mrpc_microsoft_deberta_v3_base_seed_1
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mrpc_microsoft_deberta_v3_base_seed_1` is a English model originally trained by utahnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mrpc_microsoft_deberta_v3_base_seed_1_en_5.5.0_3.0_1725282210907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mrpc_microsoft_deberta_v3_base_seed_1_en_5.5.0_3.0_1725282210907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mrpc_microsoft_deberta_v3_base_seed_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mrpc_microsoft_deberta_v3_base_seed_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mrpc_microsoft_deberta_v3_base_seed_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|573.9 MB|
+
+## References
+
+https://huggingface.co/utahnlp/mrpc_microsoft_deberta-v3-base_seed-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_sw.md b/docs/_posts/ahmedlone127/2024-09-02-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_sw.md
new file mode 100644
index 00000000000000..3204162c2beaee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_sw.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Swahili (macrolanguage) multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline pipeline BGEEmbeddings from sartifyllc
+author: John Snow Labs
+name: multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline
+date: 2024-09-02
+tags: [sw, open_source, pipeline, onnx]
+task: Embeddings
+language: sw
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline` is a Swahili (macrolanguage) model originally trained by sartifyllc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_sw_5.5.0_3.0_1725263638853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_sw_5.5.0_3.0_1725263638853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline", lang = "sw")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline", lang = "sw")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sw|
+|Size:|122.9 MB|
+
+## References
+
+https://huggingface.co/sartifyllc/MultiLinguSwahili-bge-small-en-v1.5-nli-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_sw.md b/docs/_posts/ahmedlone127/2024-09-02-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_sw.md
new file mode 100644
index 00000000000000..14c6a88fbdd268
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_sw.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: Swahili (macrolanguage) multilinguswahili_bge_small_english_v1_5_nli_matryoshka BGEEmbeddings from sartifyllc
+author: John Snow Labs
+name: multilinguswahili_bge_small_english_v1_5_nli_matryoshka
+date: 2024-09-02
+tags: [sw, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: sw
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilinguswahili_bge_small_english_v1_5_nli_matryoshka` is a Swahili (macrolanguage) model originally trained by sartifyllc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilinguswahili_bge_small_english_v1_5_nli_matryoshka_sw_5.5.0_3.0_1725263632069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilinguswahili_bge_small_english_v1_5_nli_matryoshka_sw_5.5.0_3.0_1725263632069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("multilinguswahili_bge_small_english_v1_5_nli_matryoshka","sw") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("multilinguswahili_bge_small_english_v1_5_nli_matryoshka","sw") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilinguswahili_bge_small_english_v1_5_nli_matryoshka|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|sw|
+|Size:|122.8 MB|
+
+## References
+
+https://huggingface.co/sartifyllc/MultiLinguSwahili-bge-small-en-v1.5-nli-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-mytextcheck_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-mytextcheck_pipeline_en.md
new file mode 100644
index 00000000000000..8b8ac8465d919b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-mytextcheck_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mytextcheck_pipeline pipeline DistilBertForSequenceClassification from Jnanesh12
+author: John Snow Labs
+name: mytextcheck_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mytextcheck_pipeline` is a English model originally trained by Jnanesh12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mytextcheck_pipeline_en_5.5.0_3.0_1725305957947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mytextcheck_pipeline_en_5.5.0_3.0_1725305957947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mytextcheck_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mytextcheck_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mytextcheck_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Jnanesh12/MyTextCheck
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-national_climate_targets_en.md b/docs/_posts/ahmedlone127/2024-09-02-national_climate_targets_en.md
new file mode 100644
index 00000000000000..16c3e855600c1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-national_climate_targets_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English national_climate_targets RoBertaForSequenceClassification from ClimatePolicyRadar
+author: John Snow Labs
+name: national_climate_targets
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`national_climate_targets` is a English model originally trained by ClimatePolicyRadar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/national_climate_targets_en_5.5.0_3.0_1725238321193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/national_climate_targets_en_5.5.0_3.0_1725238321193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("national_climate_targets","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("national_climate_targets", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|national_climate_targets|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|309.6 MB|
+
+## References
+
+https://huggingface.co/ClimatePolicyRadar/national-climate-targets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-nermembert_base_4entities_fr.md b/docs/_posts/ahmedlone127/2024-09-02-nermembert_base_4entities_fr.md
new file mode 100644
index 00000000000000..2e8fd4e90b9c97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-nermembert_base_4entities_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French nermembert_base_4entities CamemBertForTokenClassification from CATIE-AQ
+author: John Snow Labs
+name: nermembert_base_4entities
+date: 2024-09-02
+tags: [fr, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nermembert_base_4entities` is a French model originally trained by CATIE-AQ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nermembert_base_4entities_fr_5.5.0_3.0_1725265990216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nermembert_base_4entities_fr_5.5.0_3.0_1725265990216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("nermembert_base_4entities","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("nermembert_base_4entities", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nermembert_base_4entities|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|fr|
+|Size:|412.0 MB|
+
+## References
+
+https://huggingface.co/CATIE-AQ/NERmembert-base-4entities
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-nooks_amd_detection_full_en.md b/docs/_posts/ahmedlone127/2024-09-02-nooks_amd_detection_full_en.md
new file mode 100644
index 00000000000000..e4b55f95446725
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-nooks_amd_detection_full_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nooks_amd_detection_full MPNetEmbeddings from nikcheerla
+author: John Snow Labs
+name: nooks_amd_detection_full
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nooks_amd_detection_full` is a English model originally trained by nikcheerla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nooks_amd_detection_full_en_5.5.0_3.0_1725280849501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nooks_amd_detection_full_en_5.5.0_3.0_1725280849501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("nooks_amd_detection_full","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("nooks_amd_detection_full","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nooks_amd_detection_full|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/nikcheerla/nooks-amd-detection-full
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-nooks_amd_detection_full_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-nooks_amd_detection_full_pipeline_en.md
new file mode 100644
index 00000000000000..340b6f44a3b4d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-nooks_amd_detection_full_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nooks_amd_detection_full_pipeline pipeline MPNetEmbeddings from nikcheerla
+author: John Snow Labs
+name: nooks_amd_detection_full_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nooks_amd_detection_full_pipeline` is a English model originally trained by nikcheerla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nooks_amd_detection_full_pipeline_en_5.5.0_3.0_1725280870949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nooks_amd_detection_full_pipeline_en_5.5.0_3.0_1725280870949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nooks_amd_detection_full_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nooks_amd_detection_full_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nooks_amd_detection_full_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/nikcheerla/nooks-amd-detection-full
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_bert_ncc_male2female_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_bert_ncc_male2female_pipeline_en.md
new file mode 100644
index 00000000000000..73fad9c448ec3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-norwegian_bokml_bert_ncc_male2female_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English norwegian_bokml_bert_ncc_male2female_pipeline pipeline BertEmbeddings from NbAiLab
+author: John Snow Labs
+name: norwegian_bokml_bert_ncc_male2female_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_ncc_male2female_pipeline` is a English model originally trained by NbAiLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_ncc_male2female_pipeline_en_5.5.0_3.0_1725318943815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_ncc_male2female_pipeline_en_5.5.0_3.0_1725318943815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("norwegian_bokml_bert_ncc_male2female_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("norwegian_bokml_bert_ncc_male2female_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|norwegian_bokml_bert_ncc_male2female_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|666.0 MB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-bert-ncc-male2female
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-nuner_v1_fewnerd_fine_super_en.md b/docs/_posts/ahmedlone127/2024-09-02-nuner_v1_fewnerd_fine_super_en.md
new file mode 100644
index 00000000000000..088f8df7d5fea4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-nuner_v1_fewnerd_fine_super_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nuner_v1_fewnerd_fine_super RoBertaForTokenClassification from guishe
+author: John Snow Labs
+name: nuner_v1_fewnerd_fine_super
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuner_v1_fewnerd_fine_super` is a English model originally trained by guishe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nuner_v1_fewnerd_fine_super_en_5.5.0_3.0_1725311342386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuner_v1_fewnerd_fine_super_en_5.5.0_3.0_1725311342386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("nuner_v1_fewnerd_fine_super","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("nuner_v1_fewnerd_fine_super", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuner_v1_fewnerd_fine_super|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|462.6 MB|
+
+## References
+
+https://huggingface.co/guishe/nuner-v1_fewnerd_fine_super
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-nuner_v1_fewnerd_fine_super_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-nuner_v1_fewnerd_fine_super_pipeline_en.md
new file mode 100644
index 00000000000000..0d89858b975bca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-nuner_v1_fewnerd_fine_super_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nuner_v1_fewnerd_fine_super_pipeline pipeline RoBertaForTokenClassification from guishe
+author: John Snow Labs
+name: nuner_v1_fewnerd_fine_super_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuner_v1_fewnerd_fine_super_pipeline` is a English model originally trained by guishe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nuner_v1_fewnerd_fine_super_pipeline_en_5.5.0_3.0_1725311366414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuner_v1_fewnerd_fine_super_pipeline_en_5.5.0_3.0_1725311366414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nuner_v1_fewnerd_fine_super_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nuner_v1_fewnerd_fine_super_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuner_v1_fewnerd_fine_super_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.7 MB|
+
+## References
+
+https://huggingface.co/guishe/nuner-v1_fewnerd_fine_super
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-ofa_multi_400_en.md b/docs/_posts/ahmedlone127/2024-09-02-ofa_multi_400_en.md
new file mode 100644
index 00000000000000..ed465d55636062
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-ofa_multi_400_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ofa_multi_400 XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: ofa_multi_400
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ofa_multi_400` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ofa_multi_400_en_5.5.0_3.0_1725271597953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ofa_multi_400_en_5.5.0_3.0_1725271597953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("ofa_multi_400","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("ofa_multi_400","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ofa_multi_400|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/ofa-multi-400
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_en.md b/docs/_posts/ahmedlone127/2024-09-02-open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_en.md
new file mode 100644
index 00000000000000..66238d732c7fbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate MarianTransformer from kaiku03
+author: John Snow Labs
+name: open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate` is a English model originally trained by kaiku03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_en_5.5.0_3.0_1725294487013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate_en_5.5.0_3.0_1725294487013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|open_subtitles_finetuned_opus_maltese_english_tagalog_accelerate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|496.6 MB|
+
+## References
+
+https://huggingface.co/kaiku03/open_subtitles-finetuned-opus-mt-en-tl-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-optimizer_ner_finetune_lst2021_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-optimizer_ner_finetune_lst2021_pipeline_en.md
new file mode 100644
index 00000000000000..28fd34703a80a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-optimizer_ner_finetune_lst2021_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English optimizer_ner_finetune_lst2021_pipeline pipeline CamemBertForTokenClassification from famodde
+author: John Snow Labs
+name: optimizer_ner_finetune_lst2021_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`optimizer_ner_finetune_lst2021_pipeline` is a English model originally trained by famodde.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/optimizer_ner_finetune_lst2021_pipeline_en_5.5.0_3.0_1725266674264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/optimizer_ner_finetune_lst2021_pipeline_en_5.5.0_3.0_1725266674264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("optimizer_ner_finetune_lst2021_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("optimizer_ner_finetune_lst2021_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|optimizer_ner_finetune_lst2021_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/famodde/optimizer-ner-fineTune-lst2021
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_base_simple_freq_wce_unsampled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_base_simple_freq_wce_unsampled_pipeline_en.md
new file mode 100644
index 00000000000000..07da0177e5fe43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-opus_base_simple_freq_wce_unsampled_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_base_simple_freq_wce_unsampled_pipeline pipeline MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_base_simple_freq_wce_unsampled_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_base_simple_freq_wce_unsampled_pipeline` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_base_simple_freq_wce_unsampled_pipeline_en_5.5.0_3.0_1725304878287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_base_simple_freq_wce_unsampled_pipeline_en_5.5.0_3.0_1725304878287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_base_simple_freq_wce_unsampled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_base_simple_freq_wce_unsampled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_base_simple_freq_wce_unsampled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.9 MB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_base_simple_freq_wce_unsampled
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_big_wce_antagonistic_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_big_wce_antagonistic_en.md
new file mode 100644
index 00000000000000..82eec722b4aeed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-opus_big_wce_antagonistic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_big_wce_antagonistic MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_big_wce_antagonistic
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_wce_antagonistic` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_big_wce_antagonistic_en_5.5.0_3.0_1725304318554.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_wce_antagonistic_en_5.5.0_3.0_1725304318554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_big_wce_antagonistic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_big_wce_antagonistic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_big_wce_antagonistic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_big_wce_antagonistic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_en.md
new file mode 100644
index 00000000000000..67a81c7dddad48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-opus_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus MarianTransformer from andrejaystevenson
+author: John Snow Labs
+name: opus
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus` is a English model originally trained by andrejaystevenson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_en_5.5.0_3.0_1725304799435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_en_5.5.0_3.0_1725304799435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|330.1 MB|
+
+## References
+
+https://huggingface.co/andrejaystevenson/opus
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v2_pipeline_en.md
new file mode 100644
index 00000000000000..e24779dfe82066
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_cantonese_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_cantonese_v2_pipeline pipeline MarianTransformer from edwinlaw
+author: John Snow Labs
+name: opus_maltese_cantonese_v2_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_cantonese_v2_pipeline` is a English model originally trained by edwinlaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_cantonese_v2_pipeline_en_5.5.0_3.0_1725295476226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_cantonese_v2_pipeline_en_5.5.0_3.0_1725295476226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_cantonese_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_cantonese_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_cantonese_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|541.2 MB|
+
+## References
+
+https://huggingface.co/edwinlaw/opus-mt-cantonese-v2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_en.md
new file mode 100644
index 00000000000000..f8b78d5d8819ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667 MarianTransformer from dagger667
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667` is a English model originally trained by dagger667.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_en_5.5.0_3.0_1725295273619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667_en_5.5.0_3.0_1725295273619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dagger667|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/dagger667/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_portuguese_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_portuguese_english_en.md
new file mode 100644
index 00000000000000..55a18e42ea3b7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_portuguese_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_portuguese_english MarianTransformer from geralt
+author: John Snow Labs
+name: opus_maltese_portuguese_english
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_portuguese_english` is a English model originally trained by geralt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_portuguese_english_en_5.5.0_3.0_1725295251055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_portuguese_english_en_5.5.0_3.0_1725295251055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_portuguese_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_portuguese_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_portuguese_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|321.5 MB|
+
+## References
+
+https://huggingface.co/geralt/Opus-mt-pt-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline_en.md
new file mode 100644
index 00000000000000..eaf8c93275356a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline pipeline MarianTransformer from akardashova
+author: John Snow Labs
+name: opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline` is a English model originally trained by akardashova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline_en_5.5.0_3.0_1725305215174.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline_en_5.5.0_3.0_1725305215174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_akardashova_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|526.9 MB|
+
+## References
+
+https://huggingface.co/akardashova/opus-mt-ru-en-finetuned-ru-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..9e9a9b2242b76b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english MarianTransformer from PontifexMaximus
+author: John Snow Labs
+name: opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english` is a English model originally trained by PontifexMaximus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_en_5.5.0_3.0_1725243888120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english_en_5.5.0_3.0_1725243888120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_urdu_english_finetuned_urdu_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|520.8 MB|
+
+## References
+
+https://huggingface.co/PontifexMaximus/opus-mt-ur-en-finetuned-ur-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-phdthesis_recognizer_en.md b/docs/_posts/ahmedlone127/2024-09-02-phdthesis_recognizer_en.md
new file mode 100644
index 00000000000000..8b1ed1ee1a0e55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-phdthesis_recognizer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English phdthesis_recognizer DistilBertForSequenceClassification from LaLaf93
+author: John Snow Labs
+name: phdthesis_recognizer
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phdthesis_recognizer` is a English model originally trained by LaLaf93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phdthesis_recognizer_en_5.5.0_3.0_1725292243192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phdthesis_recognizer_en_5.5.0_3.0_1725292243192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("phdthesis_recognizer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("phdthesis_recognizer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|phdthesis_recognizer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LaLaf93/phdthesis_recognizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-phdthesis_recognizer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-phdthesis_recognizer_pipeline_en.md
new file mode 100644
index 00000000000000..a2be4e797817e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-phdthesis_recognizer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English phdthesis_recognizer_pipeline pipeline DistilBertForSequenceClassification from LaLaf93
+author: John Snow Labs
+name: phdthesis_recognizer_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phdthesis_recognizer_pipeline` is a English model originally trained by LaLaf93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phdthesis_recognizer_pipeline_en_5.5.0_3.0_1725292255981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phdthesis_recognizer_pipeline_en_5.5.0_3.0_1725292255981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("phdthesis_recognizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("phdthesis_recognizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|phdthesis_recognizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LaLaf93/phdthesis_recognizer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-pubchem10m_smiles_bpe_60k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-pubchem10m_smiles_bpe_60k_pipeline_en.md
new file mode 100644
index 00000000000000..3e3e275b0642fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-pubchem10m_smiles_bpe_60k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pubchem10m_smiles_bpe_60k_pipeline pipeline RoBertaEmbeddings from seyonec
+author: John Snow Labs
+name: pubchem10m_smiles_bpe_60k_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubchem10m_smiles_bpe_60k_pipeline` is a English model originally trained by seyonec.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_60k_pipeline_en_5.5.0_3.0_1725264282393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_60k_pipeline_en_5.5.0_3.0_1725264282393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pubchem10m_smiles_bpe_60k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pubchem10m_smiles_bpe_60k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubchem10m_smiles_bpe_60k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|310.2 MB|
+
+## References
+
+https://huggingface.co/seyonec/PubChem10M_SMILES_BPE_60k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_en.md b/docs/_posts/ahmedlone127/2024-09-02-re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_en.md
new file mode 100644
index 00000000000000..b4fa90976548fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned XlmRoBertaForTokenClassification from ajtamayoh
+author: John Snow Labs
+name: re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned` is a English model originally trained by ajtamayoh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_en_5.5.0_3.0_1725308247716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned_en_5.5.0_3.0_1725308247716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|re_negref_nsd_nubes_training_development_dataset_xlm_roberta_base_fine_tuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.2 MB|
+
+## References
+
+https://huggingface.co/ajtamayoh/RE_NegREF_NSD_Nubes_Training_Development_dataset_xlm_RoBERTa_base_fine_tuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-readabert_french_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-02-readabert_french_pipeline_fr.md
new file mode 100644
index 00000000000000..7ecfe47c048254
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-readabert_french_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French readabert_french_pipeline pipeline CamemBertForSequenceClassification from tareknaous
+author: John Snow Labs
+name: readabert_french_pipeline
+date: 2024-09-02
+tags: [fr, open_source, pipeline, onnx]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`readabert_french_pipeline` is a French model originally trained by tareknaous.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/readabert_french_pipeline_fr_5.5.0_3.0_1725299151014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/readabert_french_pipeline_fr_5.5.0_3.0_1725299151014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("readabert_french_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("readabert_french_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|readabert_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|393.2 MB|
+
+## References
+
+https://huggingface.co/tareknaous/readabert-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-reward_deberta_v3_large_aspect_xx.md b/docs/_posts/ahmedlone127/2024-09-02-reward_deberta_v3_large_aspect_xx.md
new file mode 100644
index 00000000000000..6e911cdb9a9dac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-reward_deberta_v3_large_aspect_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual reward_deberta_v3_large_aspect DeBertaForSequenceClassification from theblackcat102
+author: John Snow Labs
+name: reward_deberta_v3_large_aspect
+date: 2024-09-02
+tags: [xx, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reward_deberta_v3_large_aspect` is a Multilingual model originally trained by theblackcat102.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reward_deberta_v3_large_aspect_xx_5.5.0_3.0_1725281798100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reward_deberta_v3_large_aspect_xx_5.5.0_3.0_1725281798100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("reward_deberta_v3_large_aspect","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("reward_deberta_v3_large_aspect", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|reward_deberta_v3_large_aspect|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/theblackcat102/reward-deberta-v3-large-aspect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_bne_capitel_sayula_popoluca_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_bne_capitel_sayula_popoluca_es.md
new file mode 100644
index 00000000000000..57233a04f5c38f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_bne_capitel_sayula_popoluca_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_bne_capitel_sayula_popoluca RoBertaForTokenClassification from BSC-LT
+author: John Snow Labs
+name: roberta_base_bne_capitel_sayula_popoluca
+date: 2024-09-02
+tags: [es, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_capitel_sayula_popoluca` is a Castilian, Spanish model originally trained by BSC-LT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_capitel_sayula_popoluca_es_5.5.0_3.0_1725310698368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_capitel_sayula_popoluca_es_5.5.0_3.0_1725310698368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_bne_capitel_sayula_popoluca","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_bne_capitel_sayula_popoluca", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_bne_capitel_sayula_popoluca|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|446.5 MB|
+
+## References
+
+https://huggingface.co/BSC-LT/roberta-base-bne-capitel-pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_bne_capitel_sayula_popoluca_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_bne_capitel_sayula_popoluca_pipeline_es.md
new file mode 100644
index 00000000000000..46d219dda95e12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_bne_capitel_sayula_popoluca_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_bne_capitel_sayula_popoluca_pipeline pipeline RoBertaForTokenClassification from BSC-LT
+author: John Snow Labs
+name: roberta_base_bne_capitel_sayula_popoluca_pipeline
+date: 2024-09-02
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_capitel_sayula_popoluca_pipeline` is a Castilian, Spanish model originally trained by BSC-LT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_capitel_sayula_popoluca_pipeline_es_5.5.0_3.0_1725310722403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_capitel_sayula_popoluca_pipeline_es_5.5.0_3.0_1725310722403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_bne_capitel_sayula_popoluca_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_bne_capitel_sayula_popoluca_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_bne_capitel_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|446.5 MB|
+
+## References
+
+https://huggingface.co/BSC-LT/roberta-base-bne-capitel-pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_nepali_pipeline_ne.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_nepali_pipeline_ne.md
new file mode 100644
index 00000000000000..3ba26bb3df7e32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_nepali_pipeline_ne.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Nepali (macrolanguage) roberta_base_nepali_pipeline pipeline RoBertaEmbeddings from amitness
+author: John Snow Labs
+name: roberta_base_nepali_pipeline
+date: 2024-09-02
+tags: [ne, open_source, pipeline, onnx]
+task: Embeddings
+language: ne
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_nepali_pipeline` is a Nepali (macrolanguage) model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_nepali_pipeline_ne_5.5.0_3.0_1725264519567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_nepali_pipeline_ne_5.5.0_3.0_1725264519567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_nepali_pipeline", lang = "ne")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_nepali_pipeline", lang = "ne")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_nepali_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ne|
+|Size:|311.9 MB|
+
+## References
+
+https://huggingface.co/amitness/roberta-base-ne
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_base_suicide_prediction_phr_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_suicide_prediction_phr_v2_pipeline_en.md
new file mode 100644
index 00000000000000..b36bc7ed814921
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_base_suicide_prediction_phr_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_suicide_prediction_phr_v2_pipeline pipeline RoBertaForSequenceClassification from vibhorag101
+author: John Snow Labs
+name: roberta_base_suicide_prediction_phr_v2_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_suicide_prediction_phr_v2_pipeline` is a English model originally trained by vibhorag101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_suicide_prediction_phr_v2_pipeline_en_5.5.0_3.0_1725277032607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_suicide_prediction_phr_v2_pipeline_en_5.5.0_3.0_1725277032607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_suicide_prediction_phr_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_suicide_prediction_phr_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_suicide_prediction_phr_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.0 MB|
+
+## References
+
+https://huggingface.co/vibhorag101/roberta-base-suicide-prediction-phr-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_legal_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_legal_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..ba0f31197da21d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_embeddings_legal_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_embeddings_legal_roberta_base_pipeline pipeline RoBertaEmbeddings from saibo
+author: John Snow Labs
+name: roberta_embeddings_legal_roberta_base_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_embeddings_legal_roberta_base_pipeline` is a English model originally trained by saibo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_legal_roberta_base_pipeline_en_5.5.0_3.0_1725264410183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_legal_roberta_base_pipeline_en_5.5.0_3.0_1725264410183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_embeddings_legal_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_embeddings_legal_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_embeddings_legal_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/saibo/legal-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_bne_es.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_bne_es.md
new file mode 100644
index 00000000000000..3fd0db4a8d6c0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_bne_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish roberta_large_bne RoBertaEmbeddings from BSC-LT
+author: John Snow Labs
+name: roberta_large_bne
+date: 2024-09-02
+tags: [es, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_bne` is a Castilian, Spanish model originally trained by BSC-LT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_bne_es_5.5.0_3.0_1725264304283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_bne_es_5.5.0_3.0_1725264304283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_bne","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_bne","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_bne|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|es|
+|Size:|843.3 MB|
+
+## References
+
+https://huggingface.co/BSC-LT/roberta-large-bne
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_cola_krishna2020_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_cola_krishna2020_pipeline_en.md
new file mode 100644
index 00000000000000..96ddf4158b1376
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_cola_krishna2020_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_cola_krishna2020_pipeline pipeline RoBertaForSequenceClassification from cointegrated
+author: John Snow Labs
+name: roberta_large_cola_krishna2020_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_cola_krishna2020_pipeline` is a English model originally trained by cointegrated.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_cola_krishna2020_pipeline_en_5.5.0_3.0_1725278565985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_cola_krishna2020_pipeline_en_5.5.0_3.0_1725278565985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_cola_krishna2020_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_cola_krishna2020_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_cola_krishna2020_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|845.3 MB|
+
+## References
+
+https://huggingface.co/cointegrated/roberta-large-cola-krishna2020
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pipeline_en.md
new file mode 100644
index 00000000000000..5c075f6643f148
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_pipeline pipeline RoBertaEmbeddings from FacebookAI
+author: John Snow Labs
+name: roberta_large_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_pipeline` is a English model originally trained by FacebookAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_pipeline_en_5.5.0_3.0_1725265768430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_pipeline_en_5.5.0_3.0_1725265768430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|842.5 MB|
+
+## References
+
+https://huggingface.co/FacebookAI/roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_swiss_legal_pipeline_gsw.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_swiss_legal_pipeline_gsw.md
new file mode 100644
index 00000000000000..57c68050e918eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_swiss_legal_pipeline_gsw.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Alemannic, Alsatian, Swiss German roberta_large_swiss_legal_pipeline pipeline RoBertaEmbeddings from joelito
+author: John Snow Labs
+name: roberta_large_swiss_legal_pipeline
+date: 2024-09-02
+tags: [gsw, open_source, pipeline, onnx]
+task: Embeddings
+language: gsw
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_swiss_legal_pipeline` is a Alemannic, Alsatian, Swiss German model originally trained by joelito.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_swiss_legal_pipeline_gsw_5.5.0_3.0_1725264317049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_swiss_legal_pipeline_gsw_5.5.0_3.0_1725264317049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_swiss_legal_pipeline", lang = "gsw")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_swiss_legal_pipeline", lang = "gsw")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_swiss_legal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|gsw|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/joelito/legal-swiss-roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_large_yelp2class_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_yelp2class_pipeline_en.md
new file mode 100644
index 00000000000000..81c79c69872a41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_large_yelp2class_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_yelp2class_pipeline pipeline RoBertaForSequenceClassification from Siki-77
+author: John Snow Labs
+name: roberta_large_yelp2class_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_yelp2class_pipeline` is a English model originally trained by Siki-77.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_yelp2class_pipeline_en_5.5.0_3.0_1725238121518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_yelp2class_pipeline_en_5.5.0_3.0_1725238121518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_yelp2class_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_yelp2class_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_yelp2class_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Siki-77/roberta_large_yelp2class
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_codeberta_MT4TS_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_codeberta_MT4TS_en.md
new file mode 100644
index 00000000000000..521d554c2bfbc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_codeberta_MT4TS_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForTokenClassification Cased model (from kevinjesse)
+author: John Snow Labs
+name: roberta_ner_codeberta_MT4TS
+date: 2024-09-02
+tags: [bert, ner, open_source, en, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `codeberta-MT4TS` is a English model originally trained by `kevinjesse`.
+
+## Predicted Entities
+
+`Framebuffer`, `CryptoService`, `ClientLocation`, `AliasMapEntry`, `KeysType`, `CodeGen`, `DOMExplorerClient`, `GetAssessmentCommandInput`, `OnSaveProps`, `IKeyBinding`, `FirmwareUpdateMetaDataCC`, `DropHandlerProps`, `UpdateApplicationCommand`, `ItemProperties`, `CreateTopicResponse`, `HttpInterceptor`, `ClusterOptions`, `ex.PostUpdateEvent`, `AddTagsToResourceCommand`, `HookContext`, `LogFormatter`, `VisibilityEdge`, `BaseRoute`, `IpcRendererService`, `VocabularySortType`, `TweetItem`, `TwStyle`, `AbstractStatusBarLabelItem`, `GetByEmailAccountsValidationResult`, `TypeValues`, `Utxo`, `IGetRefParamsExternal`, `SubDirectory`, `Promisable`, `TRoutes`, `HostRef`, `DeleteGroupCommandInput`, `TMigrableEnvelope`, `ContextWithActive`, `CreatedInstance`, `ErrorPaths`, `XYZ`, `MatGridList`, `TemplateCategory`, `InterfaceVpcEndpoint`, `Config3D`, `DebounceOptions`, `HighlightSet`, `AnyRenderFunction`, `CompositeAnimation`, `BitstreamFormat`, `NamedImport`, `ProviderOverride`, `MonitoringOutput`, `KeywordCxt`, `msRest.OperationParameter`, `TSVBTables`, `WorkspaceFoldersChangeEvent`, `IReporter`, `KeyframeTrack`, `ObservableArrayAdministration`, `IGitExtension`, `PoolingService`, `BasicCredentialHandler`, `TNSDOMMatrixBase`, `ParseSuccess`, `AggregationData`, `WebSiteManagementModels.StringDictionary`, `PossibilityChild`, `SnackBarService`, `FlushEventArgs`, `DataTableDirective`, `RoseChartSlice`, `BINModelInstance`, `DefaultProps`, `ValueState`, `Box`, `ValidationFuncArg`, `ast.Grammar`, `IToolbarProps`, `RtcpRrPacket`, `ProductUpdateReason`, `MappingPatternInfo`, `GroupKeysOrKeyFn`, `ArrayBindingElement`, `GenerateFileCommandParameters`, `PrivateInstance`, `t.Type`, `StartTransformsRequestSchema`, `CreateDistributionCommandInput`, `GeoCoordLike`, `GraphQLModules.ModuleContext`, `ISPUser`, `IceCandidate`, `AddToQueryLogDependencies`, `InputObjectType`, `ProgressBarState`, `EventHandlerInfosForElement`, `StorageObjectAck`, `MorphOptions`, `CppConfigItem`, `TxInput`, `NotionalAndUnrealizedPnlReturns`, `PortingLocation`, `Check`, `SetRepositoryPolicyCommandInput`, `AlertIconProps`, `ProgramIds`, `IColorMappingFunction`, `GetFieldFormat`, `lsp.TextDocumentPositionParams`, `SInt64`, `LitvisNarrative`, `DescribeJobsCommandInput`, `WorkspaceNode`, `YargsArgs`, `requests.ListLimitValuesRequest`, `TerminalService`, `requests.ListUserAnalyticsRequest`, `Group.Scalar`, `ParsedOptions`, `NavbarProps`, `RoleProps`, `OAuthException`, `AuthPartialState`, `Hooks`, `DeprecationsRegistry`, `MockCacheService`, `IFieldCustomizerCellEventParameters`, `ILauncher`, `RelationAttrInfo`, `IEditor`, `HierarchyOfMaps`, `SpellInfoDetails`, `ProcessId`, `ServerSideTransactionResult`, `MotionResult`, `ResolvedConceptAtomType`, `Club`, `HttpContentType`, `QuestionSelectBase`, `UIRoastingMachineStorage`, `BSPTraversalAction`, `cc.BoxCollider`, `FixCreator`, `DeleteClusterRequest`, `FacebookAuthProvider`, `StructureListMember`, `webpack.RuleSetRule`, `configuration.Publications`, `VerifyRes`, `S3Service`, `RequestParser`, `ArgsOf`, `types.Transport`, `Toxic`, `MonitoringAdapter`, `MockOracleInstance`, `IActionMethodAttribute`, `SlotData`, `UserData`, `SearchPredicate`, `FilterFunctionReturnType`, `AccountsService`, `DeleteRepositoryPayload`, `TSESTree.Expression`, `ITaskItem`, `QueryToken`, `DashboardState`, `ElasticsearchServiceStart`, `BridgeableGuildChannel`, `Const`, `btQuaternion`, `CustomFunctions`, `JWK`, `evt_disasm_sub`, `TabifyBuckets`, `Pokedex`, `EscrowedPayment`, `Hsla`, `Promise`, `IMetadataStorage`, `ModalsStateEntry`, `HttpRequestConfig`, `UserFacingSerializedSingleAssetDataTypes`, `ExpenseCategoriesService`, `CanvasMethod`, `GX.AttenuationFunction`, `PDFHexString`, `DataPersistence`, `TagMap`, `LayertreeItemNode`, `LoggerClient`, `SignatureOptions`, `StaticQueryDocument`, `SendMessageCommandInput`, `InputOperation`, `ParticleEmitter2Object`, `SavedObjectsUpdateOptions`, `TransferBtcBasedBlockchain`, `CaptureStdout`, `RemoteProvider`, `LabelPosition`, `DeleteThemeCommandInput`, `PersonType`, `NotificationConfig`, `BasicDataProvider`, `RequestStatus`, `MessageBoxOptions`, `LightSetting`, `TranscriptConsequenceSummary`, `RgbColor`, `GLRenderHash`, `AnyObject`, `MapEntity`, `url.URL`, `IPolygonData`, `QueuedResponse`, `OfficeMockObject`, `DayKey`, `ListControllerProps`, `LoadCollections`, `CallArgs`, `DeleteApplicationInputProcessingConfigurationCommandInput`, `IRenderInfo`, `EnvironmentConfig`, `HIDDevice`, `TransmartCountItem`, `ExpShapeSymbol`, `HsSaveMapManagerService`, `Runtime`, `RowData`, `ObservableState`, `TemplateSpan`, `TargetColumnGeometry`, `BarcodeMetadata`, `DescribePendingMaintenanceActionsMessage`, `DistributionProps`, `KeyObject`, `IOpdsLinkView`, `FormattedStatus`, `def.Matrix44`, `IFileWithMeta`, `IGaeaSetting`, `SVGNode`, `DateInputProps`, `DejaPopupReponse`, `TaskStore`, `OpenLinkComponent`, `ComponentName`, `NodeSpec`, `IMrepoDigestConfigFilePath`, `SLabel`, `Themes`, `SingleAssetTwoPartyIntermediaryAgreement`, `Child`, `GeoAngle`, `WorkSheet`, `IApplicationHealthStateChunk`, `LongitudeLatitudeNumber`, `postcss.AtRule`, `RetentionPeriod`, `RuleActionChange`, `OPCUAServerEndPoint`, `AtomList`, `SelectOptionProps`, `BoardType`, `ChannelCredentials`, `DirectoryWatcherCallback`, `ComponentFunction`, `StationComplementPlugin`, `BaThemeConfigProvider`, `StackGroupConfigNode`, `TorrentInfo.Info`, `ProfileNode`, `BrowsePath`, `INodeProperties`, `MockDomController`, `Campaign`, `ENDAttribute`, `PositionStyleProps`, `LogAnalyticsLabelAlias`, `inquirerTypes.PromptModule`, `cc.Vec2`, `ast.ParserRule`, `RTCSctpCapabilities`, `androidx.fragment.app.FragmentManager`, `LeaveAction`, `KeyCombine`, `WorkRequestCollection`, `DinoErrorController`, `ISearchResultState`, `IfScope`, `CacheType`, `ActionCreator`, `IPane`, `ClassStaticBlockDeclaration`, `SocketProxy`, `ResponseMetadata`, `ParseIterator`, `StartCliConfig`, `DmmfDocument`, `ActionStatus`, `ERC1155OperatorMock`, `IBucketHistogramAggConfig`, `NumberArray`, `ChainID.Mainnet`, `ArgGetter`, `KeyPairEthereumPaymentsConfig`, `SubModel`, `ts.PropertySignature`, `ListLeaderboardRecordsAroundOwnerRequest`, `NotebookInfo`, `FakeProgbar`, `TRPCClientError`, `IAssetActionTypes`, `RequestEnvelope`, `TelemetryWorker`, `DeployStacksIO`, `TamaguiInternalConfig`, `RequestAPI`, `CommentUI`, `DestinationCertificate`, `GbTreeNode`, `symbol`, `LowpassCombFilter`, `EntityElements`, `PreparedQuery`, `RStream`, `AutoImporter`, `Pack`, `MetaReducer`, `CeramicClient`, `MetaIndexState`, `MetroConfig`, `IFlavorInfo`, `IPC.IShellProcess`, `IDeliState`, `IListMultipleData`, `PullRequestOpened`, `HandlerInput`, `DataManager`, `RangeFilter`, `IContextErrorData`, `Joplin`, `IProjectType`, `StackStyleProps`, `ControlledStateProperies`, `EasyPZ`, `SymbolParam`, `SessionRefreshRequest`, `Env`, `ChannelListItem`, `ICustomValidatorResponse`, `KeyboardProps`, `Solo`, `RelativeLink`, `TransactionOptions`, `ConnectionArguments`, `HoverInsertActions`, `Types.ReadyType`, `_DeepReadonlyObject`, `StorageProvider`, `QueryOrdersRequest`, `VideoStreamIndex`, `ICharaProfile`, `reduxForm.ConverterForm`, `IBaseTaskParams`, `EqualityMap`, `CodeBlockWriter`, `HitSensorInfo`, `JRPCEngineEndCallback`, `AndroidOutput`, `RenderPassContext`, `WebGLContextAttributes`, `TableForeignKey`, `PutLoggingOptionsCommandInput`, `actions.Args`, `PublicModelRouter`, `CodelistService`, `WhereFilterOp`, `IConvectorControllerClient`, `Refiner`, `ReadAllCallback`, `ShadowsocksManagerService`, `SchemaComparator`, `Monitor`, `ProjectConfigData`, `UpdateAssetCommandInput`, `IUpsertScalingPolicyCommand`, `ResourceTypeSummary`, `InfluxVersion`, `HtmlTemplate`, `GraphQLRequestContextDidResolveOperation`, `Perspective`, `CompareLookup`, `Contact`, `SetIamPolicyRequest`, `CollectionManifest`, `MetadataReader`, `MetaesContext`, `CryptographyService`, `ProviderDef`, `BoxStyleProps`, `UberChoice`, `STColumn`, `TipsLabels`, `SymbolWithParent`, `FilePropertyProps`, `AnyRawBuilder`, `K6`, `MockRequestInit`, `DiscordMessageReactionAdd`, `MessageInfo`, `LogicOperator`, `TStyle`, `IBookmarkState`, `Animate`, `ChangeEventHandler`, `NormalizedOptions`, `DeleteServiceRequest`, `PluralSub`, `ContractCallPayload`, `SerializedError`, `vscode.TextEditorSelectionChangeEvent`, `LicenseStatus`, `SourceDescription`, `ClsService`, `xDatum`, `RequestLimitConfig`, `RegExpExecArray`, `MarkedString`, `ClampedValue`, `ProcessExecution`, `FetchedBalances`, `ModelerFourOptions`, `MidiInstrument`, `Callable`, `CloudFormation`, `IViewHandler`, `BlockPos`, `Just`, `TVariables`, `PrimitiveValue`, `NamedExoticComponent`, `TClientData`, `IFriend`, `V.Scheme`, `MyButton`, `AsyncIterableQuery`, `StackUndeployOperation`, `TreeConfiguration`, `com.google.ar.sceneform.Node`, `DiagnosticsCallFeatureState`, `ComponentSID`, `TSContinue`, `LocalStorageIndex`, `Webview`, `ReactFramework`, `ThySlideConfig`, `MangoCache`, `jsdoc.Annotation`, `PSPoint`, `TabFragmentImplementation`, `InputWithModel`, `BufferViewResult`, `SavedObjectsClient`, `TxStatus`, `TimelineChartRange`, `ExperimentalStickering`, `MarkMap`, `ResourceArray`, `InputOption`, `IPnpmShrinkwrapDependencyYaml`, `TextClassification`, `PvsFormula`, `IBlob`, `MerkleInclusionQuantifier`, `Tx`, `PartialState`, `ListPositionCacheEntry`, `TestToken`, `MetricsStore`, `ExpandPanelActionContext`, `PageListProps`, `EmailActionConnector`, `AllureTest`, `SharingUpdate`, `EnumerationDefinitionSchema`, `IBufferLine`, `cp.SpawnOptions`, `OpenSearchRawResponseExpressionTypeDefinition`, `ComponentComment`, `EvaluationConfig`, `ScopeFilter`, `IAppConfig`, `QualifiedRules`, `IMutationTree`, `BaseManifestGenerator`, `NowResponse`, `GetRecordsCommandInput`, `LogParams`, `QuoteOptions`, `FinancialViewEntry`, `DecryptionMaterial`, `AnyKey`, `EdgeAttributes`, `OptionObject`, `IRECProduct`, `VisualizationDimensionGroupConfig`, `IInternalActionContext`, `SlpTransactionDetails`, `RouteMatcher`, `MiddlewareFactory`, `RectShape`, `IDropDownTreeViewNode`, `StyleTokens`, `NewTootState`, `SendChannelMessageCommandInput`, `LuaThread`, `ECS`, `Entry`, `Anchored`, `OnPreResponseToolkit`, `CategorizedSettings`, `IParseHandler`, `ArcoOptions`, `ConfigYaml`, `KGS.DataDigest`, `ChainId`, `CookiesOptions`, `DialogProperty`, `TranslationConfig`, `DestinationConfig`, `EdgeData`, `BaseTx`, `NgxsWebsocketPluginOptions`, `TRgb`, `SearchFormLayoutProps`, `PoolState`, `OrganizationProjectService`, `VscodeWrapper`, `MatchNode`, `AlertContextOptions`, `Rec`, `XRFrame`, `RegistrationData`, `dScnKy_env_light_c`, `ValueFilterPlugin`, `GfxRenderInstManager`, `SearchSource`, `CallHierarchyService`, `NoteNumberOrName`, `PagedResp`, `DaySpan`, `ExtendedPOIDetails`, `CreateTableCommandInput`, `Menu`, `RawSavedDashboardPanel630`, `InitializeHandlerArguments`, `OpenCVOperatipnParams`, `MatAutocompleteSelectedEvent`, `ReferencesResult`, `PrivKey`, `ColExpression`, `Planet`, `AttributeKey`, `FsReadOptions`, `ChainMergeContext`, `ConfirmOptions`, `WsKey`, `HsCommonEndpointsService`, `FetchResult`, `IPatchList`, `StartApplicationCommandInput`, `t.ValidationError`, `PyChessModel`, `YarnLock`, `TeamService`, `MockTextNode`, `XMessageOption`, `AxisProps`, `Results`, `ExclusionVisibleVirtualNode`, `FixedDomPosition`, `SignedBlockType`, `SyntheticKeyboardEvent`, `FontCatalog`, `NextCharacter`, `MiBrushRepaintConfig`, `DejaSnackbarComponent`, `ExportOptions`, `AnimatedComponent`, `HandleReference`, `Awaiter`, `ConnectionHealthData`, `RequestEntity`, `TableColumnDirective`, `GltfAsset`, `GetReferenceOptions`, `VcsService`, `EPObject`, `IExternalHooksFunctions`, `ParticipantTracks`, `GraphQLSchemaPlugin`, `IRenderMime.IMimeModel`, `KeyframeNode`, `FormEvent`, `UpSetThemes`, `TwoSlashReturn`, `AppRecord`, `PageResource`, `FilePaths`, `IContextualMenuItem`, `ListenerType`, `ButteryNode`, `LoadingService`, `SimpleScalarXmlPropertiesCommandInput`, `d.OutputTargetDistCustomElements`, `KueryNode`, `DescribeDBSnapshotsCommandInput`, `RoutedPoint`, `MockRule`, `FeedId`, `PointLike`, `VqlClient`, `NetworkResolver`, `LoadableClassComponent`, `MenuData`, `ImageFilter`, `INvModule`, `SearchableItemPresenter`, `PublisherProperties`, `StyleSheetType`, `PreferenceProviderDataChange`, `Moize`, `PrepareReactRender`, `DownloadOptions`, `crypto.BinaryLike`, `IAddressBookState`, `EPPrimitiveDependencies`, `ActionsSdkApp`, `Yield`, `Primitives.Numeric`, `WhenToMatchOptions`, `IReduxState`, `AtomRef`, `ServiceCatalogSummary`, `TodoItem`, `VcalDateOrDateTimeProperty`, `SaveDialogOptions`, `IHawkularAlertsManager`, `CommanderStatic`, `ValidationResults`, `NzModalRef`, `LegacyVars`, `SubTypeBuilder`, `GetConnectivityInfoCommandInput`, `TransferData`, `BeInspireTreeNodes`, `TreeMap`, `GainEntry`, `vault`, `JupiterOneClient`, `CoapResponse`, `cc.SpriteFrame`, `LocalizeRouterService`, `PercentileRanksMetricAggDependencies`, `FnN2`, `ArgTypes`, `AttachmentInfo`, `CupertinoDynamicColor`, `MockDataset`, `msRest.ServiceCallback`, `EntityNameExpression`, `LogoutOptions`, `XSession`, `Aperture`, `ThisTypeNode`, `HotswappableChangeCandidate`, `SourceInfo`, `TContext`, `ColorSwatchProps`, `RulesTestContext`, `LoggerNamespace`, `RippleBalanceMonitor`, `TransactionObject`, `IFilterModel`, `MovieDetails`, `ProgressListener`, `IE`, `Protocol.Network.ResponseReceivedEvent`, `ThyClickDispatcher`, `IMGUI`, `MyTypeDeclarative`, `TObj`, `PeopleIterator`, `MessageAttributeMap`, `KeyChange`, `PipeState`, `FloatAnimationTrack`, `ListApmDomainWorkRequestsRequest`, `AggregationResponse`, `CurrencyType`, `DialogContentProps`, `LogoProps`, `IChunk`, `ComponentRequestTable`, `BigQueryRetrievalRow`, `PermissionState`, `TabView`, `Tag`, `Vector3D`, `DeleteEventSubscriptionMessage`, `DateConstructor`, `NetworkContracts`, `NettuAppResponse`, `TypeLiteral`, `CoordinateXYZ`, `FactoryFunction`, `SkyhookDndService`, `IRawHealthEvaluation`, `LoadingManager`, `TableCellSlot`, `TabBarToolbarRegistry`, `ResponseFormat`, `ListFleetsCommandInput`, `ReduxLikeStateContainer`, `SendMessageOptions`, `SceneItem`, `ExtendedHttpsTestServer`, `SpacesService`, `IInspectorState`, `D3LinkNode`, `EndpointDescription`, `TypedThunk`, `VTF`, `RemoveTagsCommandInput`, `ChartPointSourceItem`, `Counter__factory`, `AccessKeyStorageJson`, `Diagram`, `ProductJson`, `PathNode`, `VpcSubnetArgs`, `TimelineEvent`, `GitHubEventModel`, `DebugOption`, `ImmutableCollection`, `AccountingRecord`, `IChainForkConfig`, `OpenPGPKey`, `AuthorizationRules`, `DeleteAccessPointCommandInput`, `core.CallbackOptionallyAsync`, `TerritoryAliasMap`, `CreateDedicatedIpPoolCommandInput`, `RecipientType`, `CalendarObject`, `InterfaceWithCallSignatureReturn`, `IObjectWillChange`, `JDevice`, `Paint`, `TextChannel`, `PostProcessingRule`, `DestroyArgv`, `WatchEvent`, `EventStreamSeed`, `IBaseImageryLayer`, `DAL.DEVICE_ID_COMPONENT`, `later`, `StopDeploymentCommandInput`, `P2PRequestPacketBufferData`, `EventListener`, `Text.JSON`, `GlobalParameter`, `Schema$RowData`, `interfaces.Target`, `React.FC`, `AnimationInternal`, `IfStmt`, `DefinitionElementProps`, `postcss.Node`, `MockComment`, `Insights`, `VisitResult`, `BlockbookConnectedConfig`, `Detector`, `ValidationRunData`, `AmmLiquidityPool`, `ITasksGetByContactState`, `VRMDebugOptions`, `UpdateThemeDto`, `CartItemsResponse`, `FileBox`, `MeetingCompositeStrings`, `tinycolor.Instance`, `BaseScreen`, `MarketResponse`, `TransactionGasPriceComputator`, `FactorySession`, `ScopeDef`, `LifecycleEvent`, `Tile`, `BundleEntry`, `Transducer`, `ScriptCompiler`, `UpdatePortalCommandInput`, `MouseMoveEvent`, `d.CompilerRequest`, `IProductOptionTranslatable`, `TradeType`, `ScriptInfo`, `Conversion`, `ControlPanelsContainerProps`, `NameIdentifierNode`, `VisitorInvocation`, `JournalMetadata`, `CompareFunction`, `ExprVisitor`, `LoginService`, `ModProperty`, `DragRef`, `Testrec`, `TClient`, `InstanceGeometryData`, `DescribeLimitsCommandInput`, `UiActionsPlugin`, `DatasourceOverwrite`, `CalculatorTestContext`, `EntryContext`, `SupportedEncoding`, `FileGroup`, `AggregateQuery`, `NetplayPlayer`, `PortalInfo`, `HeroesState`, `NormalizeStateContext`, `MockEnv`, `ModelQueryBuilderContract`, `AttrNode`, `providers.Provider`, `BrowserObject`, `GlobalVariantGroupConfig`, `SeverityLevel`, `GetPartitionIndexesCommandInput`, `DataSourceInstanceSettings`, `QuizReaction`, `ts.ElementAccessExpression`, `sdk.SpeechSynthesisResult`, `MiddlewareNext`, `Resp`, `DecoratorDef`, `ComponentStyle`, `Mesh3D`, `GcpCloudProvider`, `IRes`, `Nightmare`, `SHA512_256`, `GetSelector`, `RenderWizardArguments`, `InterfaceMapValue`, `ResizeObserver`, `TypeBinding`, `JoinedReturnType`, `FetchRequestId`, `JacobianPoint`, `ICoordinate`, `PaymentV1`, `ResourceMap`, `CodeBuilderConcrete`, `ResolvedDeclarationList`, `WalkMemberContext`, `requests.ListVolumeGroupBackupsRequest`, `SpecPickerInput`, `AccountRefresh`, `CheatModeMachineContext`, `CompletionSymbol`, `DateLocale`, `KontentItemInput`, `CommentDoc`, `SwaggerLambdas`, `MaterialParams`, `CompareFunc`, `ArgumentBuilder`, `Library`, `NoteEditorState`, `ViewableGrid`, `google.maps.Marker`, `TradeProvider`, `LineChart`, `NzUploadChangeParam`, `MockLogger`, `ModuleKey`, `DashboardData`, `pageNo`, `IconMenuItem`, `AzureDataTablesTestEntity`, `SObjectRefreshOutput`, `ChangeState`, `ITechnology`, `SessionStateControllerAction`, `InitializeParams`, `OrderedIndex`, `ShortConnectionDTO`, `Type_List`, `INotebookTracker`, `ColProps`, `StatefulSearchBarProps`, `ts.ExportSpecifier`, `StatusActionQueue`, `TRPCResponse`, `IUpdateStacksCommandArgs`, `RstStreamFrame`, `AvailableFeature`, `IFormControlContext`, `Dict`, `FormLayoutProps`, `ClientProxy`, `AdbSocket`, `INetworkPlayer`, `Valid`, `VolumeAttachment`, `AlertingRouter`, `OnPreAuthToolkit`, `ClJobs`, `SegmentDetail`, `IRecordReference`, `ICommandArguments`, `LitecoinAddressFormat.Modern`, `IAppInfo`, `CreateDBClusterCommandInput`, `ServerDataItem`, `IQueryConfig`, `MigrationResult`, `CellService`, `PluginCtx`, `SafeExpr`, `App.services.IRequestService`, `ProxyConfiguration`, `SingleSigHashMode`, `ButtonListenerCallback`, `FoundNodeFunction`, `MsgDeleteProvider`, `IOpts`, `SummaryNode`, `StashTabSnapshot`, `BlockProps`, `StarknetERC721ContextInterface`, `CustomRouteShorthandOptions`, `RestoreRequest`, `SGMark`, `InstructionParams`, `BUTTON_SHAPE`, `EndpointType`, `SearchResultsPage`, `LaunchOptions`, `TradingPosition`, `Epoch`, `DateRangeItemInfo`, `BaseResourceOptions`, `StringFilter`, `RuntimeField`, `NavbarService`, `IThrottleService`, `PopupModelConfig`, `PropertyValue`, `ITable`, `EPersonDataService`, `ObservableLanguagePair`, `DefaultRequestOptions`, `FullIconifyIcon`, `Immediate`, `SpeakerActions`, `LogFilter`, `BitfinexWebsocket`, `TD.DataSchema`, `ThemedComponentThis`, `Optimizer`, `Fee`, `ListDeliverabilityTestReportsCommandInput`, `StateUpdate`, `SourceControl`, `ShortcutObject`, `ISerDeDataSet`, `BookmarkTreeNode`, `ProviderService`, `GraphQLError`, `d.RobotsTxtOpts`, `SpeechSynthesisUtterance`, `EntityDocumentResult`, `IgnoredCommentContext`, `CanaryScope`, `analyze.Options`, `ProductVariantService`, `InventoryStat`, `SimpleButton`, `CmsEditorFieldRendererPlugin`, `AnimationDirection`, `CollectionObj`, `TestServer`, `EditingData`, `FeaturesList`, `requests.ListVmClustersRequest`, `TCompactProtocol`, `IRoomObject`, `ContractConfig`, `Text_2`, `ParamInstance`, `QueryFieldMap`, `RehypeNode`, `ForbiddenWordsInfo`, `IDataModel`, `NgStyleInterface`, `RouterNavigatedAction`, `AlgoliaClient`, `RouterMock`, `QuantityLabel`, `jsiiReflect.Type`, `MeterCCGet`, `SDKModels`, `GLenum`, `LegendItemList`, `PromiseBase`, `AadHttpClient`, `Tournament`, `VerdaccioError`, `Media`, `FindAndModifyWriteOpResultObject`, `ActionSequence`, `AggHistoryEntry`, `ResolveSavedObjectsImportErrorsOptions`, `ContextModel`, `templateDataType`, `ExclusiveTestFunction`, `AppSocket`, `TypeCase`, `FunctionProperties`, `ParsedNode`, `Buntstift`, `ColumnData`, `PerpMarketConfig`, `CustomElement`, `MultiChannelCCCommandEncapsulation`, `AppProps`, `Vector2_`, `ResponseFixtures`, `requests.ListGroupsRequest`, `React.SyntheticEvent`, `NoticeProps`, `AssetServiceClient`, `GraphQLModelsRelationsEnums`, `TextStringNoLinebreakContext`, `SubscriptionEmit`, `ParserServices`, `RunOptions`, `PO`, `ExecuteTransactionCommandInput`, `DataPoint`, `StreamActivityModel`, `DaffAuthorizeNetReducerState`, `NavigationPluginStartDependencies`, `DefaultConfig`, `OracleConfig`, `UpdateUserAvatarService`, `builder.IDialogResult`, `AlertTitleProps`, `GraphVertex`, `F`, `TextureFormat`, `WorkflowExecuteMode`, `IXingInfoTag`, `ProjectLock`, `GleeConnection`, `IControllerConfig`, `IBucketDateHistogramAggConfig`, `requests.ListUpcomingScheduledJobsRequest`, `CreateChannelCommandInput`, `BlockDocument`, `DeleteProjectCommandInput`, `AbstractShaderNode`, `CkbMint`, `ListSafetyRulesCommandInput`, `ClientQuery`, `SidebarItem`, `StateNodeConfig`, `PatternMatchKind`, `TreeMeta`, `ConstantSourceNode`, `InMsg`, `ReadableQuery`, `SearchResultComponent`, `CategoricalChartProps`, `CoerceResult`, `RefactoringWithActionProvider`, `MDCDialogPresentationControllerDelegateImpl`, `IStartupInfo`, `IQuaternion`, `BaseRowDef`, `CaseReducer`, `Test`, `PreparedData`, `IAnyVisualization`, `IReminder`, `IosBuildName`, `TransactionAction`, `ITaskDataConnections`, `KeyRange`, `MemBuffer`, `OrderedComparator`, `ThreeEvent`, `DevicePixelRatioMonitor`, `ThyGuiderStep`, `ViewSlot`, `UploaderInputs`, `InputFieldsComponentsDef`, `ParticipantPermission`, `BitstreamFormatRegistryState`, `CstmHasuraCrudPluginConfig`, `Koa.Next`, `CodePrinter`, `ReferenceResolverState`, `UserQueryTask`, `FilterState`, `PanelData`, `WebGLSync`, `ReporterFactory`, `CanvasPath`, `ApiPackage`, `ISuggestionsCollector`, `BaseTransaction`, `ThrowIterable`, `MockDrake`, `MarkerInstanceType`, `LensState`, `VertexElement`, `ModelList`, `DAL.KEY_ESC`, `HsSidebarService`, `Ti18nDocument`, `BatchExecuteStatementCommandInput`, `CacheContent`, `RuleWithId`, `GfxBuffer`, `DiffOptionsNormalized`, `OsqueryAppContext`, `SelectChangeEvent`, `MarkerSet`, `MenuEvent`, `N3`, `TProtocol`, `EmailValidatorAdapter`, `PagerBase`, `IStyleObj`, `RouteData`, `SubstanceEnv`, `CreateProjectDto`, `DbUser`, `MenuStackItem`, `JSXExpressionContainer`, `IndexedCallback`, `OpGraphPath`, `Vec3Sym`, `DeepImmutable`, `ContinueStatement`, `IPointAttribute`, `SimpleSelector`, `UIRouter`, `ClassicComponentClass`, `Dual`, `AppServicePlan`, `ObjectView`, `DeleteValue`, `TreeNodeHTMLElement`, `IconComponentProps`, `UserProfileService`, `ImportFromAsNode`, `UpdateDocumentCommandInput`, `IterableIterator`, `WidgetView`, `FormErrorMessageType`, `requests.ListDatabaseUpgradeHistoryEntriesRequest`, `TestObservableLike`, `PopupStackItem`, `DocumentDeltaAtomicUpdate`, `DeleteDashboardCommandInput`, `DescriptorProto`, `DirectionLight`, `RequestCompleteEvent`, `EntityActionDataServiceError`, `CodegenDesignLanguage`, `Aggregator`, `DeprecationsClient`, `TimestampTrigger`, `SavedObjectsCreateOptions`, `HexcolorInfo`, `NotificationCreateProps`, `PDFForm`, `ClientOrderGoodsInfo`, `ValidationMetadata`, `TopLevel`, `AtomGridmaskImageElement`, `MemberLikeExpression`, `IntFormat`, `DirectoryObjectListResult`, `HTMLDice`, `OrgPass`, `SheetChild`, `BookService`, `IConversionValidation`, `SavedObjectSanitizedDoc`, `TLPointerEventHandler`, `FormStore`, `NextFnType`, `IWorkerArgs`, `XSort`, `TFnWatcher`, `Plugin.SNSAdaptor.Definition`, `EvAgentSession`, `NonEmptyArray`, `SQLVariables`, `ConfiguredPluginResource`, `EditableDocumentData`, `EntityItem`, `ResultType`, `QueryMany`, `IAmazonServerGroupDetailsSectionProps`, `RemovableAnalyserNode`, `EventExclusionPlugin`, `FluentBundle`, `RequestSpan`, `ExecutorState`, `StudioComponentInitializationScript`, `cBgS_GndChk`, `MappedSingleSourceQueryOperation`, `ListKeyManagerModifierKey`, `TemplatesManager`, `GraphQLList`, `Wrapper`, `QueryFilter`, `TagLimitExceededException`, `ClusterNode`, `RadioButtonProps`, `Operand`, `SpatialOctreeNode`, `StorageArea`, `PDFAcroComboBox`, `EntityChangeEvent`, `UberChart`, `SearchOpts`, `BubbleSeriesStyle`, `Operator.fλ`, `DescribeTasksCommandInput`, `Gzip`, `LegendType`, `WebGL1DisjointQueryTimerExtension`, `DialogPosition`, `RpcMessageSubject`, `t.Identifier`, `Ternary`, `StackProps`, `CoreHelpers`, `fhir.Task`, `unist.Node`, `CGSize`, `OfficeApp`, `DatePickerProps`, `BigintIsh`, `EdiElement`, `StepComponent`, `AccountLeague`, `RollupWatcher`, `PBRCustomMaterial`, `jdspec.PacketInfo`, `IMediaQueryCondition`, `ISPField`, `ServiceMetadata`, `BEMHelper`, `DescribeConnectorsCommandInput`, `ColumnPoint`, `AbstractRunner`, `CallHierarchyDataItem`, `IFabricWalletGenerator`, `ast.LetNode`, `SanityClient`, `ReorderAggs`, `RenderData`, `InterviewQuestionSortMap`, `Cubelet`, `TransportRequestOptions`, `SMTConstructorGenCode`, `Kubectl`, `IGetActivitiesStatistics`, `EditPropertyConfig`, `EmbedType`, `IRestApiContext`, `ObserverCallback`, `PerfToolsMutation`, `IModelConfiguration`, `TransferBrowserFftSpeechCommandRecognizer`, `IFocusedCellCoordinates`, `StyledProperties`, `TransformerOptions`, `ItemMap`, `KeyLabel`, `QuickPickItem`, `ColorConfig`, `CronosClient`, `GroupedOrderPremiumRow`, `ISparqlBinding`, `PullRequestViewModel`, `ImmutableCell`, `RoosterCommandBarProps`, `AddTagsOutput`, `Widget`, `CommandModule`, `StatefulCallClient`, `ListAnalyzedResourcesCommandInput`, `BarFile`, `estree.Program`, `TProps`, `UsersResponse`, `QueryOptionNames`, `IExportProvider`, `PointContainer`, `Int32Array`, `ViewRanges`, `ArrayBindingOrAssignmentPattern`, `AnimatedNode`, `AndDeciderInput`, `ColumnsSchema`, `LinkedListChild`, `BlockStackService`, `ConnectionGraphicsItem`, `ScrollSpyService`, `IReactExtension`, `BSplineSurface3d`, `UserGroup`, `SessionSourceControl`, `INestApplication`, `IEntityState`, `ComponentLayoutStyleEnum`, `LayerGroup`, `CompositeFilterDescriptorCollection`, `IExecutionContextContainer`, `SelectSeriesInfo`, `Safe`, `AutoTuneMaintenanceSchedule`, `ODataStructuredTypeParser`, `CancellationReceiverStrategy`, `SSBSource`, `AABB`, `GenericMetricsChart`, `NSMutableDictionary`, `SavedObjectsStartDeps`, `DeployedReplicaCollection`, `ModuleListener`, `PlaneTransformation`, `HRTime`, `ProjectItem`, `TreeBacked`, `BCSV.Bcsv`, `vscode.FileStat`, `HtmlRendererOptions`, `CoverConfiguration`, `next.Group`, `TRecord`, `NodeTypes`, `React.RefCallback`, `GetJobRequest`, `SliderHandle`, `tStringDecimalUnits`, `DeploymentImpl`, `RootVertex`, `ObservableChainQuery`, `Edition`, `ThemeColorDefinition`, `CallFrame`, `UniformPub`, `ContentFilter`, `AnimationAction`, `CacheUpdateEvent`, `DeSerializersT`, `near.NearSwapTransaction`, `CameraMatrix`, `SlashCommandConfig`, `KeyToIndexMap`, `TestEthersProvider`, `VpcConfig`, `IListSelectionConfig`, `GoogleStrategy.Profile`, `jest.SpyInstance`, `NetworkgraphSeries`, `UserFromToken`, `AlertDetails`, `ListDomain`, `Pickle`, `ExtendedCodeAction`, `DebugProtocol.StackTraceArguments`, `CollapsedTransform`, `InitialProperties`, `BodyPartConstant`, `CustomSeriesRenderItemParams`, `NineZoneManager`, `UniswapV2Pair`, `InvalidTagException`, `ts.ObjectType`, `DynamicsContext`, `core.ETHSignTx`, `TransactionApplyContext`, `WithLiteralTypescriptType`, `UserStoreReference`, `ClassVisitor`, `WebSocketTransport`, `IAst`, `ComponentGeneratorOptions`, `SavedObjectFinderUiProps`, `SalesforceFormValues`, `FolderResponse`, `LocaleService`, `CalendarConstants`, `RuleValidator`, `GX.SpotFunction`, `OperationData`, `DebugProtocol.InitializeRequestArguments`, `TileView`, `PredictionContextCache`, `GraphQLEnumType`, `IThrottlingMetrics`, `Technique`, `VirtualNetworkTap`, `DropdownButtonProps`, `MulticallResponse`, `DataSourceSnapshot`, `IQueryListProps`, `KeyUsage`, `SessionStateControllerState`, `RefreshTokenRepository`, `IColumnWrapper`, `AB`, `Graphin`, `TransactionSigner`, `SShapeElement`, `ParameterList`, `CreateConnectionCommand`, `ProjectFile`, `RpcContext`, `AESCipher`, `HumidityControlSetpointCCReport`, `TypeEvaluator`, `ProxyHandler`, `ObjectOptions`, `DescribeUserProfileCommandInput`, `CreditCardView`, `StructureTerminal`, `TypeTemplate`, `EightBittr`, `LegendPositionConfig`, `MapConfig`, `IAppSetting`, `SelectItemDirective`, `ActionFunction`, `Light_t`, `ModalService`, `MotionComponent`, `GradientDataNumber`, `UserPosition`, `FormFields`, `SubSequence`, `DataSourceConfiguration`, `Dockerode.Container`, `InformationPartitionElementProps`, `InterleavedBuffer`, `Responder`, `EmployeeStore`, `Effect`, `EntryControlCCNotification`, `ItemView`, `HookDecorator`, `SubConfig`, `CategorizedPropertyMemberDoc`, `IEntityType`, `TransactionId`, `WebWorker`, `requests.ListVmClusterPatchHistoryEntriesRequest`, `CollectionResult`, `CF.Subscribe`, `ColumnMetaData`, `AnnotationCollection`, `HintContext`, `Metas`, `UpdateStateValueFunc`, `Corner`, `GoldTokenWrapper`, `object`, `ICanvas`, `QConn`, `RegisterOutput`, `VerificationCode`, `CodeFlowReferenceExpressionNode`, `NextStep`, `BackgroundProcessState`, `NumBopType`, `FbBuilderFieldPlugin`, `Events.prekill`, `DestinationsByType`, `ActionsSubject`, `FieldProps`, `Diagnostic`, `ProcessRequestResult`, `TestFunctionImportEdmReturnTypeParameters`, `Patient`, `ICellRendererParams`, `Reflecting`, `DeleteDomainRequest`, `Champions`, `SyntheticErrorLabel`, `ZoneFileObject`, `d.OutputTargetDocsVscode`, `ListOdaInstancesRequest`, `UpdateEntryType`, `ListLeaderboardRecordsRequest`, `StoredFile`, `iDataTypes`, `INixieControlPanel`, `SVGTransform`, `RequestInit`, `CollectionTemplateable`, `Array3`, `SelectionSetNode`, `ExtConfig`, `TButtons`, `InfoPlist`, `PersistentVolumeClaim`, `Uuid`, `BubbleLegendItem.RangesOptions`, `ListNodesCommandInput`, `VisualizeEmbeddableContract`, `C51BaseCompileData`, `SourceMapSpan`, `GenericBinaryHeapPriorityQueue`, `UtilityInfo`, `XRFrameOfReference`, `EventSubscriptionsMessage`, `GasOption`, `GPUTextureFormat`, `InsertResult`, `FigurePart`, `SubsetStory`, `TransferTransaction`, `FileLoader`, `AWSSNSEvent`, `ModalInstance`, `SbbNotificationToastConfig`, `MaxPooling3D`, `ObservedNode`, `SocketAwareEvent`, `InjectorIndexes`, `DeleteDeviceCommandInput`, `CategoryResults`, `Portfolio`, `OpRecInterface`, `TransactionOutput`, `QueueOptions`, `RenderOptionFunction`, `ProcessingJobsMap`, `RouteMatch`, `K1`, `StorageValue`, `ListAttachmentsCommandInput`, `PaymentMethod`, `EmojiData`, `SubstituteOf`, `Indexes`, `PluginDeployerEntry`, `ts.Visitor`, `ProxyType`, `Keyframes`, `PackageContribution`, `ObservableMedia`, `NamedAttrMap`, `AngularFireDatabase`, `ShoppingCartState`, `ListDashboardsCommandInput`, `VaultItemID`, `IMinemeldCandidateConfigNode`, `EnvironmentProps`, `DisplayStyleProps`, `JGOFIntersection`, `DocUrl`, `TagValueType`, `NodeIdLike`, `AnimationEntry`, `BooleanLiteralExpr`, `SudokuBoard`, `FormFieldsProps`, `DecoratorType`, `Nodes`, `ts.MethodSignature`, `SPClientTemplates.RenderContext_Form`, `PUPPET.payloads.Room`, `DidDocument`, `StackEvent`, `Type_AnyPointer`, `RouterOptions`, `SubtitlesTrackId`, `LTypeResolver`, `AthenaClient`, `ParsedSite`, `NodeInstructure`, `NativeCallSyntax`, `CognitoUser`, `SchemaValidationContext`, `SsgRoute`, `FormApi`, `HintsConfigObject`, `angular.IIntervalService`, `SourceBuffer`, `RequestSet`, `R3`, `ShaderSlot`, `x.ec2.Vpc`, `RulesMap`, `StreamType`, `d.PrerenderUrlRequest`, `ICreateCommitParams`, `requests.ListExportSetsRequest`, `HttpResponseEncoding`, `languages.Language`, `Plural`, `Tense`, `BlockDefinitionCompiler`, `SimpleList`, `MockActivatedRoute`, `TimelineOptions`, `ConnectedSpace`, `Iam`, `EmbeddableInput`, `SeriesZonesOptions`, `DistanceExpression`, `ECB`, `vscode.Command`, `V1CommandInputParameterModel`, `ListSwipeAction`, `IContainerRuntimeOptions`, `PrebootDeps`, `IFilterOptions`, `XMLSerializer`, `TransactionGenerationAttempt`, `DeserializeWire`, `LicensingPluginSetup`, `LoadingProps`, `ControllerClient`, `QuickInputStep`, `RequestController`, `UpdatePublicData`, `Chord`, `SavedObjectMigrationContext`, `IGLTFRuntime`, `EngineArgs.CreateMigrationInput`, `BluetoothDevice`, `DeleteBotAliasCommandInput`, `CommandLineArguments`, `TextCanvasLayer`, `SummaryItem`, `ProgressBarData`, `ListTagsForResourceRequest`, `GetPolicyResponse`, `DefinitelyTypedTypeRun`, `GroupedFunnel`, `HistoryState`, `PaginationComponent`, `TextureUsage`, `models.NetFramework`, `DefaultEditorDataTabProps`, `VIS0`, `Freeze`, `ToastsApi`, `GlobalPositionStrategy`, `ContextMember`, `IPatch`, `ActionKey`, `OrderPremiumRow`, `RuntimeOptions`, `Torrent`, `PlaylistTrack`, `SObjectTransformer`, `BlogTag`, `AnyImportSyntax`, `StateService`, `SF`, `LinkedDashboardProps`, `KeyPair`, `NetworkManager`, `CustomPropertyHandler`, `$E.IBaseEdge`, `TydomController`, `ISyncedState`, `minimist.ParsedArgs`, `ListUsersCommandInput`, `KeyframeTrackType`, `bitcoinish.BitcoinishPaymentTx`, `AutoCompleteLabel`, `DashEncryption`, `Int32List`, `QueryDeploymentResponse`, `ListRepositoriesReadModel`, `Viewer`, `BluetoothRemoteGATTCharacteristic`, `UpdateOptions`, `KeySchema`, `IMappingsState`, `ControlElement`, `PackedBubbleLayout`, `AWSSNSRecordItem`, `IStats`, `ProjectMap`, `ClipboardEvent`, `ProfilerFrame`, `Yarguments`, `IntrospectionResult`, `FileId`, `DeleteWebACLCommandInput`, `SortClause`, `SubdomainAndZoneId`, `HttpParams`, `MetamaskState`, `MultigraphRequestOptions`, `RTCIceCandidateJSON`, `BoxPlotData`, `ExpressionTypeDefinition`, `IErrorCallback`, `ASNDBS`, `PredictableHook`, `anchor.BN`, `BubbleLegendItem.Options`, `PubEntry`, `imperative.IProfileLoaded`, `FilterOptionOption`, `MatSortable`, `V1Prometheus`, `LocalParticipant`, `ProcessedPackageConfig`, `p5exClass`, `GraphObject`, `IntraDayDataSourceType`, `d.EventSpy`, `ColorSpace`, `CallHierarchyOutgoingCallsParams`, `TestScheduler`, `MockStateContext`, `AnyConfigurationModel`, `CanvasEditorRenderer`, `SourceLocation`, `ArmParameters`, `IndexTree`, `IntlMessages`, `Responses.IListContentItemsResponse`, `GeoPointLike`, `BuiltinFrameworkMetadata`, `TestGraphic`, `Apply1`, `QExtension`, `ShellResult`, `OnReferenceInvalidatedEvent`, `ResourceRecord`, `PromiseResolver`, `Outlet`, `CreateStageCommandInput`, `HomebridgeConfig`, `AnimatableColor`, `SmsHandler`, `RespostaModel`, `PostType`, `IMergeNode`, `TodoType`, `RepositionScrollStrategyConfig`, `ArrayBinding`, `React.MutableRefObject`, `SyncEvent`, `IMYukkuriVoice`, `F.Function`, `TiledSquareObject`, `BaseUIManager`, `FilterGroupKey`, `ServerInfo`, `AnySchemeForm`, `SpacesClientService`, `MockedDataStore`, `IModelHubClientError`, `QueriesStore`, `StartStopContinue`, `ProfileRecord`, `u`, `TokenClaims`, `ExternalProject`, `RectResponderModel`, `IWholeSummaryPayload`, `MongoConnection`, `TemplateInput`, `WriteTournamentRecordRequest`, `SignatureHelp`, `IdentifierInfo`, `TopicId`, `RPC.IWatchResponse`, `KubernetesService`, `GlyphVertices`, `BundleItem`, `SuiteInfo`, `ContentCache`, `Encoder`, `AnimGroupData_Shape`, `AxisTitleOptions`, `FormFieldMetadataValueObject`, `LogsData`, `Employee`, `DataGatewayService`, `$NextFunctionVer`, `TimelineViewWrapper`, `ISO`, `ModuleCode`, `ArgPathOrRolesOrOpt`, `ConfigProviderProps`, `JRPCEngineNextCallback`, `cookie.CookieSerializeOptions`, `Vote`, `ClipRenderContext`, `TRef`, `Json.ObjectValue`, `IApiKubernetesResource`, `DatabaseService`, `ContrastColors`, `IonicModalController`, `EffectCallback`, `WebGLQuery`, `ObservationService`, `IMatrixEventProcessorResult`, `IThyDropContainerDirective`, `CreateProps`, `AWSError`, `BufferStream`, `SqipImageMetadata`, `InvalidInput`, `AxisGeometry`, `EditorChangeEvent`, `UserMessage`, `ICXListHTLCOptions`, `Show`, `AnchorPosition`, `ShippingMethod`, `ButtonComponent`, `IAmazonServerGroup`, `ContainerConfig`, `RigidBodyComponent`, `DisplayNameChangedListener`, `ElectronCertificate`, `DoOnStreamFns`, `StorageQuotaExceededFault`, `TypographyProps`, `GetMessageKeys`, `DDL2.IField`, `ts.ConstructorDeclaration`, `Package.ResolvedPackage`, `GetConfigOptions`, `ColumnAnimation`, `ArenaNodeText`, `Bezier`, `MsgCloseGroup`, `KameletModel`, `ToneEvent`, `GraphQLDirective`, `AzExtTreeDataProvider`, `ElementSourceAnalysis`, `Algorithm`, `AaiMessageTraitDefinition`, `NotificationDataFilled`, `Plane3dByOriginAndVectors`, `AliasOptions`, `FormInterface`, `CommentType`, `VaultID`, `coreClient.OperationArguments`, `IEditorProps`, `GetReadinessCheckResourceStatusCommandInput`, `InruptError`, `Src`, `VisualizeEditorCommonProps`, `ViewModel_`, `requests.ListBdsInstancesRequest`, `DocumentValidationsResult`, `Load`, `NullAndEmptyHeadersServerCommandInput`, `LivelinessMode`, `LightType`, `ExternalDMMF.Mappings`, `GoalItemViewModel`, `DebugConsole`, `IAdjacencyBonus`, `PoiGeometry`, `CssBlockAst`, `AnyValue`, `PlaylistModel`, `PureComputed`, `TSTypeParameterInstantiation`, `DeleteDeploymentCommandInput`, `IVectorStyle`, `TeamMember`, `BaseMessage`, `Adb`, `CountParams`, `IGlobalManager`, `NgWidget`, `ListPoliciesCommandInput`, `Roadview`, `IDBIndex`, `ODataQueryArgumentsOptions`, `Tween`, `SetSelectionMenuDelegate`, `IDBValidKey`, `TextMarker`, `DocumentRangeFormattingParams`, `HeaderStreamManipulator`, `TGroupHandle`, `QueryHook`, `WithoutSheetInstance`, `TypeReference`, `GfxInputLayoutDescriptor`, `NormalizedModule`, `CreateRequest`, `IAppContainer`, `HDWallet`, `ToggleGroupProps`, `Uint256`, `PrerenderContext`, `RootBank`, `ReducersMapObject`, `Visit`, `BasicReflectionEvent`, `TimeFormatter`, `QueryJoin`, `Runtime.Port`, `SilxStyle`, `MultiChannelAssociationCCReport`, `SqrlInstance`, `IContainerNode`, `IEmbedConfigurationBase`, `XPCOM.nsIFile`, `TLSSocket`, `ChangeFn`, `Knowledge`, `UserType`, `Reservation`, `IFavoriteColors`, `HTMLScLegendRowElement`, `IComputedFieldOwner`, `PinejsClient`, `CompilerCtx`, `OpenApiRequestBuilder`, `SourceMapGenerator`, `AuthContextType`, `DocumentStore`, `NavigationDescriptor`, `ValidatedPassword`, `Parjser`, `NodeSSH`, `AlterTableAddColumnBuilder`, `RoomModel`, `AutocompleteItem`, `AccessorConfig`, `CachePage`, `TFunction`, `SerialOptions`, `DecorationOptions`, `Session`, `RepositoryStatistics`, `ReadonlyNFA`, `Let`, `ParsedResults`, `common.WaiterConfiguration`, `SingleSpaAngularOptions`, `ResolveModuleIdOptions`, `GoogleProvider`, `vd.VNode`, `QueryKey`, `ITypeUnion`, `DescribeDashboardCommandInput`, `AuthedRequest`, `Advice`, `AnyRawModel`, `ThrottleSettings`, `MIRTypeOption`, `TypeMap`, `EngineResults.EvaluateDataLossOutput`, `AccountingService`, `AthenaExecutionResult`, `StepInfo`, `DeploymentResult`, `PatternLike`, `d.OutputTargetDocsCustom`, `inferHandlerInput`, `DeleteLifecyclePolicyCommandInput`, `OrderedRotationAngles`, `IToolbarAction`, `MetadataProvider`, `Slab`, `PymStub`, `requests.ListBackupsRequest`, `ITextDiffData`, `WholeHalfUnison`, `StringTypes`, `CommandsSet`, `ParserProduction`, `TypedEvent`, `ArrayCollection`, `Collectible`, `DaffNewsletterSubmission`, `IApprovalPolicy`, `_GlobalJSONStorage`, `UINavigationBar`, `BatchCreateAttendeeCommandInput`, `SVErrorLevel`, `CSSObject`, `IPuppet`, `DirFileNameSelection`, `RequestMock`, `ContentModel`, `DataViewValueColumn`, `UseRefetchOptions`, `PhaseModel`, `DtlsContext`, `IsTenantAvailableInput`, `DataFetcherOptions`, `TEventHandler`, `NotificationID`, `ReplExpect.AppAndCount`, `LazyService`, `PacketInfo`, `IFilePropertiesObject`, `TypeMetadata`, `GitBlameCommit`, `CoreFeature`, `SerializedData`, `CustomType`, `JQueryMouseEventObject`, `GenerateMappingData`, `QRPolynomial`, `stream.Readable`, `Slot`, `LiveExample`, `Define`, `AttributeKeyAndValue`, `ContractInterface`, `TestSuiteInfo`, `d3Geo.GeoRawProjection`, `CharGroup`, `AppUserCard`, `CopyResponse`, `CredentialsOverwritesClass`, `GeneratorFile`, `IndexerManagementResolverContext`, `IErrorPayload`, `RuleEngine`, `FileMode`, `messages.Background`, `PartnerActions`, `UserFacade`, `DocumentLinkShareState`, `ParameterConfig`, `NodeChanges`, `BenzeneGraphQLArgs`, `RelayServiceConnectionEntity`, `TestPlayer`, `AnalyzeCommentResponse`, `MessageAttachment`, `Permissions`, `IncludeMap`, `InputMode`, `ModuleBlock`, `point`, `TPropertyTypeNames`, `RosApiCommands`, `Fiber`, `ContinuationData`, `HashMapIteratorLocationTracker`, `DialogItem`, `ExpoAppManifest`, `TraitNode`, `NormalCollection`, `GenericRequestHandlerChain`, `VerifyEmailAccountsValidationResult`, `MappedTypeNode`, `ScopedCookieSessionStorage`, `TValue`, `RedBlackNode`, `MountedHttpHandler`, `SourceFileLike`, `EnhancedGitHubNotification`, `Apollo.SubscriptionHookOptions`, `ActivitySettings`, `FlowView`, `PickResult`, `CesiumLayer`, `WebCryptoFunctionService`, `PDFAcroField`, `NavigationAction`, `AfterGroupCallback`, `IHTMLCollection`, `InternalTakomoProjectConfig`, `MIRInvokeDecl`, `requests.ListPdbConversionHistoryEntriesRequest`, `DescribeCertificateAuthorityAuditReportCommandInput`, `express.Router`, `GetSharedData`, `LogFileParsingState`, `ActivityHeight`, `PackTypeDefinition`, `TagResourceRequest`, `TypeGenerics`, `WalletInitializationBuilder`, `IContentSearchRequest`, `CodegenContext`, `BabelConfigOptions`, `DataInterface`, `ObservableValue`, `Trees`, `XMessageBoxAction`, `DependencyStatus`, `UsersOrganizationsService`, `DependencyInfo`, `React.FormEvent`, `GenericOperation`, `AppApp`, `ListQueuesCommandInput`, `LogFormula`, `Appservice`, `UInt8`, `JQuery.TriggeredEvent`, `IdentifierType`, `CreateResponse`, `Facets`, `ViewerNetworkEventStarted`, `FormEventDetail`, `PDFCatalog`, `ItemElement`, `Blueprint`, `requests.ListKeyVersionsRequest`, `TEDirective`, `RouteProps`, `GeometryType`, `GlobStats`, `QueryLeasesRequest`, `HandlerParamMetadata`, `InputEventMouseButton`, `ICommandManager`, `Fn3`, `Line`, `GetByIdAccountsValidationResult`, `MarkerBase`, `Postable`, `UpdateTableCommandInput`, `InsertChange`, `BackendWasm`, `TestSchemaProcessor`, `PiConceptProperty`, `PeriodData`, `Packet`, `CSSParsedDeclaration`, `INamedObjectSchemaProperty`, `AutowiredOptions`, `SerializedNode`, `GPGPUBinary`, `TypedDocumentNode`, `GraphQLQueryGenerator`, `ObjectValueNode`, `IAuthConfig`, `OfficialAccount`, `Segno`, `Embed`, `AddressBookEntry`, `PipetteNameSpecs`, `StructureMap`, `RedspotArguments`, `PopulatedContent`, `CrochetValue`, `AaiDocument`, `DatabaseInstanceHomeMetricsDefinition`, `InjectorClient`, `NgextConfigResolved`, `NavigationButton`, `ListRecommendationFeedbackCommandInput`, `OciError`, `DataGraph`, `GlobalChartState`, `SubsetCheckResult`, `ClusterClient`, `Radians`, `WebviewTag`, `SendEventCommandInput`, `Prize`, `SimpleInputParamsCommandInput`, `WU`, `QuickInfo`, `Geoposition`, `By2`, `ColumnHeaderOptions`, `ProgressModel`, `CaretPosition`, `QueryImpl`, `JsonEnumsCommandInput`, `fakeDevice.Device`, `FoundationType`, `TransactionMeta`, `UserTimeline`, `ServerTransferStateTranslateLoader`, `EmergencyCoordinates`, `GraphCalculator`, `ITreeDataProvider`, `SecurityService`, `Equaler`, `PieceModel`, `TopNavItem`, `IBackendRequestData`, `yubo.WaveOptions`, `IManualTimeInput`, `DecoratorData`, `UiThread`, `UploaderEnvs`, `BaseModule`, `ImmutablePerson`, `BasicAuthResult`, `td.AppLogger`, `ICoreService`, `PlatformRepositoryService`, `RelativeInjectorLocation`, `IStateProps`, `DeclarationBlockConfig`, `Draggable`, `SheetSpec`, `ProtoJson`, `Finality`, `Information`, `XCommentNode`, `requests.DeleteConnectionRequest`, `IFeatureOrganization`, `PropsWithAs`, `A.App`, `OutgoingHttpHeaders`, `WatchSource`, `IDBOpenDBRequest`, `IResizeState`, `RouteFilterRule`, `On`, `MiddlewareFunction`, `FileAsset`, `ServerArgs`, `TimePickerBase`, `AggConfigs`, `CipherCollectionsRequest`, `UserController`, `SocketIO.Socket`, `ModelSummary`, `ng.IAttributes`, `requests.ListBdsMetastoreConfigurationsRequest`, `ERROR_CODES`, `Fixer`, `ShaderAttributes`, `NextLink`, `AutorestExtensionHost`, `MiniSimulation3D`, `DefaultClause`, `RollupStateMachine`, `CISKubeBenchReport`, `MasterKeySecret`, `Pseudo`, `DateTimeData`, `BaseHandlerCommonOptions`, `AzureComponentConfig`, `IGameState`, `Cat`, `SceneGraphComponent`, `Launch`, `DataLabelOptions`, `Katana`, `ThemeObject`, `VariableParserAST`, `AttributionData`, `Pickability`, `webpack.compilation.Compilation`, `HumanAddr`, `OrganizationalUnitConfig`, `BarService`, `FastifyPluginCallback`, `FirebaseTools`, `ListRowProps`, `SignatureHelpParameter`, `Server`, `CreateDeviceDTO`, `GetCertificateCommandInput`, `DappKitRequestMeta`, `ListEventsRequest`, `RecordDef`, `TableInstance`, `DropTargetMonitor`, `DeleteResult`, `FabricWallet`, `Tick`, `Accelerometer`, `IVec3Term`, `IObservable`, `ActionCodeSettings`, `ElectionMetadata`, `MapMouseEvent`, `SearchRequest`, `LocaleRecord`, `MarkdownProps`, `PropTypeConfig`, `LinkingCrossPlatform`, `JPA.JPAResourceData`, `logging.Level`, `ActionParams`, `IExportedValue`, `ArticleModel`, `ResetDBClusterParameterGroupCommandInput`, `ast.EscapeNode`, `Beacon`, `IMapping`, `OperationDescriptor`, `WetMessage`, `Delete`, `ConfigStorage`, `ShapeOptions`, `ts.BooleanLiteral`, `AssetService`, `BleepsSettings`, `SliderComponent`, `FrameData`, `DomainName`, `EditionsList`, `SimplePubSub`, `ErrorContinuation`, `ImportResolver`, `UnicornInfo`, `AlertInstance`, `d.Workbox`, `AddGroupUsersRequest`, `EventRepository`, `NodeCallback`, `FloatingPanel`, `Reduction`, `ResponsiveQueryContextType`, `EdaColumn`, `ToolchainName`, `TSForIn`, `Editors`, `GradientAngularVelocity`, `SingleResponseModel`, `THREE.Texture`, `VideoCapture`, `InheritanceChain`, `All`, `AtomChevronElement`, `UpdateSubnetGroupCommandInput`, `EnumEntry`, `ScreenReaderSummaryStateProps`, `ParserError`, `OnChildElementIdArg`, `ModifyRelationOptions`, `RoutesMeta`, `PackageChangelog`, `OperationPath`, `Easing`, `IHydrateResult`, `ReaderMiddleware`, `FormValues`, `d.CollectionCompilerMeta`, `VpnClientIPsecParameters`, `TiledMapResource`, `ConstantNode`, `requests.ListNetworkSecurityGroupSecurityRulesRequest`, `GenericThemes`, `SearchStrategyProvider`, `XYAndZ`, `PanelPlugin`, `NodeJS.Timer`, `SflibInstrumentMeta`, `IModelDb`, `FeatureSet`, `ErrorRequestHandler`, `Prog`, `ERC721ContractDetailed`, `CategoricalChartState`, `ScrollBehavior`, `GraphQLResponse`, `IAddMemberContext`, `ClientHello`, `YesNoLimitedUnknown`, `CustomQuery`, `These`, `Top`, `ColumnMetricsObject`, `StorageType`, `IUserInfo`, `PreprocessCollector`, `BitcoinAPI`, `GPUBuffer`, `TagResourceInput`, `SymbolTable`, `CtrOr`, `FlexibleConnectedPositionStrategyOrigin`, `TParams`, `IEntityAction`, `UInt64Value`, `BranchNode`, `FilePreviewModel`, `RuleFn`, `Children`, `lf.query.Select`, `IWatchCallback`, `CombatantInfoEvent`, `InferableComponentEnhancer`, `DatabaseEventBus`, `BlobPart`, `ICreateTableOptions`, `ISearchResponse`, `LocalRepositoryService`, `AnyToVoidFnSignature`, `IModalListInDto`, `CollapsableSidebarContainerState`, `CurrencyFormat`, `CardHeaderProps`, `UrlTree`, `RenderBox`, `IMarker`, `Derivative`, `JGOFMove`, `http.IncomingHttpHeaders`, `MatchedMention`, `ReadableAtom`, `SinonStub`, `CoreAPI`, `TopicsService`, `ViewConverter`, `SearchBar`, `ShallowWrapper`, `ESTree.CallExpression`, `DayResults`, `InputModel`, `PageG2Type`, `IOrganizationRecurringExpenseFindInput`, `PivotAggsConfig`, `TreeBranch`, `StepExpr`, `FileSystemProviderWithFileReadWriteCapability`, `CommandLineStringListParameter`, `Core`, `ISagaModule`, `INavNodeFolderTransform`, `CmsEditorFieldTypePlugin`, `TRejector`, `PipelineDescriptor`, `LibSdbTypes.Contract`, `VertexEntry`, `SpatialAudioSeat`, `SqsMetricChange`, `StoryApi`, `ts.Node`, `IIMenuState`, `ScanGameFile`, `BMP24`, `MIPS.Register`, `IOpenSearchDashboardsMigrator`, `OperationsListOptionalParams`, `CdtFrontElement`, `CodeError`, `Await`, `DataKey`, `UberToggleState`, `CancelToken`, `StatsTree`, `Msg`, `CreateChannelResponse`, `DTMock`, `PhotoData.PhotoDataStructure`, `CSVDataImporter`, `FileWatcherEventType`, `http.ServerResponse`, `Linter.Config`, `EntryProps`, `IJob`, `BlockGroup`, `LoginInput`, `CfnIntegration`, `AsyncQueue`, `PlatformConfig`, `TicTacToeAppState`, `ResolvedPos`, `DeleteDBSubnetGroupCommandInput`, `CustomCallAst`, `ProxyNode`, `requests.ListExadataInfrastructuresRequest`, `AsyncQueryable`, `DescribeParametersCommandInput`, `ECA`, `RNN`, `PreCheckerClient`, `AspectRatioType`, `InputEventType`, `ExpressionAstExpression`, `PiClassifier`, `ReportingUser`, `GoogleMeetSegmentationOperationParams`, `IBlockHeader`, `FungiblePostCondition`, `TimelineElement`, `LocalDataProvider`, `BoundFrustum`, `TooltipInitialState`, `TreeEntry`, `OptionFC`, `Events.hidden`, `TexturePalette`, `PopupService`, `FileStorageOption`, `SentinelType`, `SpectatorFactory`, `ExpandResult`, `AnyConstructor`, `TileDoc`, `SinkBehavior`, `HttpClientRequestConfig`, `BookModel`, `CrawlerDomain`, `DeploymentParams`, `Subgraph`, `QueryDetails`, `requests.GetAllDrgAttachmentsRequest`, `GraphQLInputFieldConfigMap`, `PendingQueryItem`, `JConfiguration`, `DistinctValuesRpcRequestOptions`, `EstimateGasOptions`, `ChangeUserLanguageDto`, `ProcessMainAdapter`, `IUrl`, `PutAppInstanceRetentionSettingsCommandInput`, `UserIdDTO`, `puppeteer.ClickOptions`, `Pose2DMap`, `LazyBundleRuntimeData`, `DescribeFlowCommandInput`, `ConnectionInfo`, `Quota`, `IChangeInfoHash`, `IOptionsService`, `TwingNode`, `ExpNumUop`, `FillerHook`, `SimplifiedParameterType`, `mongoListener`, `OpenAPI.HttpOperation`, `TFieldName`, `DOMWidgetView`, `DynamoDBClient`, `EventHub`, `ListingType`, `RaycasterService`, `SSRContext`, `UpdateEntry`, `Importer`, `ForestNode`, `FormRowModel`, `ParticleEmitterWrapper`, `PanelState`, `PlatformInformation`, `LayerVariable`, `FileData`, `AreaService`, `UpdateThemeCommandInput`, `FileWatcherProvider`, `PvsContextDescriptor`, `VersionHistory`, `TelemetryContext`, `TableProps`, `CompoundStatementContext`, `Nonce`, `Fun`, `Markets`, `ComponentTypeTree`, `NonFungibleConditionCode`, `TagCreator`, `requests.ListFindingsRequest`, `IOutput`, `ToastProvider`, `WalletContextState`, `SectionConfig`, `IInteraction`, `AllQueryStringTypesCommandInput`, `TypedArrayConstructor`, `OrganizationModel`, `EntityActionPayload`, `IQueryBus`, `PageSort`, `ApplicationContract`, `CalendarView`, `NeuralNetwork`, `FeatureNode`, `GraphModel`, `ServerCancellationToken`, `ShaderMaterial`, `MainWindow`, `QueryEngineConfig`, `Relay`, `InstructionWithText`, `FormatMetadata`, `BuildifierConfiguration`, `GPUShaderModule`, `J3DModelInstance`, `IPlotState`, `PrivateKeyPEM`, `Keys`, `LoaderResource`, `TransitionSpiral3d`, `MatListOption`, `NotebookCell`, `IntrospectionEngine`, `SessionContext`, `coreRestPipeline.RequestBodyType`, `IVocabularyItem`, `NzSelectItemInterface`, `IRemovalInfo`, `BasePacket`, `ConnectedAccount`, `DescribeDBEngineVersionsCommandInput`, `StripePaymentListener`, `ExtendableBox`, `Exclude`, `JQuery.ClickEvent`, `BlockModel.Resolved`, `JsonSchemaRootAssertion`, `grpc.Request`, `AsyncArray`, `ConnectionSummary`, `CompiledPredicate`, `DateSpan`, `Interior`, `JRPCEngineReturnHandler`, `IsSelectableField`, `StoreTypes`, `TextLiteralContext`, `MetadataCacheResult`, `ExpressionsService`, `OpMapper`, `ConfigRepository`, `ResolverInput`, `XTermMessage`, `IHookStateInitAction`, `T.RenderFunction`, `ActivityRequestData`, `ResolverFactory`, `BezierPoints`, `PerformRenameArgs`, `DescribeClusterCommandInput`, `FieldValidator`, `TrialVisit`, `ITab`, `IVerificationGeneratorDependencies`, `IsDeletedEventPipe`, `AtlasResourceItem`, `MangoGroup`, `EosioContractRow`, `Verifiable`, `NowBuildError`, `FinderPattern`, `DecompositionResult`, `PerformReadArgs`, `RegisterInstanceCommandInput`, `ObjectTypeMetadata`, `AvailableFilter`, `RecursiveShapesCommandInput`, `TwingSource`, `DaffCartFacade`, `TootDetailState`, `IRadioGroupProps`, `Swarm`, `KBService`, `PositionComponent`, `JSONIngestionEvent`, `JsonFormsCore`, `GetPredicateParams`, `ValidateEvent`, `StorableUser`, `Sampler`, `TxCreate2Transfer`, `InputTokenObject`, `OvSettingsModel`, `GX.DistAttnFunction`, `BuildConfig`, `FileNode`, `KeywordErrorDefinition`, `WorkspaceEdit`, `InputOnChangeData`, `NativeScriptPager`, `DeviceDetectorService`, `CustomPropertyDecorator`, `HttpsProxyAgent`, `Arc`, `NodeProps`, `GridProps`, `Approval`, `SpawnOptionsWithoutStdio`, `HashCounter`, `RatioMetric`, `VerificationRule`, `TagEntity`, `NSString`, `UID`, `CompilerSystem`, `ARCommonNode`, `UnderlyingAsset`, `PartialMessageState`, `TheSagaStepfunctionSingleTableStack`, `ValidatorSpec`, `AuditLogger`, `FunctionEntity`, `BreadcrumbProps`, `moq.IMock`, `AppStatusStore`, `InvertedIndex`, `SpriteAssetPub`, `ByteSizeValue`, `BaseChartisan`, `Timesheet`, `PenroseState`, `UserConfiguredActionConnector`, `AuthService`, `ClientTipsData`, `GeoNode`, `NotificationType0`, `DayPickerProps`, `SignerWithAddress`, `D3_SELECTION`, `ClassSelector`, `ReplyMsgType`, `TensorBuffer`, `QueryCallbacksFor`, `AlertContentProps`, `TagResourceResult`, `AutoBounds`, `Conflict`, `TripleObject`, `IdOrSym`, `CLI_OPTS`, `TorrentState`, `WIPLWebpackTestCompiler`, `P2WPKHTransactionBuilder`, `PreviewState`, `ItemInfo`, `HostRule`, `EcsEvent`, `UpdateExpressionDefinitionChain`, `wjson.MetricWidgetAnnotationsJson`, `CopyAsOrgModeOptions`, `RegName`, `React.KeyboardEvent`, `VNodeThunk`, `MatchExpr`, `GenericCall`, `StatusIndicatorProps`, `TLayoutSize`, `GeoPosition`, `createStore.MockStore`, `ActionHandlerRegistry`, `ResolvedType`, `requests.ListTargetDatabasesRequest`, `Drop`, `TableItem`, `EncodedMessage`, `AmqpConnectionManager`, `connection`, `HubstaffService`, `CoreFeatures`, `IonicApp`, `GeneratorContext`, `d.CompilerFileWatcherCallback`, `ListOrganizationAdminAccountsCommandInput`, `OAuthToken`, `CreateGroupRequest`, `Func0`, `OneOrMany`, `P.Parser`, `RadixParticleGroup`, `ToggleComponent`, `Type`, `CredentialRepresentation`, `JSONSchemaAttributes`, `DiscoveryService`, `TargetLanguage`, `HeftConfiguration`, `ABLTempTable`, `BoundsOctreeNode`, `GF`, `CashScriptVisitor`, `DocumentationLink`, `CoverageFlatFragment`, `MeshBuffers`, `UploadTask`, `PlayState`, `SpaceUser`, `DataServiceConfig`, `Signale`, `GraphSignedTransferAppState`, `Types.Config`, `PiContainerDescriptor`, `Minimum`, `CanvasTheme`, `ShowProjectService`, `TopicStatus`, `InputFile`, `TrackedEither`, `ts.SwitchStatement`, `IDBFactory`, `ProgressCallback`, `Weave`, `RelationalOperatorConfig`, `HTTPError`, `IRoute.IParameter`, `Matrix3d`, `AbortedCallback`, `HsConfig`, `IFetchedData`, `BlockAttributes`, `Commitment`, `TlsConfig`, `SidenavMenu`, `AppOptions`, `PluginHost`, `JSONEditorSchema`, `CreateProjectCommandOutput`, `PartyMatchmakerRemove`, `LeaderboardRecord`, `BasePath`, `Flap`, `ModuleResolutionState`, `Graphics.BlendOperation`, `VirtualNode`, `TClass`, `AttributeValueChoiceOption`, `ExpShapeSlice`, `IndexOp`, `ListUserGroupsRequest`, `TimePointIndex`, `Classes`, `Y.Doc`, `Styles`, `AzureFileHandler`, `PluginInstance`, `MarketInfo`, `ClarityAbi`, `CheckboxState`, `TextNode`, `MockPointOptions`, `ChipColor`, `INetworkInfoFeatureDependency`, `WetAppBridge`, `IncomingForm`, `ODataQuery`, `IRuleSpecObj`, `ISkill`, `UnwrapRef`, `FileRecord`, `TemplateParam`, `DaffCategoryFilterEqualToggleRequest`, `fixtures.Fixtures`, `SfdxFalconErrorRenderOptions`, `L.Property`, `UseLiveRegionConfig`, `VariantCurveExtendParameter`, `AppGachaItem`, `InversionFix`, `ModelPlayer`, `IMapState`, `TextElementFilter`, `DaffCategoryFilterRequest`, `MetadataScanner`, `RegSuitCore`, `ast.Name`, `ScalarParamNameContext`, `EventHandler`, `StreamHead`, `IHistory`, `CubieCube`, `TypedArrays`, `ProblemDimension`, `ISettingRegistry`, `MicrosoftDevTestLabLabsResources`, `FormatFlags`, `zowe.IUploadOptions`, `WorkRequestSummary`, `BasicAcceptedElems`, `CreateDomainResponse`, `IWorkspace`, `TestElementProps`, `ParseParams`, `FibaroVenetianBlindCCGet`, `CaseUserActionsResponse`, `UnitOfMeasurement`, `IRichPropertyValue`, `PublicTransition`, `PluginPositionFn`, `ActionTreeItem`, `CustomerState`, `t.STStyle`, `StackedRNNCellsArgs`, `InputMessage`, `ParsedRepo`, `ListSecurityProfilesCommandInput`, `ServerRequest`, `ListEnvironmentsCommandOutput`, `NameObj`, `IconName`, `CoverageMap`, `SharedFunctionCollection`, `OptionDefinition`, `CpuRegister.Code`, `MessageHashService`, `Blockly.Workspace`, `InjectableMetadata`, `ResourceValue`, `Mesh2D`, `EuiBasicTableColumn`, `IToolbarDialogAddonHandler`, `DescribeResourceCommandInput`, `ThyAbstractOverlayPosition`, `PostprocessSetOptions`, `StackInspector`, `ModuleNameAndType`, `EllipsisNode`, `Protobuf.Type`, `EntityLoaderOptions`, `DocumentWatcher`, `BrowserState`, `float`, `Outputs`, `MapAnchor`, `DescribeAddressesCommandInput`, `LinesChangeEvent`, `Percentage`, `Pause`, `DocumentOnTypeFormattingParams`, `IDBPTransaction`, `InterfaceCombinator`, `SerializedFieldFormat`, `NodeCollection`, `DropdownListItem`, `ProblemLocation`, `LexerContext`, `BlockEntity`, `NotificationPayload`, `LiveAnnouncer`, `Calendar_Contracts.IEventCategory`, `HandlerArgs`, `RelativePattern`, `WriteStream`, `INotesGetByContactState`, `Done`, `CesiumService`, `RTCSessionDescription`, `MethodAbi`, `OptimizeJsResult`, `LocationHelper`, `CtrAnd`, `IQuizQuestion`, `SelectionModelConfig`, `PluginService`, `ISpacesClient`, `ChartComposition`, `QuerySolution`, `FormatterProps`, `RichRemoteProvider`, `CachedItem`, `ContentEditableEvent`, `HostSchema`, `UISchemaElement`, `ESLintNode`, `MDCRipple`, `IInput`, `GfxBindingsDescriptor`, `ExtendedPoint`, `FilterData`, `RpcMessagePort`, `SoloOptions`, `RnnStepFunction`, `DeployBundle`, `AnyBuildOrder`, `GlobalModelState`, `TComponentConfig`, `AggregateColumnModel`, `FormSchema`, `RawSavedDashboardPanel640To720`, `ListManagementAgentsRequest`, `Schemas`, `ParameterNode`, `RenderContainer`, `ISPListItems`, `IActivity`, `types.IDBRow`, `NightwatchBrowser`, `ConfigModule`, `ServiceHealthStatus`, `DataTransferItemList`, `Conv3D`, `InAppBrowserObject`, `IMenuItemInfo`, `CapabilitiesResolver`, `GroupEntity`, `ResolveContext`, `TapoDeviceKey`, `CommonTypes.NotificationTypes.LastKnown`, `ThyGuiderManager`, `RoomService`, `SetupApp`, `WishlistState`, `ExpString`, `ExportCollector`, `SystemHealth`, `BindingForm`, `Ng2SmartTableComponent`, `DictionaryNode`, `GroupItemDef`, `TimerService`, `CopyDBParameterGroupCommandInput`, `DataTable.Row`, `WithUserAuthOptions`, `PaymentService`, `RequestorHelper`, `DeleteSecurityConfigurationCommandInput`, `THREE.Quaternion`, `LocaleOptions`, `IEventSource`, `requests.ListDbSystemShapesRequest`, `ColumnsType`, `SupportedModels`, `GetDirsOrFilesOptions`, `DoomsdayDevice`, `CreateProjectResponse`, `HeaderRepository`, `ArrowCallableNode`, `Regex`, `CoverageRunner`, `DeleteDBParameterGroupCommandInput`, `L1Args`, `ConfigurableCreateInfo`, `RepoCommitPathRange`, `UpdateClusterCommandInput`, `INodePackageJson`, `ReviewItem`, `MongoPagination`, `IPatchRecorder`, `DryadPlayer`, `ProtractorExpectedConditions`, `CommentDto`, `MeetingEvent`, `GroupButton`, `TNodeType`, `ImageConfig`, `PropertyValueRendererContext`, `ScreenshotOptions`, `requests.ListMigrationsRequest`, `AnimationOptions`, `UserService`, `SimpleClass`, `AnimationMixer`, `LiveAtlasWorldDefinition`, `StableTokenInstance`, `BlueprintInfo`, `BitSet`, `DocumentContext`, `VectorStage`, `PartialStepState`, `NotificationCCAPI`, `position`, `JwtService`, `BitWriter`, `GeneratedIdentifierFlags`, `LayerWizard`, `HttpResult`, `xLuceneFieldType`, `S3PersistenceAdapter`, `SlugifyConfig`, `ScryptedNativeId`, `StixObject`, `Ending`, `FeatureDefinition`, `FakeConfiguration`, `SoftwareSourceId`, `ICompletionItem`, `FieldFilterRowData`, `MediaExtended`, `RouteState`, `IWatchExpressionFn`, `Core.Color`, `UnitProps`, `ElementSelector`, `web3ReactInterface`, `AsyncFunction`, `LimitLeafCounter`, `int`, `Vidi`, `CmbInstance`, `CPU6502`, `ScannedElementReference`, `GoToOperation`, `AccountsModel`, `protos.common.CollectionConfigPackage`, `AN`, `CollectorState`, `RouteRecordRaw`, `ValidationQueueItem`, `Cypress.Chainable`, `ExternalSource`, `CoinTransfer`, `Nodes.ASTNode`, `ListPermissionsCommandInput`, `IAttributeData`, `IConnectionParams`, `Prisma.SortOrder`, `VirtualNetworkWaiter`, `CatalogEntry`, `ArrayNode`, `HSD_JObjRoot_Instance`, `SpecificWindowEventListener`, `RepaymentRouterContract`, `cg.Key`, `SizeWithAspect`, `Branch`, `ConversionFunction`, `IDroppableItem`, `HJPlayerConfig`, `GLSL`, `BaseContractMethod`, `FilterExcludingWhere`, `IndicatorObject`, `AsyncResource`, `UiSettingsDefaultsClient`, `InternalCoreStart`, `LinkDownload`, `Adapters`, `ReadyValue`, `AuthStorage`, `WorkboxService`, `TestKernelBackend`, `io.WeightsManifestConfig`, `CmsGroupPlugin`, `NamedTensorsMap`, `AboutComponent`, `HSD_JObj_Instance`, `WorkbenchPageObject`, `Range2d`, `SimulatedPortfolio`, `CaseStyle`, `ArtifactVersion`, `ReplayTick`, `PaymentInformation`, `Lanes`, `ExtendedBlock`, `WildlingCard`, `RuntimePlugin`, `ServerClass`, `ElementRect`, `ConditionalDeviceConfig`, `IXPath`, `Noise`, `ComponentFramework.Dictionary`, `MetaTagModel`, `DenseLayerArgs`, `CdkOption`, `LayerName`, `LegendLocationSettingsProps`, `TemplateLiteralType`, `TimelineKeyframe`, `MathjaxAdaptor`, `PopupState`, `ValueIterator`, `IDecodePackage`, `SignaturePubkeyPair`, `LinkedNodeList`, `DocViewRenderProps`, `OrderedIterable`, `EdgeType`, `WidgetProps`, `ErrorCodeDefinition`, `IContainerProps`, `FetchVideosActions`, `ITaskFolder`, `Apdex`, `window.ShellWindow`, `THREE.Group`, `InPacketBase`, `FailureEventData`, `DealCriteria`, `QueryNameContext`, `QueryOne`, `TypeDescriptor`, `IZosmfTsoResponse`, `JasmineBeforeAfterFn`, `ICacheItem`, `TileTextElements`, `FlashcardFieldName`, `AccountGoogle`, `CustomArea`, `OperationOptions`, `BrowseResult`, `NotificationPressAction`, `TColumnRowPair`, `d.Config`, `Modifiable`, `GeneratedCodeInfo_Annotation`, `RenderArgsDeserialized`, `_Explainer`, `OrganizationPolicy`, `IngameGameState`, `SphereColliderShape`, `IChapter`, `TraceStep`, `DragItem`, `IFBXConnections`, `GitRevisionReference`, `GroupUserEditResponse`, `ConfigLoaderResult`, `FieldError`, `DefaultSDP`, `IVarAD`, `tinyapp.PageOptions`, `BrowserFftSpeechCommandRecognizer`, `TAuthUserInfo`, `CodeMirrorAdapter`, `IFruit`, `ContextEntry`, `ITreeItem`, `MerchantUserEntity`, `EventFragment`, `NodeTracerProvider`, `OpOrData`, `Fix`, `PaneInvalidation`, `SpaceBonus.STEEL`, `StickyDirection`, `ICXOffer`, `PercentLength`, `DescribeChannelModeratorCommandInput`, `CopyDBClusterParameterGroupCommandInput`, `ListTablesCommandInput`, `SteamDeviceReport`, `TransferOptions`, `FabricIdentity`, `TextAreaCommandOrchestrator`, `Integer64`, `SafeBlockService`, `Trigger`, `IViewportInfo`, `MailOptions`, `BiquadFilter`, `ControllerMeta`, `Instance`, `ProjectExport`, `_CollectorCallback2D`, `ReflectionCategory`, `ISiteScriptAction`, `ConditionExpressionDefinitionFunction`, `WorkingService`, `FlatConvectorModel`, `HomeService`, `UnitFormatOptions`, `MappingEvent`, `RouteObject`, `VectorOptions`, `SandboxType`, `VpnConnection`, `SignedStateWithHash`, `AsyncComponent`, `PageScrollInstance`, `TxBroadcastResult`, `HierarchicalFilter`, `MetricTypes`, `SignupDTO`, `ng.IAugmentedJQuery`, `ApiQueryOptions`, `tcp.ConnectionInfo`, `CurriedFunction2`, `NodeKind`, `EngineConfig`, `PreventAny`, `Condition`, `tf.TensorBuffer`, `SetupFn`, `OrganizationTeamsService`, `StructuredTypeSchema`, `FormattingContext`, `TInstruction`, `ArrayPaginationService`, `BindingDef`, `PsbtInputData`, `PopoverContextOptions`, `MDCTopAppBarBaseFoundation`, `PoolCache`, `MonzoPotResponse`, `HttpClient`, `ColumnsContextProps`, `DescribeReplicationConfigurationTemplatesCommandInput`, `OrganizationMembershipProps`, `ABLVariable`, `Granularity`, `TermsIndexPatternColumn`, `SessionStorageCookieOptions`, `Format`, `ContractVerificationInput`, `ScrollHooks`, `Database`, `ProductResult`, `Dayjs`, `NcPage`, `ArgumentCheck`, `theia.CancellationToken`, `Lines`, `PriorityListGroup`, `CloudDirectorConfig`, `dayjs.ConfigType`, `ScmRepository`, `ODataApi`, `Bias`, `IpcPacket`, `IExportData`, `HasId`, `flatbuffers.Builder`, `BungieGroupMember`, `ListTagsResponse`, `UpToDateStatus`, `CpuRegister`, `WriteStorageObjectsRequest`, `TwingEnvironment`, `RushCommandLineParser`, `A`, `StyleProps`, `SeedAndMnemonic`, `LabelValues`, `OnCancelFunc`, `ErrorHandlingResult`, `ECSComponentInterface`, `UpdateOpts`, `FindCharacterMotion`, `GeneratorError`, `ThyTransferItem`, `requests.ListDataSafePrivateEndpointsRequest`, `IMenuItemConfig`, `requests.ListCloudVmClustersRequest`, `Stroke`, `GameFeatureObject`, `GXMaterialHelperGfx`, `ReadModelStoreImpl`, `ManagedFocusTrap`, `BuildStyleUpdate`, `VirtualGroup`, `IAggFuncParams`, `CreateMockOptions`, `ChartHookReturnType`, `LockMode`, `FeedQueryVariables`, `TsickleIssue1009`, `IRequest.Options`, `ModelField`, `AggParamType`, `GetSpaceEnvironmentParams`, `MemberEntity`, `ActionConnector`, `UiStateStorage`, `ListField.Value`, `DQLSyntaxErrorData`, `SaladTheme`, `TokenService`, `MessageViewProps`, `PotentialApiResult`, `IQueueRow`, `providers.BaseProvider`, `TestInfo`, `CompilerJsDocTagInfo`, `ManifestEditor`, `App.services.IPrivateBrowsingService`, `KubernetesObject`, `IResourceEntity`, `CrochetTrait`, `ZipkinSpan`, `DeleteRuleGroupCommandInput`, `ErrorObservable`, `ContractName`, `TelemetryEvent`, `PointData`, `IOSProjectConfig`, `JourneyStage`, `ResponseDataAccessor`, `FunctionEnvelope`, `IEncoder`, `IPatchData`, `AudienceOverviewWidgetOptions`, `T.MachineEvent`, `NavigateToItem`, `SecurityTokenAdapter`, `Paged`, `MangoQuery`, `BuildDecoratorCommand`, `AthleteModel`, `JsonOutput`, `RequiredParams`, `MalFunc`, `EventList`, `NotebookCellData`, `ts.CompletionEntry`, `MethodWriter`, `OutModeDirection`, `PageDoc`, `FoldingContext`, `WifDecodeResult`, `EventFetcher`, `NetworkError`, `NativeTexture`, `HighPrecisionLineMaterial`, `ImageFormat`, `PddlConfiguration`, `RouteMap`, `Interception`, `LoginDto`, `ConnectorProps`, `IMenuContext`, `PostCombatGameState`, `WidgetsRegister`, `ChainState`, `IInviteAcceptInput`, `SimpleTypeFunctionParameter`, `IConfigData`, `GovernObservableGovernor`, `CornerMap`, `FoundOrNot`, `FramesType`, `IObserverLocator`, `DisabledTimeFn`, `ListOfferingsCommandInput`, `MenuState`, `MDCShapeCategory`, `KeyringTrace`, `UnionType`, `ListServicesCommandInput`, `PadId`, `Bignum`, `S3Object`, `SObjectDefinition`, `InterfaceNamespaceTest`, `NuxtApp`, `SchemaMetadata`, `FunnelCorrelation`, `CacheService`, `ItBlock`, `DataSourceTileList`, `CtrLte`, `Breadcrumbs`, `BifrostRemoteUser`, `PhysicsComponent`, `StackTrace`, `GeneratorConfig`, `Comments`, `Eof`, `EventReporter`, `ButtonBaseProps`, `EntitySelectors`, `PromoCarouselOptions`, `LocationDescriptorObject`, `DOMStringMap`, `OpenOrders`, `AppCurrency`, `FunctionCallNode`, `TableEvent`, `PlasmicComponentLoader`, `GetDeliverabilityDashboardOptionsCommandInput`, `three.Geometry`, `ASTPath`, `AnyImportOrRequireStatement`, `PlayerChoice`, `ConfigurationCCReport`, `FileStatusResult`, `InputChart`, `Username`, `XmlDocument`, `DatasourceConfig`, `LinkLabelsViewModelSpec`, `AuditoryDescription`, `DAL.DEVICE_ID_SYSTEM_LEVEL_DETECTOR`, `ColorPickerItem`, `LoginResponse`, `BlobsModel`, `Interface2`, `CounterService`, `LocationMarkModel`, `AWSContext`, `CreateCatDto`, `GraphcisElement`, `cc.AudioClip`, `NodejsFunction`, `LoggerSink`, `EmbeddedRegion`, `ProgressUpdate`, `EncryptedMessageWithNonce`, `StatePathsMap`, `DeploymentTemplateDoc`, `AssignmentExpressionNode`, `WaiterResult`, `IStaticMetadata`, `CacheMap`, `T12`, `turkInformation`, `SegmentBase`, `UnsubscribeCommandInput`, `ParseStream`, `SchemaUnions`, `ClozeRange`, `IStoredTransaction`, `CardModel`, `CopyLongTermRetentionBackupParameters`, `LogLevelType`, `Tspan`, `EventsService`, `ShurikenParticleSystem`, `WebviewPanel`, `LineUp`, `Electron.MessageBoxReturnValue`, `ESLPanel`, `HleFile`, `PuzzleGeometry`, `ISODate`, `PeriodicWave`, `StepGenerator`, `Lint.IOptions`, `requests.ListAvailablePackagesForManagedInstanceRequest`, `MessagesPageStateModel`, `Referenceables`, `FetchHandle`, `ColorDynamicStylePropertyDescriptor`, `UICollectionViewLayoutAttributes`, `PatternEnumProperty`, `EuiSwitchEvent`, `IScope`, `Hover`, `THREE.Material`, `IRadio`, `AnyResponse`, `RunGroupProgress`, `PathObject`, `RedirectPolicy`, `Platforms`, `QueryArgDefinition`, `CreateQueueCommandInput`, `PartyMatchmakerTicket`, `Frequency`, `FileType`, `DecodedOffset`, `view.View`, `OrdenationType`, `MaterialLayer`, `ScreenOptions`, `IRenderableColumn`, `ProjectQuery`, `puppeteer.ScreenshotOptions`, `Animated`, `IFunctionAppWizardContext`, `AbstractElement`, `SaveEntitiesCancel`, `RenderServiceMock`, `AssetDetails`, `ClientContext`, `StakingBuilder`, `GameMap`, `AcceptPaymentRequest`, `Schema`, `DictionaryExpandEntryNode`, `IOrg`, `TreeNodeInterface`, `BSTProcess`, `UnitTypes`, `GotResponse`, `RealFileSystem`, `IListenerDescription`, `CaptureOptions`, `ChromeBadge`, `LazyBundlesRuntimeData`, `HighlighterOptions`, `CompositionEvent`, `IBetaState`, `ChannelMetadataObject`, `TextureCubeMap`, `ts.TranspileOptions`, `Sku`, `TokenIndexedCoinTransferMap`, `IO`, `RecordSourceProxy`, `ListTagsForResourcesCommandInput`, `Sprite`, `EyeProps`, `RtmpOutput`, `WriteBuffer`, `HSD_TETev`, `RawValue`, `vscode.CancellationToken`, `AppUpdater`, `IGatewayMemberXmpp`, `TFLiteWebModelRunnerTensorInfo`, `MarkerData`, `ValueMap`, `IApiSourceResult`, `IRichTextObjectItem`, `RoomBridgeStoreEntry`, `PluralRules`, `FocusOptions`, `TaskRunnerCallback`, `AuthenticateGameCenterRequest`, `SVObject`, `BaseAdapter`, `UpdateAccountSettingsCommandInput`, `PutBucketLifecycleConfigurationCommandInput`, `RequestId`, `IWidget`, `IBrowser`, `VirtualKeyboard`, `TransformResult`, `ActionBinding`, `BaseLayer`, `MeetingAdapter`, `IJsonSchema`, `HammerInputExt`, `ExecutionPathProps`, `LinterConfig`, `CombatZerg`, `PromisifiedStorage`, `GetLaunchConfigurationCommandInput`, `TestScriptErrorMapper`, `PolyfaceData`, `StyleResources`, `IControllerAttributeProvider`, `ESLImage`, `Evaluate`, `RollupChunkResult`, `IStashEntry`, `FileSystemState`, `TopicsData`, `SdkError`, `AssignmentPattern`, `OrderWithContract`, `SqrlExecutionState`, `Game`, `google.maps.Map`, `MemberDescriptor`, `AnswerType`, `CanvasImageSource`, `PackageInstructionsBlock`, `ReduxStoreState`, `BrokerConfig`, `ConnectionConfig`, `IFindWhereQuery`, `AutorestNormalizedConfiguration`, `AccountManager`, `AssessmentData`, `CacheEntryListener`, `UIPreparationStorage`, `Case`, `ZRC2Token`, `Sector`, `ByteBuffer`, `IModelBaseHandler`, `TheWitnessGlobals`, `LayerArgs`, `SquireType`, `RequestState`, `UpdateWebACLCommandInput`, `TypedMessage`, `IntrospectionField`, `Http3PMeenanNode`, `NzThItemInterface`, `ActivityAudience`, `PreReqView`, `PageInstance`, `EnsuredMountedHTMLElement`, `AtomState`, `StravaActivityModel`, `IServiceParams`, `INameAtom`, `ExplorerView`, `SEdge`, `VSTS`, `ReconnectingWebSocket`, `TreeNodeComponent`, `android.view.View`, `SpeechSynthesisVoice`, `ClientEngineType`, `TargomoClient`, `ClassMethod`, `SessionPromise`, `StaffTuning`, `DaffCategoryFilterRequestRangeNumericFactory`, `FilterGroup`, `ActivityPubActor`, `DocumentView`, `DisconnectionEvent`, `IRestClientResponse`, `BackgroundProps`, `TypeObject`, `EyeglassOptions`, `d.ComponentRuntimeMetaCompact`, `Example`, `QuerySuggestionGetFnArgs`, `ParamInfo`, `FieldFormat`, `PutImageCommandInput`, `TimeBucketsInterval`, `FsWatchResults`, `StatusView`, `KVPair`, `AnimationTransform3D`, `TestEvent`, `PersistedData`, `CreateNote`, `DescribeDatasetCommandOutput`, `AxisDependency`, `ExpectStatic`, `sdk.AudioConfig`, `Node.Traversal`, `MatchJoin_MetadataEntry`, `Tree`, `IDesk`, `Merchant`, `JWKStore`, `B7`, `RoleRepository`, `TextOpComponent`, `UnitFactors`, `requests.ListEventsRequest`, `RequestOptions`, `ReplicationConfiguration`, `SavedObjectComparator`, `V1Prometheusrule`, `ConnectionID`, `CreateJobRequest`, `EdgeNode`, `StatesOptionsKey`, `Site`, `J3DFrameCtrl`, `ServiceQuotaExceededException`, `ResourcesFile`, `MochaDone`, `CreateRangeChartParams`, `DisabledDateFn`, `TViewNode`, `Chunk`, `MetadataService`, `AccountRipplePaymentsConfig`, `ConstructorFuncWithSchema`, `DeploymentParametersDoc`, `ResolvedElementMove`, `Repertoire`, `IntersectionC`, `CommandResponse`, `AggregateResponse`, `IWorkflowExecutionDataProcess`, `SqrlRuleSlot`, `PushpinUrl`, `BooleanFilter`, `_Props`, `IfNotExistsContext`, `ForgeModInput`, `CraftTextRun`, `ReactVisTypeOptions`, `TorrentInfo.MediaTags`, `FeatureEdges`, `GitData`, `AuthRequired`, `MousePosition`, `AwsRegion`, `FaastModule`, `backend_util.Activation`, `ListDomainsResponse`, `IMyDpOptions`, `NgSourceFile`, `WalletType`, `IFormField`, `PouchDB`, `ConfigType`, `FileWatcher`, `AggResponseBucket`, `LineCollection`, `RendererType2`, `InputRegisterMaster`, `WebGLResourceRepository`, `Spark`, `IVssRestClientOptions`, `Add`, `BaseInternalProps`, `DescribePendingMaintenanceActionsCommandInput`, `ExtensionProvider`, `StylesConfig`, `FileSystemWatcher`, `C1`, `App.windows.window.IMenu`, `ExtensionPriority`, `InjectCtx`, `ChartsState`, `MediaSlotInfo`, `AdonisRcFile`, `RegistryClient`, `ast.CallNode`, `TypedTransaction`, `ApimService`, `FormattedTransactionType`, `TranspileModuleResults`, `AbstractSession`, `SyntaxNode`, `ReviewerRepository`, `LocationCalculator`, `InsertQueryNode`, `StoredState`, `BoardTheme`, `BFS_Config`, `ScopeFn`, `AST.Expression`, `SeedFile`, `C4`, `G2`, `GasParameters`, `BaseClass`, `VuexModuleOptions`, `apid.CreateNewRecordedOption`, `MdcSnackbarContainer`, `TileFeatureData`, `FlatScancode`, `VFileMessage`, `IIndex`, `SelectionChange`, `angular.IRootScopeService`, `NodeFetchHttpClient`, `Fp`, `providers.TransactionRequest`, `FunctionDeclaration`, `ReactiveChartDispatchProps`, `BlockhashAndFeeCalculator`, `LhcDataService`, `CommonTerminalEnum`, `PolarData`, `MockDocument`, `DetectorConfiguration`, `C8`, `X12QueryEngine`, `SimpleUnaryImpl`, `AssignableDisplayObjectProperties`, `PluginsStatusService`, `CollectionReturnValue`, `PortalService`, `ICommonCodeEditor`, `CommandFlag`, `AttributeIds`, `ModalFlavor`, `IMetricAlarmDimension`, `IResourceItems`, `pw.Frame`, `AggParam`, `ReactLike`, `RefactoringsByFilePath`, `IDataIO`, `MailService`, `MockFixture`, `Installation`, `BytesLike`, `MonzoBalanceResponse`, `ListPipelinesCommandInput`, `DiscoverSidebarProps`, `Series`, `CompositionContext`, `Canvas`, `Spinnies`, `ZoneChangeWhisperModel`, `d.PixelMatchInput`, `MemAttribute`, `AirUnpacker`, `PersistItem`, `AsExpression`, `FilePathPosition`, `PrimitiveValueExpression`, `ListTagsCommandInput`, `BackgroundBlurVideoFrameProcessorObserver`, `JSESheet`, `requests.ListWaasPoliciesRequest`, `IHeaders`, `Int32Value`, `HistoryRecord`, `HealthStatus`, `StackFn`, `ResultState`, `LoadingIndicatorProps`, `FetchHttpClient`, `CalendarEventsCache`, `ServiceClass`, `WebXRSystem`, `ScrollDispatcher`, `NodeVo`, `IChannel`, `DeleteBotVersionCommandInput`, `PutLoggingConfigurationCommandInput`, `ClClient`, `StringPublicKey`, `ModalController`, `Shader`, `TableColumns`, `Sub`, `IActionArgs`, `ResourceService`, `playwright.Page`, `ICDN`, `LocalizedError`, `GraphQLNonNull`, `ResourceAlreadyExistsException`, `OrderedAsyncIterableBaseX`, `Core.Position`, `ComponentLookupSpec`, `EntityTree`, `AuthStore`, `Join`, `napa.zone.Zone`, `XUL.tabBrowser`, `dataStructures.BufferMap`, `PriorityCollectionEntry`, `IUploadOptions`, `WidgetDescription`, `DateTimeNode`, `OffscreenCanvasRenderingContext2D`, `DogRepresentation`, `IWriter`, `ExpandGroupingPanelCellFn`, `CreateOpts`, `soundEffectInterface`, `MdxTexture`, `HelpRequest`, `NgbModalRef`, `CardImage`, `TopUpProvider.RAMP`, `ChildDatabase`, `QueryOpt`, `Param`, `DevicesStore`, `TooManyRequestsException`, `TaskObserver`, `requests.ListDedicatedVmHostInstancesRequest`, `ScalesCache`, `AddRoleToDBClusterCommandInput`, `RequesterAuthorizerWithAirnode`, `MatchRecord`, `AlbumType`, `MessageRequester`, `BuildHandler`, `requests.ListIdpGroupMappingsRequest`, `RollupBlockSubmitter`, `NumberTuple`, `ISession`, `BrowserView`, `KhouryProfCourse`, `GridDimensions`, `UsedNames`, `DescribeUserRequest`, `DescribeTagsRequest`, `UserEmail`, `StrikePrices`, `Models.GameState`, `STDataSourceResult`, `VirtualMachineScaleSet`, `FlatQueryOrderMap`, `PopoverTargetProps`, `JSDocPropertyTag`, `IPipelineOptions`, `DetachedRouteHandle`, `QueueClient`, `MessageToMain`, `SqlPart`, `Buttons`, `TutorialContext`, `LookupStrategy`, `InventoryItem`, `CallbackError`, `AnimationEasing`, `ServiceProperties`, `CIFilter`, `VoiceFocusAudioWorkletNode`, `LinesIterator`, `ts.TextSpan`, `RadixTree`, `PageRoute`, `EndpointBuilder`, `EnumShape`, `Rep`, `JupyterMessage`, `OrganizationDepartmentService`, `VueI18n`, `bluebird`, `PermissionResolvable`, `ArgumentNode`, `IsZeroBalanceFn`, `InvalidPaginationTokenException`, `ComputeManagementClient`, `MethodDescriptor`, `PIXI.Application`, `ProcessApproachEnum`, `TundraBot`, `AttrMutatorConfig`, `IDateGrouper`, `TE.TaskEither`, `ResponsePromise`, `FeatureCatalogueEntry`, `FileExplorerState`, `Angulartics2`, `StaticCardProperties`, `Partial`, `EffectRenderContext`, `IEditorPosition`, `ImageEditorTool`, `OutboundMessage`, `SceneComponent`, `PerfKeeper`, `RequestPausedEvent`, `AggParams`, `SimpleScalarPropertiesCommandInput`, `CommittedFile`, `KeyInfo`, `DataResolver`, `WebMscore`, `MatchPath`, `SelectOutputDir`, `HTMLFormatConfiguration`, `ServerlessResourceConfig`, `TriangleCandidate`, `Lint.WalkContext`, `StartDependencies`, `ASVariable`, `Fork`, `TestRequest`, `MediatorMapper`, `ITag`, `FileDetails`, `DropoutMasks`, `ColumnFilterDescriptor`, `BN`, `AppExtensionService`, `Argument`, `ClientRepresentation`, `ItemTemplate`, `RelatedViews`, `ProblemData`, `CssBlockError`, `MockAddressBookInstance`, `IncomingRegistry`, `Beneficiary`, `InitialState`, `JsonPayload`, `WorkRequestOperationType`, `CreateRoleDto`, `IEventCategory`, `InterfaceImplementation`, `DeleteContext`, `IInitiativeModel`, `GridSprite`, `AlainConfig`, `CatCommonParams`, `DstatementContext`, `Image`, `FormatGraph`, `FieldParamEditorProps`, `MetricDescriptor`, `DOMTokenList`, `ethers.BigNumber`, `Semver`, `Blog`, `Immutable.List`, `EventMapper`, `pxtc.CompileOptions`, `AbstractProject`, `BreakpointFnParam`, `DaffBestSellersReducerState`, `FileSystemTrap`, `NormalizedField`, `EventIded`, `AccountsStore`, `ToggleButtonProps`, `ICardFactory`, `MaxSizeStringBuilder`, `UninterpretedOption_NamePart`, `RecordOptions`, `GetPointTransformerFn`, `IEnumerator`, `QualifierSpec`, `Dirent`, `JestExt`, `MethodCall`, `VulnerabilityReport`, `DirectoryDiffResults`, `SearchSessionDependencies`, `ExtendedGroupElement`, `GenericTwoValuesAndChildren`, `AndroidPerson`, `AsyncIterableExt`, `HostContext`, `DeployedApplication`, `jest.MockedFunction`, `Services.Configuration`, `TocStepItem`, `ModifyDBClusterSnapshotAttributeCommandInput`, `ResourceStatus`, `Ordering`, `TurnTransport`, `HttpPayloadWithStructureCommandInput`, `DetailedCertificate`, `FleetMetricDefinition`, `ContentChange`, `UIAction`, `NowRequest`, `EC.KeyPair`, `StackParameterInfo`, `Ulimit`, `InitializeHandler`, `CCIndicatorSensor`, `InteractionMode`, `MetaInfoDef`, `TextChar`, `Brush`, `ChangeSetType`, `ZoomDestination`, `HsAddDataVectorService`, `FloatTypedArrayConstructor`, `EngineResults.DiagnoseMigrationHistoryOutput`, `FontFeature`, `LoaderAction`, `QueryOrdering`, `PluginFactory`, `ClientConfiguration`, `CreateViewOptions`, `Repositoryish`, `IPC.IFile`, `IMock`, `ComponentTemplate`, `ChemicalDoseState`, `ExpiryMap`, `RuleSetRule`, `WatermarkedType`, `ErrorHandlingService`, `UnsubscribeFn`, `PartyJoin`, `BytesReader`, `YDomain`, `PyrightFileSystem`, `PredictableStepDefinition`, `ListSendersRequest`, `ChildData`, `BusyService`, `PartialVisState`, `TypeProto`, `TextType.StyleAttributes`, `Tiles`, `TileTexSet`, `GPUTexture`, `FakeChain`, `ResFont`, `SdkFunctionWrapper`, `PolygonCollider`, `ListTagsCommandOutput`, `InspectResult`, `ActionParamsType`, `SegmentItem`, `StreamHandler`, `ITracerBenchTraceResult`, `MkFuncHookState`, `UpdateProjectInput`, `LightChannelControl`, `Resolvers`, `LayersModel`, `SqlTuningAdvisorTaskSummaryReportObjectStatFindingSummary`, `AnyObj`, `ExpressionStepDefinition`, `JsonLdDocumentProcessingResult`, `TestProduct`, `CollisionZone`, `ApplyWorkspaceEditParams`, `ListenOptions`, `AngularFireList`, `TInsertAdjacentPositions`, `IBackgroundImageStyles`, `Desktop`, `OrderItem`, `ARMUrlParser`, `PutIntegrationCommandInput`, `IID3v2header`, `IdleState`, `DateInputObject`, `MetricAggTypeConfig`, `NodeDefinition`, `DrawerInitialState`, `Delegate`, `CommandBuffer`, `ColorScheme`, `RobotApiResponseMeta`, `MP.Version`, `IConnectionProfile`, `ResourcePendingMaintenanceActions`, `StringOrNull`, `ILineDiv`, `IqSelect2Item`, `IContextualMenuProps`, `IVarXYValue`, `requests.ListInternetGatewaysRequest`, `Shift`, `ContentBlockNode`, `vscode.TerminalDimensions`, `TIcu`, `NVM500JSON`, `SpheroMini`, `ITokenRefresher`, `GfxProgramP_GL`, `IViewData`, `NavigationPublicPluginStart`, `SolutionBuilderState`, `HoverResults`, `ClassSchema`, `AuthenticationMethodInfo`, `TreeDir`, `HomePublicPlugin`, `HandlerFunction`, `ShortUrlRecord`, `NormalizedEnvironment`, `SharedCLI`, `ConditionsArray`, `NativePath`, `ElementsTable`, `Source`, `SharedTestDef`, `RestClientOptions`, `OAuthError`, `IEnumerable`, `RemoteController`, `CommentNotification`, `UpdateComponentCommandInput`, `LocalizeParser`, `Highland.Stream`, `RuleFailure`, `PortBinding`, `ISample`, `RtkResourceInfo`, `RuntimeTable`, `Vertex`, `Phaser.Math.Vector2`, `ListModelsRequest`, `Electron.OpenDialogOptions`, `WizardTestComponent`, `QueryService`, `SessionChannel`, `SkipBottomButtonProps`, `m.Vnode`, `IRawHealthStateCount`, `ISetLike`, `HasSelectorNodes`, `VirgilPrivateKey`, `PublicIPAddress`, `DropTargetConnector`, `requests.ListInstanceAgentCommandExecutionsRequest`, `helper.PageOptions`, `VaultBackupType`, `SavedObjectsImportError`, `RenderAPI`, `EditableEllipse`, `ThemeTag`, `GetPrismaClientConfig`, `IWorkerContext`, `CategoryCollectionParseContextStub`, `UseConnectResult`, `ContextContributorFactory`, `SpeculativeTypeTracker`, `EntryProcessor`, `IMessageOptions`, `TreeItemComponent`, `OrderbookResponse`, `EditableRectangle`, `core.ScalarOutSpread`, `OrderService`, `RxFormControl`, `DropIdentifier`, `IDataItem`, `IDialogContext`, `InternalPlotConfigObject`, `DeleteQueueCommandInput`, `UnoGenerator`, `lf.schema.TableBuilder`, `requests.ListLoadBalancerHealthsRequest`, `DSOChangeAnalyzer`, `MutableCategorizedStructProperty`, `DefinitionLocations`, `LoadCache`, `mjComponent`, `Globe`, `TSize`, `BasicGraphOnEdges`, `SerializedDatatable`, `Machine`, `ODataEntitySet`, `PutAccountsRequestMessage`, `requests.ListResolversRequest`, `ReadResult`, `PreferenceSchema`, `RunProps`, `Math2D.UvBox`, `LocalUser`, `LexerInterpreter`, `EscapeableMethod`, `TemplatePart`, `Ornaments`, `TokenIterator`, `IObjectOf`, `HTMLLabelElement`, `TagObject`, `AtlasManager`, `TreeDirItem`, `SingleSampledTexture`, `EzBackend`, `InterfaceInternal`, `ListModelDeploymentsRequest`, `Argv`, `CLM.ScoredAction`, `Promotion`, `AnalyticsService`, `ExternalAttributionSources`, `PolicyType`, `ResolveIdResult`, `Register`, `MerkleIntervalTreeNode`, `ServiceAnomalyTimeseries`, `PhysicalLayout`, `Mdast.Link`, `PodDataPoint`, `IData`, `PiPropertyInstance`, `UiSettingsClient`, `SearchExpressionGroup`, `CreateAggConfigParams`, `N2`, `HighContrastModeDetector`, `builder.IEvent`, `ResultPoint`, `Bind`, `ProgramCounter`, `TransformerPayload`, `TrackingData`, `Bass`, `OutgoingMessage`, `Constructor`, `AdminActions`, `RoleOption`, `NoteItem`, `CompressorOptions`, `LoaderData`, `FacepaintStyleSheetObject`, `DirItem`, `InstancesState`, `StorageAdapter`, `ScalarTypeComposer`, `StandardProps`, `MemoExoticComponent`, `TransformLike`, `RadListView`, `PolymerElement`, `NgWalker`, `SearchInWorkspaceResult`, `ContractProgram`, `NativeStackScreenProps`, `SettingsDataProvider`, `PointerPressAction`, `VRMCurveMapper`, `ParenthesizedExpression`, `CsvFormatterStream`, `BoolTerm`, `CraftBlock`, `EmitterManager`, `PartialConfig`, `RealtimeUsersWidgetData`, `PanelConfig`, `IStyleAttr`, `BlockService`, `JsonResult`, `WindowService`, `React.PropsWithChildren`, `TestOptions`, `DomainDropSet`, `VisualizePluginSetupDependencies`, `ConfirmedTransaction`, `ArrayType1D`, `Internal`, `StateHandler`, `WorkflowActivateMode`, `IFormat`, `WhiteBalance`, `IRouterConfig`, `CompressedEmojiData`, `IFormSection`, `StacksPublicKey`, `SelectionService`, `InputObjectTypeDefinitionNode`, `BasePlayer`, `SqlQuery`, `DataModel.RowRegion`, `GUIDestination`, `ProtocolNotificationType0`, `NoteForActivitySetup`, `SiteLicenses`, `ListEnvironmentTemplatesCommandInput`, `IDataFilterValue`, `WhitelistType`, `FullyQualifiedScope`, `StatusService`, `Graph`, `IMaterial`, `FirebaseListObservable`, `StubProvider`, `IsAssign`, `DescribeAccountCommandInput`, `NinjaItemInfo`, `StatementCST`, `FeaturedSessions`, `PlaywrightTestConfig`, `TaskPriority`, `VersionHistoryDataService`, `UseMutationOptions`, `Preview`, `Expectation`, `PrerenderUrlResults`, `FirewallRule`, `GetPromiseInvocationContext`, `DescribeEventsCommandInput`, `ThyTransferDragEvent`, `UrlDrilldown`, `types.UiState`, `NextPageContext`, `ListProfilingGroupsCommandInput`, `ts.DiagnosticCategory`, `LayerEdge`, `QueryCompleteContext`, `size_t`, `RelationsService`, `CompilerOptionsValue`, `IComplexTypeEx`, `EntityWithGroupType`, `DecryptedUserMessage`, `ListFindingsResponse`, `Square`, `OpenAPISchema`, `OperatorFormat`, `CaptionElementProps`, `OptionalRef`, `IBindingTemplate`, `DateSchema`, `QueryParamConfig`, `Routes`, `C2dRenderTexture`, `StandardSchemeParams`, `RegionData`, `RegisteredActionRunner`, `KeyPathList`, `AssetId`, `KernelParams`, `MediaTrackSettings`, `SceneNodeBuilder`, `TraitMap`, `CommandSetting`, `k`, `RegisteredPlugin`, `LookUp`, `MetronomeBeam`, `SimpleRNN`, `TabbedRangeFilterParams`, `Probe`, `freedom.Social.ClientState`, `AuthDispatch`, `DOMHandlerScope`, `ContractMetadata`, `PointCloudMaterial`, `PlacementTypes`, `schema.Context`, `NotificationBarService`, `AppearanceCharacteristics`, `LoginPayload`, `UpSetProps`, `JsonLocations`, `ListConnectionsCommandInput`, `RLAN`, `ArrowHelper`, `TestFunction`, `ConnectionMessage`, `IAmazonS3Credentials`, `CmdType`, `JobAgent`, `DescribeLoadBalancersCommandInput`, `Preprocessor`, `Path1`, `PatternRecognizer`, `PersistedStatePath`, `DragDropProviderCore`, `FieldValidationResult`, `ProjectInput`, `ChainableElement`, `EditorWidget`, `AddFriendsRequest`, `HttpServer`, `DomainData`, `ActivityDefinition`, `StreamDescription`, `ITextureInfo`, `DocumentManager`, `FieldToMatch`, `GetImportJobCommandInput`, `ExprVisState`, `BlockChainUser`, `HTMLDetailsElement`, `SeriesChanges`, `InternalGroup`, `MockClientFactory`, `WasmResultValues`, `SecurityRequestHandlerContext`, `ItemOptions`, `ApiErrorReporter`, `HashParams`, `IRpoToken`, `TypeKind`, `HistoryNodeEvent`, `TileInfo`, `NbToastrService`, `GltfNode`, `Point`, `ConflictType`, `GestureEventData`, `CreateTokenAccount`, `android.content.Intent`, `EntityColumnDef`, `GetUserData`, `HsDialogItem`, `IAccordionItemContextProps`, `OrganizationSet`, `AzureConfigs`, `GetSymbolAccessibilityDiagnostic`, `OnEvent`, `PriceOracle`, `UntagResourceInput`, `PrismaClient`, `ICountryModel`, `ReaderConfig`, `Group`, `ActionFilter`, `ParametersPositionContext`, `InternalProps`, `CustomOkResponse`, `JsonIdentityInfoOptions`, `Events.postcollision`, `SaveEntities`, `ts.WriteFileCallback`, `MethodDetails`, `CamelElement`, `IModelConnection`, `ControlOptions`, `IPivotItemProps`, `NodesInfo`, `ConnectedWallet`, `IFormInput`, `ParameterInformation`, `ModelRenderer`, `SamlRegisteredService`, `AngularFireFunctions`, `W1`, `GunGraphAdapter`, `program.Command`, `RedPiece`, `DataOption`, `DeleteNamespaceCommandInput`, `GossipMemoryStore`, `ProjectLabelInfo`, `Viewport_t`, `BaseExecutor`, `StackDescriptor`, `ProjectExtentsClipDecoration`, `LicenseSubs`, `CacheKeys`, `FullRequestParams`, `Inhibitor`, `DescribeDBClusterSnapshotAttributesCommandInput`, `BoneDesc`, `Lru`, `PutResourcePolicyRequest`, `ViteDevServer`, `RequireFields`, `d.BundleModule`, `JoinDescriptor`, `BatchCheckLayerAvailabilityCommandInput`, `MockCachedRule`, `ErrorState`, `ShareMap`, `InterfaceDeclarationStructure`, `StateChange`, `TStylingContext`, `Declaration`, `UseSavedQueriesReturn`, `IRootState`, `GraphService`, `IpcRendererEvent`, `TypesStart`, `CombatantState`, `IReader`, `Knuckle`, `DataReader`, `TokenState`, `BsModalRef`, `ConnectionSetting`, `MatOpM`, `ShaderRegisterElement`, `TSObj`, `ICXOrder`, `TouchMouseEvent`, `ODataUri`, `cdk.App`, `ModelTypes`, `UInt32`, `TimePickerState`, `SimpleToastCreator`, `ApolloTestingController`, `AuthProps`, `Bean`, `MockRouter`, `PDFPageEmbedder`, `RegSuitConfiguration`, `CloudWatchDimensionConfiguration`, `IOrganizationSprint`, `DataSnapshot`, `IComponentName`, `IAmazonClassicLoadBalancerUpsertCommand`, `XRSession`, `RestorePoint`, `ISelectionId`, `MetadataProperty`, `StageRuntimeContext`, `GanttSettings`, `SubscriptionTracker`, `UpdateGroupRequest`, `Uri`, `MediaProviderConfig`, `MessageProps`, `WebSettings`, `PropertiesField`, `TreeNode2`, `Truncate`, `ScannerState`, `CreateCrossAppClickHandlerOptions`, `WechatSettingService`, `HeaderComponent`, `requests.ListTsigKeysRequest`, `LayoutDefaultHeaderItemComponent`, `DeleteExpression`, `CommonSelectedNode`, `APIClient`, `IEventFunction`, `GraphIIP`, `TestHost`, `CategoryCollectionParserType`, `TreeviewComponent`, `PlotArea`, `IAppContext`, `SessionConnection`, `SalesLayoutState`, `HttpRequestOptions`, `GlobalVarsService`, `BleepsGenerics`, `NavigatableWidget`, `EntityNameOrEntityNameExpression`, `PerspectiveCamera`, `ChartJSNodeCanvas`, `ServiceNowActionConnector`, `IAuthStrategy`, `WorkerPoolResource`, `HealEvent`, `SupCore.Data.Schema`, `PedalTuning`, `fromAuthActions.Login`, `HsEventBusService`, `SemanticTokensParams`, `SolutionToApiAnalysis`, `AngularPackage`, `ArrayBuffer`, `GfxrGraphBuilder`, `BadRequestException`, `ModuleNameNode`, `PortalType`, `StreamResponse`, `SetContextLink`, `MemoryPages`, `BookmarkChange`, `CreateStackCommandInput`, `FileScan`, `IFiber`, `ICondition`, `CronProcessTable`, `CanaryExecutionRequest`, `TransactionSkeletonType`, `MovingDirection`, `SceneObjHolder`, `ComponentFileItem`, `TestType`, `BitstreamDataService`, `GenerateFn`, `IGitApi`, `HistoryResponse`, `TextPathGeometry`, `MaxPooling1D`, `ExtractDto`, `NumberFormat`, `APIConfig`, `Slugifier`, `protocol.Message`, `DestinationAuthToken`, `CoreContext`, `MappedPosition`, `ODataModelField`, `Ivl`, `TestFunctionImportEdmReturnTypeCollectionParameters`, `AssetPropertyTimestamp`, `AirtableBase`, `AccountImplement`, `Combinator`, `UInt160`, `TypeDetails`, `HeadingProps`, `DataSeriesDatum`, `PathRef`, `ICardEpisode`, `ReadonlyArray`, `core.BTCAccountPath`, `IScreen`, `Survey.Operand`, `Store`, `FIRStorageTaskSnapshot`, `SignOptions`, `ChartWidget`, `IncludedBlock`, `OpType`, `IContext`, `CustomNestedProps`, `PubArt`, `ModuleDefinition`, `PromiseSocket`, `TranslationSettings`, `HttpStatusCodes`, `SavedVisualizationsLoader`, `SFUISchemaItem`, `PassportStatic`, `DeviceService`, `ProductService`, `TextAreaComponent`, `TNodeReturnValue`, `LoggingConfigType`, `MyEvent`, `MetalsTreeViewNode`, `ResolvablePromise`, `EvmContext`, `PaymentInfo`, `InputSettings`, `RollupWarning`, `FkQuadTree`, `TestFolder`, `Filesystem`, `SnackbarKey`, `DescribeEndpointsCommandInput`, `ResourceArguments`, `CaretOptions`, `StaffLayout`, `DecorationFileMap`, `ECharts`, `IConnectionFormState`, `Evt`, `LinkObject`, `UsbDevice`, `IsometricPoint`, `SecurityReport`, `SpeechServiceConfig`, `NotificationTemplateEntity`, `IDrawOption`, `LikeEntity`, `InspectorViewDescription`, `TemplRef`, `ComponentService`, `AccessKey`, `SelectionModel.Selection`, `AVRIOPort`, `yargs.Arguments`, `DataViewCustom`, `ProjectColumn`, `SavedObjectsImportFailure`, `StorageImpl`, `SMTMaskConstruct`, `TryStatement`, `IPlDocObject`, `PhraseFilterValue`, `Prisma.Sql`, `UsersActionType`, `Matrix`, `ITooltipProps`, `PlaybackSettings`, `AnyBody`, `IFeature`, `InternalHandler`, `Servient`, `TemplateSummary`, `NibbleDisk`, `DataItem`, `Progression`, `ExtendedType`, `IQueryBuilderPart`, `oke.ContainerEngineClient`, `SdkSignalFrame`, `DebugProtocol.OutputEvent`, `DebugProtocol.Source`, `ScopedLabel`, `DecoratorConfig`, `ICategory`, `NationalTeam`, `TokenSource`, `Cypress.Response`, `requests.ListSecretVersionsRequest`, `AggTypeFieldFilter`, `FieldToValueMap`, `DelayNode`, `UsageSummary`, `MonitoredItem`, `DeleteImageCommandInput`, `SavedObjectUnsanitizedDoc`, `ScullyRoute`, `CalculateBoundsFn`, `ActivePoint`, `SqlObject`, `SymbolKey`, `AuxChannelData`, `BundleModuleOutput`, `DescribeCodeBindingCommandInput`, `VdmFunctionImport`, `TupleAssignmentContext`, `DocumentDelta`, `CreateTokenCommandInput`, `ClanStateService`, `IAnalysisState`, `NumberDraggerSeg`, `JsonFormsState`, `AsyncLocalStorage`, `StateProvider`, `SolanaNetwork`, `BeatUnitDot`, `SRT0_MatData`, `vscode.ConfigurationChangeEvent`, `d.OptimizeCssInput`, `U`, `VersionStage`, `IBlockchain`, `FolderItem`, `ScrollInfo`, `UniversalRouterSync`, `TT.Tutorial`, `Stream`, `TupletDot`, `TestContracts`, `ReferenceContext`, `IFileTreeItem`, `Field_Ordinal`, `ParticipantSubscriber`, `H264RtpPayload`, `AuthModeChanged`, `CompilerAssetDir`, `ApplicationRepository`, `TextureFetcher`, `DmChannelDTO`, `jasmine.Spy`, `IServerOptions`, `UserFunctionNamespaceDefinition`, `JSON_PayloadInMask`, `PrismaClientRustErrorArgs`, `StartQueryCommandInput`, `IDBAccessQueryParams`, `DiscordBridgeConfig`, `PerformListFilesArgs`, `GfxQueryPoolP_GL`, `GoStoneGroup`, `ResolvedConnection`, `ListConfigurationsCommandInput`, `AndroidChannel`, `SchemaToArbitrary`, `GherkinException`, `AllFile`, `VideoModel`, `child_process.ChildProcess`, `BaseVisTypeOptions`, `VAStepData`, `NotifyPlacement`, `ButtonColor`, `TResult`, `UserFunctionDefinition`, `PairSide`, `TemplateTag`, `ChartSpecPage`, `HttpEvent`, `SubjectDataSetColumn`, `WorkRequestWaiter`, `MetricType`, `GetMasterAccountCommandInput`, `CreateJobCommandInput`, `InferenceInfo`, `UserInput`, `TooltipValue`, `MenuSection`, `ApisTreeItem`, `LocalOptionsMap`, `MockBaseElement`, `RedirectResult`, `Ecies`, `WebAppRuntimeSettings`, `ts.LabeledStatement`, `AlterTableBuilder`, `ZipResource`, `NameType`, `ExpirableKeyV1`, `IBaseView`, `ReactChild`, `eui.Image`, `MarkSizeOptions`, `Fill`, `Mute`, `BlockMap`, `SelectorCore`, `MobileRpcChunks`, `TypingIndicatorReceivedEvent`, `CancellablePromise`, `SerializeErrors`, `marked.Renderer`, `MockCall`, `MnemonicLanguages`, `AbsoluteDirPath`, `ScaleMap`, `UpdateUserResponse`, `IterableChanges`, `ChannelFactoryRegistry`, `Perm`, `V1DaemonSet`, `Calendar_Contracts.IEventSource`, `SymbolAccessibilityDiagnostic`, `SourceControlResourceState`, `JsonDocsSlot`, `WalletError`, `TestStep`, `ElmExpr`, `ShorthandFieldMapObject`, `AnalyticSegment`, `Q.Deferred`, `SourceFileInfo`, `IPropertyValueDescriptor`, `YBasicSeriesSpec`, `WorkItemTypeUI`, `User.Type`, `GuideType`, `ComponentTestingConstructor`, `WordStorage`, `ViewUpdate`, `Toolbox`, `CrochetType`, `BTreeNode`, `DocView`, `OrgInfo`, `GetText`, `ModuleResolutionKind`, `estree.Node`, `EncodeOptions`, `EventAccumulator`, `FileOutput`, `PointCloudHit`, `ConversationState`, `MilestoneActivity`, `Polyface`, `LoggerFormat`, `AuthenticateFacebookInstantGameRequest`, `ValidatedPurchase`, `Persistor`, `FuncMode`, `CachedTileLayer`, `BreadcrumbItemType`, `PathReference`, `WebSocketClient`, `ApplicationStart`, `ShaderParam`, `TestScriptResult`, `FileDefinition`, `IContextMenuItem`, `Beam`, `BranchDataCollection`, `DefaultDataService`, `ResponseError`, `TaskFn`, `InteriorNode`, `TExtra`, `New`, `TernaryNode`, `IPosition`, `SpecializedFunctionTypes`, `LabelDefinitionJSON`, `tmrm.TaskMockRunner`, `ChatItemSet`, `AssignmentCopyStep`, `AppRedux`, `KeyRingStore`, `DataFileType`, `SfdxCommandDefinition`, `CustomDecorator`, `VisualizationChartProps`, `EntriesArray`, `HsdsEntity`, `ModuleDatafeed`, `GraphEdge`, `GetDeprecationsContext`, `ApexTestNode`, `Predicate`, `TemplateHandlers`, `KeyofC`, `HeaderColumnChainRow`, `NextApiRes`, `WalkerDown`, `Z64SkeletonHeader`, `VersionNumbers`, `RoverInitialState`, `DeeplyMocked`, `CdkDragEnter`, `requests.ListConnectHarnessesRequest`, `IEffect`, `LabelValue`, `PSIDataType`, `Sema`, `QueryFormColumn`, `PackageId`, `DSlash`, `YConfig`, `Bytecode`, `EnvValue`, `Dependency`, `BuiltAction`, `IntrospectionEngineOptions`, `NavigatorParams`, `MemoryArray`, `GetUserSettingsCommandInput`, `ConfirmationService`, `PluginEditorProps`, `SegmentRef`, `CandleData`, `RequiredFieldError`, `ApiRoute`, `StyledButtonProps`, `DescribeEventsMessage`, `ItemType`, `ThreadID`, `RevisionValueCache`, `CppCbToNew`, `DeliveryDetails`, `BreakpointObserver`, `QueryFormData`, `IndexedDB`, `InputInfo`, `TicTacToeGameState`, `CollisionContact`, `InternalProvider`, `PluginPageContext`, `Node_Interface`, `ListApplicationsCommandOutput`, `TransactionReceiptTruffle`, `ReplacementRule`, `ParamsOptions`, `EntityUpdate`, `TransferItemOption`, `FastifyError`, `IStorageLayer`, `EmptyInputAndEmptyOutputCommandInput`, `Fanduel`, `InterfaceWithThis`, `DoubleValue`, `OpenApi.Document`, `VectorList`, `d.BuildSourceGraph`, `CancellationStrategy`, `InputPort`, `CommandCreatorError`, `DirectBuy`, `ObjectModel`, `IHawkularAlertRouterManager`, `SimpleNode`, `Heap`, `DaLayoutService`, `DnsValidatedCertificate`, `ILinkProps`, `core.ETHAccountPath`, `KibanaResponse`, `SpecRoleCapabilities`, `IAbortAblePromise`, `LoginAccountsRequestMessage`, `OrganizationMemberType`, `ProgressConfig`, `IBalanceValue`, `MutationObserverInit`, `MeshSprite3D`, `StartPipelineExecutionCommandInput`, `IDistributionDelta`, `JsonFragment`, `ConnectionInformations`, `FortuneOptions`, `BufferId`, `Lambda`, `ComponentClass`, `ODataSingletonResource`, `IValidationResponse`, `Chip`, `TableClient`, `ExportDefaultDeclaration`, `RemoteInfo`, `IMessageValidator`, `FormReturn`, `GenerationStatus`, `GetAppDefinitionParams`, `DiffFile`, `FeatureID`, `ReactComponent`, `Airline`, `MonacoEditorService`, `PouchDBFileSystem`, `NotFound`, `Array4`, `FormlyDesignerConfig`, `RouteValidator`, `MessageError`, `ListPresetsCommandInput`, `QueryWithHelpers`, `Matrix2`, `At`, `CouncilData`, `OnDemandPageScanResult`, `GunGraphData`, `ProductSearchParams`, `core.ITenantManager`, `SubscribableEditionComboboxItemDto`, `TSIf`, `IAbstractControl`, `SerializableMap`, `InternalDatasource`, `CodeMirror.Editor`, `RangeFilterParams`, `IPageData`, `Hook`, `GetDeploymentsCommandInput`, `NelderMeadPointArray`, `webpack.Configuration`, `SpriteData`, `ParsedMessage`, `WriterContext`, `BufferView`, `AllAccessorDeclarations`, `RectAnnotationSpec`, `ProjectorPerformanceLogger`, `TextProperties`, `NodeRef`, `IndexPatternSelectProps`, `BehaviorObservable`, `NgbPanelChangeEvent`, `BlinnPhongMaterial`, `RangeSelectorOptions`, `AbstractDistanceCalculator`, `AlertData`, `ModelProps`, `ICommon`, `QueryPayload`, `LaunchTemplateOverrides`, `CellSelection`, `ConceptConstraint`, `Setdown`, `IShellMessage`, `Composable`, `InstantiableRule`, `MaterialSet`, `ReservedIP`, `CommandEvent`, `Swizzle`, `RefService`, `FileDeclaration`, `_ZonePrivate`, `GeoJSON`, `AreaChartOptions`, `AlertAction`, `SqlTaggedTemplate`, `QuestionModel`, `DappRequest`, `MessagePayload`, `AuthenticationName`, `IJumpPosition`, `ChannelType`, `FieldVisitor`, `NzFormatEmitEvent`, `AttributionInfo`, `ServiceImplementations`, `NSData`, `MEMBER_FLAGS`, `JsonAstNode`, `DeleteSnapshotCommandInput`, `GameBase`, `Pagerank`, `DiagnosticMessage`, `Other`, `TEAttr`, `TSBreak`, `CacheItem`, `HistoryTreeItem`, `IRequestInfo`, `AnalysisResults`, `SavedObjectsMigrationVersion`, `CliqueVote`, `Project.ID`, `DhcpOption`, `ActivatedRouteSnapshot`, `CommandExecution`, `AggConfigSerialized`, `VideoDescription`, `SchemaValidatorFactory`, `DeviceType`, `StateIO`, `IOptimizeOptions`, `TypeScriptEmitter`, `ITransUnit`, `ConfigTypes.CFWorkers`, `BucketMetadataWithThreads`, `ConceptDb`, `ContractState`, `FSFile`, `ProfileStateModel`, `FaunaIndexOptions`, `SimpleReloaderPlugin`, `Notes_Contracts.Note`, `IReduxAction`, `EnvironmentOptions`, `RelationExt`, `ValuePaddingProvider`, `TDiscord.Guild`, `AuthorizeParamsDto`, `BookSavedObjectAttributes`, `XmlStateConsumer`, `UpdateValueExpression`, `DataValidationCxt`, `NoteSnippetEditorRef`, `IApplicationState`, `DbStxLockEvent`, `requests.UpdateProjectRequest`, `SkeletonField`, `CompositeDisposible`, `QueryCommandInput`, `IGDILogger`, `Vector3Keyframe`, `ExchangeOptions`, `$G.IGraph`, `interfaces.BindingInWhenOnSyntax`, `Key2`, `IFormValues`, `IFrameHeader`, `EmailConfirmationValidator`, `JSExcel`, `ts.FileWatcher`, `StructDef`, `ArrayServiceArrToTreeNodeOptions`, `EventArgs`, `PiTypeDefinition`, `Enumerator`, `NodeJS.Process`, `HsAddDataCommonService`, `SfxData`, `CommandArgument`, `ts.Expression`, `HitsCounterProps`, `IconifyIconCustomisations`, `MemberData`, `RTCStatsReport`, `DisLabel`, `FileTextChanges`, `RequestConfig`, `Trait`, `Words`, `GetAccountCommandInput`, `ListingMeta`, `SafeTransaction`, `PathAndContent`, `BranchFlagStm`, `WebElementWrapper`, `ConnectDetails`, `OperationDetails`, `Decoration`, `MessageWithoutId`, `BeforeCaseCallback`, `CLM.TextVariation`, `StoreNode`, `IReducer`, `IsoLayer`, `DinoController`, `DeleteEndpointCommandInput`, `requests.ListPoliciesRequest`, `tf.Tensor1D`, `TemplateFunction`, `TPackage`, `dia.Link`, `ResourceHelper`, `path.ParsedPath`, `TransientState`, `TInjector`, `GetGeneratorOptions`, `DeleteVpcPeeringConnectionCommandInput`, `NetworkContext`, `RBNFNode`, `ImageRequest`, `Version`, `egret.Event`, `JUser`, `GClient`, `CdsControlMessage`, `UST`, `EVMPayload`, `RawGraphData`, `Vector2`, `PlanetInfo`, `ResolverRpCb`, `objectPointer`, `AmongUsSession`, `ColorSwitchCCStartLevelChange`, `sdk.LanguageUnderstandingModel`, `RumConfiguration`, `Rx.Observer`, `Yendor.TickResultEnum`, `IUserDetails`, `ReaderPage`, `Padding`, `AccordionComponent`, `ReplayableAudioNode`, `IModuleMap`, `MessageRepository`, `IUserRequestOptions`, `MIRArgument`, `UsePaginationModelConfig`, `ResponseParams`, `ITransformerHandleStyle`, `IParticipant`, `VersionOperatorContext`, `GraphQLSchemaWithFragmentReplacements`, `TableDataProvider`, `BlokContainerUserSettings`, `EzBackendOpts`, `TEmoji`, `WaitForSelectorOptions`, `fhir.Identifier`, `ActionInterval`, `vile.Issue`, `AppWithCounterState`, `UserInputPlugin`, `ScopeableRequest`, `Sid`, `FixtureContext`, `Matrix4d`, `IRuntimePosition`, `LoadingBarsEffectsRefs`, `ITemplate`, `PollerLike`, `ValueHandler`, `anchor.web3.Connection`, `HarmajaStaticOutput`, `Touched`, `TInput`, `ExtOptions`, `EntityActionParam`, `ShaderParams`, `LogFunction`, `ParameterValueDefinition`, `IArguments`, `SingleASTNode`, `ConvertService`, `GanttDate`, `CommandClient`, `IFactory`, `Timeline`, `TargetRange`, `PkgConflictError`, `SetIconMode`, `BoxCache`, `Relationships`, `IUserDocument`, `MutationFunction`, `MessageHeaders`, `ListTagsRequest`, `StagePanelSection`, `ColorGradient`, `SupabaseClient`, `MDCAlertAction`, `UpdateDependenciesParams`, `RectModel`, `requests.ListAutonomousContainerDatabaseDataguardAssociationsRequest`, `ThroughputSettingsUpdateParameters`, `B13`, `ToastParams`, `SecretVersion`, `NavService`, `TimeScale`, `EventTypeService`, `serialization.ConfigDictValue`, `ListRequest`, `Sphere`, `AggregationMode`, `parse5.ASTNode`, `UserStorage`, `IManifestArmor`, `InfuraProvider`, `Identification`, `DeepLink`, `_DeepPartialObject`, `TooltipPayload`, `SourceConfiguration`, `CSTeamNum`, `ts.AsExpression`, `SVGGraphicsElement`, `ImageState`, `TangentType`, `NcTabs`, `BitGo`, `MatBottomSheet`, `ParameterCategory`, `AliasMapItem`, `IAGServer`, `PublishDiagnosticsParams`, `EventCreatorFn`, `QTMCounterState`, `SuccessfulMatchReport`, `CobIdentifier`, `UserSession`, `ContextTransformFieldType`, `IColumnToolPanel`, `StitchesComponentWithAutoCompleteForReactComponents`, `d.RollupChunkResult`, `IFieldSchema`, `ComponentLocale`, `BooksState`, `AudioPlayerState`, `Public`, `NavControllerBase`, `TransmartStudy`, `IStorage`, `ConversationNode`, `StorageFile`, `OrbitTransformation`, `CalendarRepository`, `AddressHashMode.SerializeP2SH`, `InboundTransport`, `CrawlContext`, `SubscriptionObserver`, `ResStatus`, `RSSI`, `RRNode`, `FindConditions`, `ApprovalPolicy`, `MDCLineRippleFoundation`, `CreateAuthorizerCommandInput`, `EvaluationResult`, `RenderBufferTargetEnum`, `DecryptedSymmetricKey`, `MentorBasic`, `EventArg`, `IUnitStoryChapter`, `ObservableMap`, `DMMF.SchemaEnum`, `FaceNameSwizzler`, `GitHubClient`, `Hour`, `UserChallengeData`, `CryptoFrame`, `VectorType`, `CreateContactCommandInput`, `LuaSymbolInformation`, `Achievement`, `Lazy`, `CreateDeploymentCommandInput`, `Password`, `CaseInsensitiveMap`, `DestinyCacheService`, `PackedBubblePoint`, `TSESLint.RuleModule`, `Ingredient`, `ListSortMembersSyntax`, `ElementResult`, `ObjectButNotFunction`, `IArgs`, `DecodedPixelMapTransaction`, `CoreUsageStatsClient`, `IndexedGeometryMap`, `SpawnASyncReturns`, `FolderService`, `Invoice`, `Pixels`, `ChoicesEntity`, `ListOpsInfo`, `IExpectedIdToken`, `DataCenterResource`, `CategoryMap`, `RPCConnection`, `ResolvedPointer`, `ColorScale`, `PackageSummary`, `EmitContext`, `MarkupElement`, `InterpolateData`, `TranslationFile`, `UploadApiResponse`, `TranslationKeys`, `PatchOperation`, `NgGridItem`, `AtomicMarketNamespace`, `DiagnosticResult`, `CollisionCategorizedKeeper`, `ColorFunc`, `HR`, `AnalyserNode`, `ts.TypeParameterDeclaration`, `IssueLocation`, `LambdaContext`, `ARMRamItem`, `ResponseWithBodyType`, `PanelNotificationsAction`, `Trail`, `RequestedServiceQuotaChange`, `GraphQLInputField`, `PointerAllocationResult`, `PackagePolicy`, `CLM.TrainScorerStep`, `SdkAudioStreamIdInfoFrame`, `MicroAppConfig`, `ApiCall`, `protocol.FileLocationOrRangeRequestArgs`, `PackageJsonWithTsdConfig`, `ModifyDBInstanceCommandInput`, `Junction`, `UiSettingsParams`, `ODataService`, `AddGatewayV1`, `JobValidationMessage`, `AccessTokenResponse`, `AbortChunk`, `ValueOptions`, `RawLogEvent`, `HomeComponent`, `WalletPage`, `CloudTasksClient`, `FieldResultSettingObject`, `HighlightData`, `StorageConfig`, `TxOptions`, `GetZoneRecordsRequest`, `ColumnWorkItemState`, `StringifiedUtil`, `WebTally`, `EmitTextWriterWithSymbolWriter`, `VueFile`, `CreateEndpointCommandInput`, `AirlineEffects`, `OrthographicCamera`, `IArticleField`, `MessageGroup`, `Manipulator`, `UISliceState`, `ExpandedArgument`, `TaskDraftService`, `FilterDataStatusValues`, `CompletionRecord`, `HandledEvent`, `CommonTableExpressionNode`, `Bank`, `CreateDBSubnetGroupCommandInput`, `SearchInputProps`, `SnapshotListenOptions`, `ReconnectDisplay`, `DockerRegistryHelper`, `ParamT`, `ChainJson`, `PnpmShrinkwrapFile`, `IMergeViewDiffChunk`, `StorageManager`, `DiffCopyMessage`, `Datastore.Context`, `CDJStatus.State`, `AddressData`, `SavedToken`, `ServerListEntry`, `ChordType`, `TypeOperatorNode`, `ChartDownload`, `ActionFilterAsync`, `DefaultRollupStateMachine`, `IntlShape`, `ButtonType`, `PreRenderedChunk`, `ExpressionReturnResult`, `DeleteConfigurationSetEventDestinationCommandInput`, `Knex.TableBuilder`, `ScaleLinear`, `ContainerBase`, `BuiltQuery`, `IComm`, `WrappedStep`, `MDCChipAdapter`, `IsNot`, `SecureRandom`, `RaycasterEmitEvent`, `requests.ListBootVolumeBackupsRequest`, `vscode.CancellationTokenSource`, `CodeBlockProps`, `ElementSession`, `AxisLabelFormatter`, `ApplyResult`, `EmulateConfig`, `IPlatformService`, `ts.ParseConfigFileHost`, `SHA384`, `avcSample`, `ReputationOptions`, `preValidationHookHandler`, `fs.Dirent`, `ISceneActor`, `ObjectiveModel`, `GEvent`, `CarouselInternalState`, `LinearSweep`, `ProColumns`, `TextEditorHelperReturnType`, `UserState`, `Moment`, `DeleteFileOptions`, `snowflake`, `MdcIconRegistry`, `IntervalType`, `EzBackendInstance`, `CommandClass`, `SuccessCallbackResult`, `DateTime`, `TestSet`, `Identify`, `OUTPUT_FORMAT`, `TensorData`, `PropertyAst`, `BlurState`, `TabBar`, `AddTagsCommandInput`, `IInventoryArmor`, `DaffCartCouponFactory`, `CmsModelFieldToElasticsearchPlugin`, `EncryptionError`, `Ray3`, `OneListing`, `PreloadData`, `ExecuteStatementCommandInput`, `ServerSecureChannelLayer`, `Salt`, `MapIncident`, `ReportingCore`, `DomainEntity`, `CreatePostInput`, `NSV`, `AtomFamily`, `SnapshotOrInstance`, `VariableDeclarationList`, `CreateFieldResolverInfo`, `SeriesUrl`, `CodeLens`, `Operator.fλ.Stateless`, `CompassCardConfig`, `RelativeTimeFormat`, `IFunctionCall`, `XPCOM.nsXPCComponents_Results`, `InterceptorOptions`, `StorefrontApiModule`, `MatchReport`, `ConfigSource`, `UnpackOptions`, `SimpleObjectRenderer`, `WidgetZoneId`, `SigningRequest`, `Defaults`, `ResponderRecipeResponderRule`, `RadioChangeEvent`, `aws.iam.Role`, `CommandLineBinding`, `DragSourceSpec`, `SelectPlayer`, `TextureDataFloat`, `HttpRes`, `TaskLifecycleEvent`, `TCallback`, `StopWatch`, `ApigatewayMetricChange`, `ODataEntityResource`, `DAL.DEVICE_ID_RADIO`, `ColumnProperty`, `RepoClient`, `DiagnosticBuffer`, `CheckPointObject`, `WesterosCard`, `ClearingHouseUser`, `UnsignedContractDeployOptions`, `comparator`, `QuickPickStep`, `ITimeline`, `Function1`, `IgnoreMatcher`, `ProtocolType`, `TextDocumentPositionParams`, `ArgumentCategory`, `TestProps`, `NewTorrentOptions`, `JPAC`, `OptionsInit`, `RowBox`, `PrinterOptions`, `DirectiveHarvest`, `WorkerMeta`, `Extend`, `RenderDebugInfo`, `CSSResult`, `next.SketchLayer`, `PddlExtensionContext`, `RectGeometry`, `IStorageOperationModel`, `GetDomainStatisticsReportCommandInput`, `SideEntityController`, `HTMLPreviewManager`, `HeatmapSpec`, `UserObjectParam`, `Biquad`, `IOptionsObj`, `SolarWeek`, `SingleProvider`, `TextOptions`, `ValidatorBuilder`, `GestureStateChangeEvent`, `LineSegment`, `DecodedInstruction`, `PointAttribute`, `Logging`, `OverlayPositionBuilder`, `BuildEnv`, `TAG_SIZE`, `EVCb`, `SimpleChanges`, `PayoutNumeratorValue`, `AuthenticationExecutionInfoRepresentation`, `ResourcesWithAttributedChildren`, `QueryAuditorAttributesRequest`, `FollowLinkConfig`, `TernarySearchTree`, `SignDoc`, `BaseTexture`, `RowTransformFunction`, `ObjectFlags`, `DimensionGroup`, `NetworkingState`, `TextElementsRendererOptions`, `MdlOptionComponent`, `SecuritySchemeObject`, `TimechartHeaderProps`, `KeyboardShortcut`, `TweetTextToken`, `WatchableFunctionLogic`, `ReactFragment`, `TypeToMock`, `BespokeServer`, `CustomersGroupState`, `core.ETHSignMessage`, `QueueReceiveMessageResponse`, `AuthReduxState`, `FlipDirection`, `MetricRegistry`, `VNodeProps`, `StateNode`, `ResolvedAtomType`, `Transpiler`, `Preposition`, `DynamoDBDocumentClientResolvedConfig`, `GroupList`, `HTTPResponseBody`, `PoxInfo`, `IDatePickerModifiers`, `VerticalPlacement`, `TaskResolver`, `SoftmaxLayerArgs`, `requests.ListWorkRequestErrorsRequest`, `Feeder`, `OperandType`, `DockerGlobalOptions`, `IApiResponse`, `ContractCallOptions`, `SelectEvent`, `CheckSimple`, `DeleteQueryNode`, `JhiAlertService`, `Phaser`, `_Identifiers`, `BroadcastEvent`, `LegacyResult`, `UsersState`, `UAObject`, `IHWKeyState`, `IVehicle`, `SetElemOverlap`, `ThyUploaderConfig`, `OutputEntry`, `SerializableRecord`, `BatchCreateChannelMembershipCommandInput`, `Rule.RuleFixer`, `ComponentsProps`, `fromSettingsActions.GetSettingModelCollection`, `TruncatablesState`, `TextureCoordinateType`, `TsConfigResolver`, `FragmentDefinitionMap`, `SVGDatum`, `BrickRenderOptions`, `DatabaseParameterSummary`, `MenuAction`, `FunctionAddInfo`, `CreateUserCommandInput`, `InputTree`, `ITransactionProps`, `Alt1`, `ReferenceParams`, `ComponentManager`, `UserActions`, `CompositeName`, `AppiumClient`, `AuthenticateEmailRequest`, `LiteColliderShape`, `LayerSpec`, `PackedTag`, `ParsedFileContent`, `SwaggerMetadata`, `ListResponse`, `ShaderSpec`, `ChangelogEntry`, `MaterialFactory`, `ExternalService`, `FolderView`, `RepoService`, `IListenerRule`, `HallMenus`, `ExpressionKind`, `StatsFieldConfiguration`, `IFeatureOrganizationUpdateInput`, `TAggregateCommit`, `InternalViewRef`, `Specialty`, `AddedKeywordDefinition`, `ApiClientResponse`, `ColumnModelInterface`, `StacksPrivateKey`, `DescribeDBClusterParameterGroupsCommandInput`, `StepperProps`, `SceneActuatorConfigurationCCSet`, `DynamicFormService`, `NotificationEntity`, `ContentTypeService`, `GeneratedFiles`, `ICandidateInterview`, `PerformanceEntry`, `ATOM`, `ResourcesToAttributions`, `IPagingTableState`, `SelectorNode`, `AuthContextProps`, `PrivilegeCollection`, `StateAB`, `TranscriptEvent`, `ReadonlyMat4`, `BasePin`, `ArianeeWalletBuilder`, `TimePanelProps`, `WithPLP`, `OptionalFindOptions`, `IPersonState`, `ButtonVariant`, `ExpressionFunctionDefinition`, `HlsEncryption`, `HiNGConfig`, `UiAtomType`, `TagProps`, `PageMetadata`, `WebCryptoDefaultCryptographicMaterialsManager`, `PipelineStageUnit`, `DeleteDataSourceCommandInput`, `DecodedTile`, `ResourceType`, `QueryParamsAsStringListMapCommandInput`, `uint8`, `GX.IndTexWrap`, `TLndConf`, `BoardSettings`, `RouterStateData`, `CategoryPreferences`, `Hmac`, `UpdateResourceCommandInput`, `DocumentInitialProps`, `TestingConfig`, `Realm.Object`, `MdcElementObserverAdapter`, `FileTreeComponent`, `INodeDetailResolverService`, `ShimFactory`, `Scrobble`, `CSSStyleSheet`, `SyncGroup`, `DebugProtocol.ConfigurationDoneArguments`, `vscode.TestRun`, `StickerExtT`, `PrivateDnsZoneGroup`, `InstallTypes`, `RgbTuple`, `GX.AlphaOp`, `RowOutlet`, `ResolverFn`, `AnimationTrackComponent`, `SlopeWallet`, `ECSSystem`, `EntityStore`, `CanvasFillRule`, `ArgOptions`, `EventPriority`, `UserSubscriptions`, `is_pressedI`, `AngularFirestoreDocument`, `ExtendFieldContext`, `TRawConfig`, `MapItem`, `DeleteFolderCommandInput`, `AsyncReaderWriterLockWriter`, `OnCallback`, `GLTF`, `ShapeType`, `TileLoaderState`, `ConfigPlugin`, `ConfigAction`, `DeckPart`, `ColumnType`, `AbstractServiceOptions`, `EngineRanking`, `SemanticTokensBuilder`, `NavSource`, `BattleDetail`, `ASScope`, `CSSValue`, `LogOptions`, `EmbedObj`, `FunctionTypeBuildNode`, `FetchableField`, `LayoutedNode`, `ServiceBinding`, `PluginImport`, `CdsIcon`, `MessageCallback`, `ReportsService`, `Agents`, `RouterProps`, `IGen`, `ControlItem`, `Flight`, `Dispatch`, `RawRestResponse`, `AbsoluteFilePath`, `CreateVolumeCommandInput`, `RectangleProps`, `NoopExtSupportingReactNative`, `PinType`, `IBufferCell`, `DescribeAccountAttributesCommandInput`, `DeleteNotificationsRequest`, `FileResult`, `BillingInfo`, `SelectModel`, `Footer`, `Triggers`, `AccountDevice_VarsEntry`, `TableMap`, `ValuedConfigurationMetadataProperty`, `EvaluationContext`, `AggsStart`, `MultipleLiteralTypeDeclaration`, `InputBoolean`, `StepProps`, `Mockchain`, `nodes.Node`, `DestroyOptions`, `HitInfo`, `AssemblyData`, `IPayload`, `Control`, `Asset`, `RunEvent`, `ProcessorModule`, `ILegacyScopedClusterClient`, `DDSTextureHolder`, `IFieldFormat`, `IRequestMap`, `IUri`, `NonNullable`, `TranslatorType`, `ProxyRule`, `Mapping`, `Dec`, `SphericalHarmonicsL2`, `StepArgs`, `LabelTable`, `SavingsManager`, `SelectionData`, `IDateStatistics`, `ElementProps`, `ConfigurableFocusTrap`, `DisabledTimeConfig`, `ExpandedEntry`, `MockDialog`, `DependencyResolver`, `IFsItem`, `EncodeOutput`, `ProjectReference`, `CartoonConfig`, `BlockBlobGetBlockListResponse`, `XanimePlayer`, `InteractionWaitingData`, `MutationRequest`, `ErrorFormatter`, `ComponentCtor`, `CrossBridgeAsset`, `TrackMapOptions`, `monaco.Range`, `KeyIcon`, `AndroidTarget`, `IJobConfig`, `ClassNameType`, `AnimationTrack`, `ResponsiveStorage`, `Channel`, `RowMap`, `FunctionImpl`, `RpcResponse`, `ServerWalletAPI`, `ApplicationQuestion`, `ScheduleType`, `StackResultsMatcher`, `JournalShowQueryParams`, `JSDocType`, `OperationGroupDetails`, `MapDispatchProps`, `PotentialPartnersState`, `InjectionToken`, `IServerError`, `ListRecommendationsCommandInput`, `BadGuy`, `IOptions`, `LitecoinjsKeyPair`, `SuiteNode`, `ExpressionAttributeValues`, `InterfaceTypeDefinitionNode`, `AutocompleteSettings`, `SendDataRequest`, `StrokeDrawingContext`, `Where`, `ITrack`, `IOutputOptions`, `Mocha.Suite`, `AppserviceMock`, `LoaderOptions`, `ObjectConsumer`, `Connex.Driver`, `LazyQueryHookOptions`, `GlobbyOptions`, `SVGAttributes`, `PortalProps`, `DragState`, `ModuleInstance`, `TranslateConfig`, `VueDecorator`, `ContextMenuService`, `ee.Emitter`, `JestProcess`, `IContainerRuntimeMetadata`, `ChannelCardType`, `CapabilitiesService`, `SavedObjectsMigrationConfigType`, `SendParams`, `InitCmdContext`, `WebGLVertexArrayObjectOES`, `GetAuthorizersCommandInput`, `IProtoTask`, `QueuingStrategy`, `EmissionsController`, `SuperAgentRequest`, `PackageResult`, `AlertDialog`, `ReferencesIdDictionary`, `IBasePath`, `ErrorCallback`, `Person_Employment`, `ViewPort`, `IMark`, `_IObjectMap`, `XcomponentClass`, `Images`, `StringValueNode`, `AttributeDerivatives`, `Queue`, `HsLanguageService`, `StoreConfiguration`, `Coda`, `AddressDTO`, `ViewBaseDefinition`, `ErrorHandler`, `GeneratorOptions`, `ListMembersCommandInput`, `DataRowItem`, `ProtocolResponse`, `Nuxt`, `LevelsActionTypes`, `NzAutocompleteOptionComponent`, `GetDatabaseCommandInput`, `FetchHandlers`, `URLLoader`, `GetRowLevelKeyFn`, `IEndpoint`, `NodeUnit`, `CheckStatus`, `MountedBScrollHTMLElement`, `TodoAppDriver`, `d.MatchScreenshotOptions`, `_1.Operator`, `Awaited`, `ResolvedTypeReferenceDirective`, `IDate`, `DiscussionEntity`, `TestEnv`, `ListAlertsCommandInput`, `PersonaId`, `CustomParameterGroup`, `XLSX.WorkSheet`, `ImportFacebookFriendsRequest`, `HLTVPageElement`, `Express.Multer.File`, `LambdaExpr`, `EditorContext`, `CollisionBox`, `Cone`, `MsgSignProviderAttributes`, `LinesResult`, `CompoundFixture`, `CategoryModel`, `ITask`, `IModelDecoration`, `ParameterChange`, `ChartScene`, `ColRef`, `FormulaOptions`, `ValueDescPair`, `ProjectsState`, `MatchPrefixResult`, `ROPCService`, `DialData`, `DaffCategoryFilterEqualRequest`, `SelectValue`, `HierarchicalItem`, `RpcRequest`, `ItiririAsync`, `OnConflictNode`, `Stripe.Event`, `PatternValueNode`, `SimpleAnalyzer`, `ActionBarProps`, `TextDrawer`, `HierarchyRectangularNode`, `InputComponent`, `ButtonOptions`, `IBackoffStrategy`, `SelectedIndexChangedEventData`, `SignInState`, `ImmutableBucket`, `ExecutionContract`, `SubscriptionResult`, `RemoteMessage`, `SymbolFormatFlags`, `SelectQuery`, `SolidityVisitor`, `Tools`, `RichEmbed`, `FacetFaceData`, `StaticSiteZipDeploymentARMResource`, `CompilerEventFileUpdate`, `GroupEventType`, `I18nUpdateOpCodes`, `FunctionMethods`, `ANDGate`, `FieldDescriptor`, `Type_Which`, `RepoConfig`, `MatchFunction`, `CalcFun`, `ShurikenParticleRenderer`, `SortCriteria`, `QRCodeSharedData`, `IPullRequestListItem`, `GherkinDocumentHandlers`, `matrix.MatrixArray`, `GfxRenderPass`, `IRGB`, `SanityDocument`, `requests.ListMfaTotpDevicesRequest`, `BasicInfo`, `ClonePanelAction`, `SimpleSignedTransferAppState`, `ScopedMemento`, `KeysRequest`, `StickyVirtualizedListState`, `ProjectStore`, `RangeAsyncIterable`, `IndexedAccessTypeNode`, `pointerState`, `d.ComponentRuntimeHostListener`, `Alternative`, `InputGenerator`, `HitTesters`, `ExtendedWebSocket`, `UseDropdown`, `dRes_control_c`, `PublisherDoc`, `TabContentItem`, `ExtendedVue`, `AttachmentData`, `CodePddlWorkspace`, `ResourceGroup`, `Real_ulong_numberContext`, `ProductFilterDTO`, `PerfState`, `SocketIOClient.Socket`, `TextEncoder`, `MockDataGenerator`, `GenerateConfig`, `HydrateFactoryOptions`, `TypeScriptService`, `Appointment`, `TransactionClientContract`, `UpdateConnectionCommandInput`, `IDict`, `States`, `QueryAccess`, `ParameterType`, `VariableGroupData`, `TreeGridAxis`, `React.Navigator`, `StyleCompiler`, `ListFlowsCommandInput`, `Availability`, `Undo`, `ProjectTilemap`, `TestParams`, `GameObjectInfo`, `DesignerTypeOption`, `ViewableRobot`, `AnnotationEventEmitter`, `StylusNode`, `ICompactPdfTextObj`, `IMatchResult`, `ScrollLogicalPosition`, `DateKey`, `IRoundResult`, `TResolver`, `Int128`, `RuleIteratorWithScope`, `BanGroupUsersRequest`, `NewPackagePolicyInput`, `Reminder`, `CacheNode`, `TrackData`, `Expected`, `GLTF.AccessorComponentType`, `ListRulesResponse`, `PuppetClassInfo`, `OptionsOrGroups`, `IHashProvider`, `ToastOptions`, `DataRecordValue`, `SGSCachedData`, `MappingTreeArray`, `AlexaLambda`, `ConcreteBatch`, `IAnnotation`, `PLSQLCursorInfosVSC`, `AlertComponent`, `EgressSecurityRule`, `VoiceAssistant`, `DeserializerContext`, `common.ClientConfiguration`, `RemoteHandler`, `ParseElement`, `JSONDiff`, `BulkInviteCommand`, `HandlebarsTemplate`, `TaskTiming`, `Deferrable`, `ItemInterface`, `RenderPlugins`, `T14`, `BasicProfile`, `NamedMouseElement`, `LinkTextLocator`, `apid.ManualReserveOption`, `PropertyAssignments`, `Sound`, `CreateMeetingWithAttendeesCommandInput`, `ISolution`, `ShuffleIterator`, `AudioSource`, `JsonAst`, `GameMarks`, `IKeyValue`, `ReflectedValueType`, `NodeDef`, `ForecastSeriesContext`, `CallHierarchyDeclaration`, `Introspector`, `tStartupOrShutdown`, `Sign`, `Highcharts.RangeSelectorButtonsOptions`, `AkimaCurve3d`, `EvaluatorOptions`, `IMediatorConfigurator`, `VirtualRows`, `VideoStreamIdSet`, `DurationEvent`, `DefaultClientMetricReport`, `PlyAdapter`, `PanResponderGestureState`, `ColumnReference`, `PgAttribute`, `MeshInfo`, `SerializeOptions`, `ContactSubscription`, `Demo`, `Review`, `WebGLContextWrapper`, `fabric.Object`, `ComponentTreeNode`, `RoleData`, `TestCaseInfo`, `StringOrNumberOrDate`, `webpack.Compiler`, `ThemeManager`, `EntryId`, `WorkerArgs`, `CodeActionParams`, `TokenAccount`, `ReadableData`, `ElementAspectProps`, `Segment1d`, `VariableModel`, `SigningMethod`, `APIRequest`, `requests.ListBucketsRequest`, `requests.ListCrossConnectGroupsRequest`, `VocabularyOptions`, `TestResultContainer`, `interfaces.Unbind`, `EventKeys`, `Progress.INeonNotification`, `messages.Scenario`, `RequestEvent`, `IGhcMod`, `UIError`, `ThemeExtended`, `Fig.Option`, `ResponseInterface`, `Urbit`, `IFeatureSet`, `ScheduleDoc`, `ThemeModeEnum`, `AthenaRequest`, `DisplayMarker`, `TestDataSource`, `MarkerInfoNode`, `CW20Instance`, `ICosmosTransaction`, `AnchorMode.Any`, `Droppable`, `SerializedObject`, `Behavior`, `LangOptions`, `DiffOptions`, `LightInstance_t`, `FactoryArgs`, `ParsedQRL`, `DirectoryInode`, `OnCleanup`, `Point3dArrayCarrier`, `ColumnDef`, `MDCListIndex`, `Browser.Interface`, `UtxoInfoWithSats`, `PureTransition`, `ProcessRequirement`, `Sigma`, `ListTargetsForPolicyCommandInput`, `PrayerTimes`, `VObject`, `SeekRange`, `RenderFlags`, `GetModelCommandInput`, `MockOtokenInstance`, `BaseTranslatorService`, `ICarsRepository`, `StateInstance`, `TS`, `RuleTransition`, `TracePrinter`, `HealthpointLocationsResult`, `NavigationEdge`, `TileMapLayerPub`, `TSQuerySelectorNode`, `App.webRequest.IRequestProcessor`, `bigint`, `ComparisonOperator`, `SummaryST`, `KeyInDocument`, `GX.TexPalette`, `ListFunctionsCommandInput`, `BaseMultisigData`, `ListCertificatesRequest`, `Http3PriorityFrame`, `BackupJSONFileLatest`, `CreateService`, `DiscordStore`, `WordCloudSettings`, `DAL.KEY_X`, `ECSqlValue`, `FileInode`, `RefundPayerStore`, `MemoOptions`, `AppModule`, `GlobalEnv`, `AssetReference`, `CLM.EntityBase`, `XmlParserNode`, `ConsumedCapacity`, `DescribeSchemaCommandInput`, `IGetProjectsStatistics`, `IValidationContext`, `ProxyReducer`, `mongoVisitor`, `VisibleTreeNodes`, `ClusterCollection`, `SessionsConfigSchema`, `TutorialModuleNoticeComponent`, `FileFilter`, `RouterSource`, `GenericIdModel`, `DynamoDbFileChange`, `DangerInlineResults`, `GreetingService`, `Frakt`, `CredValues`, `StoreAction`, `InjectedConnector`, `CachedNpmInfoClient`, `TypedTensor`, `CoordinateType`, `AdalService`, `GetPerspectiveOptions`, `t_6ca64060`, `Viewer.Viewer`, `ROLES`, `TreeBudgetEvent`, `ResponserFunction`, `MockData`, `LogAnalyticsCategory`, `FS`, `CompBitsValue`, `DropPosition`, `ZxBeeper`, `TaskExecutionSchema`, `VideoStreamOptions`, `ChannelJoin`, `DrawBufferType`, `DiagnosticSeverityOverrides`, `IUrlResolver`, `PadData`, `ShorthandPropertyAssignment`, `PokemonService`, `ValueReflector`, `SubscriptionAlreadyExistFault`, `AuthProviderProps`, `MathsProcessor`, `IterationStatement`, `Reshape`, `ModuleModel`, `MaybeTypeIdentity`, `TaskRun`, `ReifiedType`, `CustomFeatureConfig`, `LoadEventData`, `OverlayContainer`, `addedNodeMutation`, `CliHttpClientOptions`, `MediaStreamsImpl`, `RequestsService`, `KamiConfig`, `DNSAddress`, `UpdaterService`, `BotTags`, `ElementMaker`, `RenderingOptions`, `NotifyService`, `SearchQueryCtx`, `Json.ParseResult`, `InstancePrincipalsAuthenticationDetailsProviderBuilder`, `DOMQuery`, `GluegunToolbox`, `IBoundingBox`, `CacheOptions`, `PageDensity`, `eventType`, `FunctionalLayout`, `PluginValidateFn`, `NewBlock`, `ActorRenderModeEnum`, `DurationLike`, `TLBounds`, `IPositionComponent`, `UpdateUserRequest`, `PS`, `WalkNode`, `DeleteAccountsValidationResult`, `RuntimeIndex`, `LongOptionName`, `angular.IQService`, `CloningRepository`, `CurveCollection`, `IComparatorFunction`, `ParamSpecEntry`, `next.AppLayer`, `RTCConfiguration`, `BitbucketPipelines`, `ResponseComment`, `DemographicCounts`, `CameraState`, `PanelPackage`, `ProductControlSandbox`, `Http3Header`, `ProtocolRequestType`, `DeleteTemplateCommandInput`, `GameObject`, `Md.List`, `d.StyleCompiler`, `KeychainCredential`, `SubnetMapping`, `CreateMediaDto`, `Decibels`, `TransferRequest`, `ImportsAnalyzerResult`, `VdmComplexType`, `OpenSearchDashboardsSocket`, `Img`, `PostService`, `FileRange`, `BinarySwitchCCSet`, `CtrNot`, `ProviderConfig`, `StopDBClusterCommandInput`, `TextEditorViewColumnChangeEvent`, `FrameManager`, `ServerMap`, `GitHubLocation`, `AppStoreReplay`, `TableInterface`, `StatusBarAlignment`, `AlgBuilder`, `AsyncFactory`, `OhbugUser`, `Codeword`, `PDFHeader`, `MediaService`, `TreeNodeInfo`, `NotificationsServiceStub`, `Shadows`, `MythicAction`, `IFeatureFlag`, `EngineOptions`, `TestFile`, `SPNode`, `OBS`, `CeloTokenType`, `UUIDType`, `AddApplicationOutputCommandInput`, `LocalStorage`, `Events`, `parse5.DefaultTreeElement`, `IRemoteTargetJson`, `Indentation`, `SearchActions`, `GaugeSettings`, `SchemaMap`, `IDBOperator`, `SysTask`, `UserLogin`, `ITodo`, `requests.GetProjectRequest`, `AxiosError`, `HookProps`, `IOptionSelectText`, `TranslationState`, `Calendar`, `HTMLHeadElement`, `ObjectPage`, `OutboundTransport`, `ErrorResponse`, `CommBroker`, `CommonIdentity`, `GeometryCollection`, `requests.ListAutonomousVmClustersRequest`, `MerchantEntity`, `SandDance.types.Column`, `EditableTextStyle`, `EventPayload`, `PagedParamsInput`, `WebGLTimingInfo`, `ThemeValueResolver`, `HashChangeEvent`, `InlineConfig`, `types.Message`, `BenchmarkResult`, `ProblemModel`, `DetailsProps`, `ConnectionMetrics`, `IRouteTable`, `DashLowerthirdNameInputElement`, `TaskExitedEvent`, `MDCBaseTextField`, `IStatus`, `TestServerHost`, `CustomRenderer`, `WorkRequestLog`, `Artwork`, `NavigationExtras`, `ts.ConciseBody`, `serialization.ConfigDict`, `ActiveOverlay`, `Episode`, `OperationContext`, `cp.ForkOptions`, `DescribeReportDefinitionsCommandInput`, `Portal`, `RecurringBillPeriod`, `FieldTypeMetadata`, `RendererService`, `IUserModel`, `UpdateEnvironmentCommandInput`, `IHost`, `ts.TypeNode`, `PrivateIdentifierInfo`, `CreateMessageDto`, `SendTable`, `CallMethodRequestLike`, `d.PlatformPath`, `Deep`, `NVMJSONNodeWithInfo`, `IProfileLoaded`, `AzExtParentTreeItem`, `Private.PaintRegion`, `PushRequest`, `WebsocketProvider`, `ConvertIdentifier`, `NormalModule`, `CodeEditorMode`, `LockState`, `CfnExpressionResolver`, `TypeList`, `IPQueueState`, `RegExpMatchArray`, `Surface`, `SystemMessage`, `MetadataORM`, `IMessageRepository`, `PaletteOptions`, `FilterStatusValues`, `IHandleProps`, `IDBEndpoint`, `ACrudService`, `ViewInfo`, `MyComponent`, `LineSide`, `requests.ListWorkspacesRequest`, `StructuredType`, `EmojiService`, `RecommendationCount`, `CallExpressionArgument`, `Generatable`, `CspConfig`, `Features`, `TimeHistoryContract`, `FaceletCubeT`, `CipherResponse`, `IInputHandler`, `AppClientConfig`, `SwitchFunctorEventListener`, `IEqualityComparer`, `IterableActivity`, `TransportSession`, `ExpressionResult`, `WebSiteManagementModels.SiteConfig`, `Documentation`, `d.ComponentCompilerListener`, `IdMap`, `ToolItemDef`, `React.Route`, `ExpectedNode`, `ExpressionFunctionParameter`, `P9`, `Script`, `MockEventListener`, `VideoTexture`, `MagicString`, `LexoInteger`, `ClientRenderOptions`, `EPickerCols`, `cdk.StackProps`, `StoreConstructor`, `ReactClientOptionsWithDefaults`, `WebProvider`, `DataStateClass`, `CLR0`, `Graphql`, `SegmentEvent`, `IGameUnit`, `TableImpl`, `WebGLShaderPrecisionFormat`, `AuthHeaders`, `UpdateGatewayInformationCommandInput`, `CreateApplicationRequest`, `TaskProvider`, `DataProps`, `RestPositionsResponse`, `DeviceMetadata`, `HsDrawService`, `Vec3`, `BuildMiddleware`, `IDocumentManager`, `AppContextType`, `IChip`, `Mirror`, `RouteNode`, `AccountFacebook`, `WebpackConfiguration`, `Monad2C`, `HeroAction`, `UploadxService`, `TouchData`, `FormControlConfig`, `SlicedExecution`, `IBlockchainsState`, `StrictEventEmitter`, `PartitionBackupInfo`, `TextRangeCollection`, `BranchSummary`, `ITaskData`, `ProgramInfo`, `Registers`, `DOMPoint`, `CodeActionCommand`, `IMidwayBaseApplication`, `IMidwayBootstrapOptions`, `OHLCPoint`, `LogInfo`, `IStringDictionary`, `ArtifactItemStore`, `BufferData`, `OnEffectFunction`, `Rental`, `GfxAttachmentState`, `AjaxResponse`, `DeployResult`, `PublicAccessBlockConfiguration`, `LeanDocument`, `IOperatorIdentifier`, `InterfaceWithValues`, `NodeJS.WritableStream`, `NodeSet`, `MDCShapeScheme`, `StatusContext`, `Tax`, `GlobalsSearch`, `Post`, `Keyword`, `IEquipment`, `IQueryState`, `MDCLineRippleAdapter`, `AdminGameEntity`, `CustomSeriesRenderItemAPI`, `IOidcOptions`, `Simplify`, `IColumnRelationMetadata`, `EntityCollectionReducer`, `Vue`, `SwitcherState`, `SubjectInfo`, `SubscriptionClass`, `IMiddlewareGenerator`, `QCBacktest`, `cc.Prefab`, `ReadOptions`, `ICharAtlasConfig`, `GpuInformation`, `TagsFilter`, `IKeyQuery`, `CsvGenerator`, `Empty`, `ComponentInterface`, `UserView`, `ReactTestRenderer`, `GetDatabasesCommandInput`, `CurrencyToValue`, `GLclampf3`, `ExtractedCodeBlock`, `CanvasSpace`, `TNSCanvas`, `BroadcasterService`, `RobotApiRequestOptions`, `FrameStats`, `ValProp`, `CreateDirectoryCommandInput`, `GLRenderingDevice`, `FlowListener`, `RedisModuleOptions`, `FragmentedHandshake`, `ProcessEvent`, `GeoPolygonFilter`, `ZeroPadding2DLayerArgs`, `TestScriptOptions`, `Pkcs12ReadResult`, `ProductState`, `SpeakerWithTags`, `AnnotatedFunctionInput`, `PointItem`, `sdk.RecognitionEventArgs`, `StandardTask`, `AbsolutePath`, `IDataViewOptions`, `WebGLRenderbuffer`, `PDFDocument`, `Phaser.Geom.Point`, `InvestDateSnapshot`, `ContentReader`, `UiMetricService`, `QueryOutput`, `P6`, `EthereumNetwork`, `RopeBase`, `MongoRepository`, `GaussianDropoutArgs`, `Reconciliation`, `requests.ListInstancePoolInstancesRequest`, `GetUsageStatisticsCommandInput`, `VertexLayout`, `SubscriptionEnvelope`, `GherkinDocumentWalker`, `IRun`, `ApiPromise`, `BehaviorNode`, `CompletedLocalIpcOptions`, `CompositeBatch`, `TextEditAction`, `SearchFacetOperatorType`, `CompileTarget`, `ListenCallback`, `Assertions`, `TRPCError`, `StepDefineExposedState`, `VariableNames`, `BaseType`, `Declarator`, `ModdedBattleScriptsData`, `JQueryEventObject`, `ScreenshotService`, `ObjectKeyMap`, `NodeJS.Timeout`, `CommittersDetails`, `TemplateCompiler`, `CronConfig`, `IOctreeObject`, `GADRequest`, `RecursiveStruct`, `KubeConfiguration`, `EncryptionContext`, `ParsedCommandLine`, `CapnpVersion`, `SingleSigSpendingConditionOpts`, `InternalServiceErrorException`, `RouteOptions`, `TestPlan`, `Fragment`, `IFileSystemCreateLinkOptions`, `DatabaseFeatureOptions`, `ToolbarDropdownButtonProps`, `QueryResponse`, `FileHandler`, `OffsetRange`, `VirtualMachineRunCommandUpdate`, `DescribeInstanceAttributeCommandInput`, `HistoryInstructionInfo`, `TutorialDirectoryNoticeComponent`, `ComponentHolder`, `IStepInfo`, `ɵAngularFireSchedulers`, `TSFunDef`, `ThyAbstractOverlayRef`, `InputMap`, `CanvasFontWeights`, `CheckerType`, `DbCommand`, `CombatGameState`, `IViewRegionsVisitor`, `EthersBigNumber`, `UpgradeConfigsParams`, `messages.SourceMediaType`, `TileAttrs`, `BckCtrlData`, `AppAction`, `Anchor`, `GameId`, `SiteService`, `BaseArtifactProvider`, `TabularRows`, `PromiseRejectedResult`, `UserCreateInput`, `IViewbox`, `AuthenticationResult`, `SimpleGit`, `Traversable`, `esbuild.OnLoadArgs`, `WsClient`, `ImageAssetService`, `DmarcState`, `LegacyDateFormat`, `NamedArgTypeBuildNode`, `PropertyDataChangeEvent`, `MethodsOrOptions`, `DeployedBasset`, `ts.ExpressionStatement`, `SdkSubscribeAckFrame`, `ActivitySourceDataModel`, `GetResourcePolicyCommandInput`, `IResolvedUrl`, `xmlModule.ParserEvent`, `IFileSystem`, `SimpleWallet`, `IPathsObject`, `StockState`, `ScreenSize`, `FormControlName`, `SimNet`, `ChartRef`, `requests.ListNetworkSecurityGroupVnicsRequest`, `ResolvedId`, `NetworkInterfaceInfo`, `TextOffset`, `CookieAttributes`, `IPCMessage`, `SceneView`, `FastifyAdapter`, `http.Server`, `TempFlags`, `GadgetPropertyService`, `Painter`, `SplitField`, `JIterator`, `WorkerMessage`, `MigrationContext`, `FreeCamera`, `TaskConfig`, `Telegraf`, `SKU`, `WalletGroupTreeItem`, `IItemTree`, `OCSpan`, `Apollo.MutationHookOptions`, `Eyes`, `K.IdentifierKind`, `MockDirective`, `MockProvider`, `TJS.Definition`, `IModalState`, `DeleteDBClusterCommandInput`, `TableRowPosition`, `IQuiz`, `requests.ListOdaInstancesRequest`, `IAppOption`, `PkGetter`, `ConnectedProps`, `monaco.Position`, `U8Node`, `IndicatorProps`, `ExecutionPlanImpl`, `StepBinary`, `PluginType`, `QuickAlgoLibrary`, `BackstageItem`, `MonthYearDate`, `VideoFrameProcessorPipelineObserver`, `SubmitProfile`, `ExtraDataModel`, `PBRMaterial`, `RequestInfoUtilities`, `IFlowItemComponent`, `LogTracker`, `OverrideCommandOptions`, `AttributeTableData`, `IDynamicPortfolioColumnConfig`, `PossiblyAsyncIterable`, `XListNode`, `ColumnIndexMap`, `QueryResults`, `Ec2MetricChange`, `InstanceWrapper`, `StackLine`, `RtorrentTorrent`, `DirectiveBinding`, `DescribeFleetAttributesCommandInput`, `Fixed18`, `PositionType`, `Blending`, `IRenderContext`, `AllowedParameterValue`, `IBlockData`, `OAuth2Client`, `OperationObject`, `SVGUseElement`, `CreateSubscriptionRequest`, `SystemErrorRetryPolicy`, `NoteSequence`, `Traced`, `CompatibleDate`, `TypeUtil`, `ICustomer`, `MarkerRange`, `UsersAction`, `Journal`, `TestService`, `PerformanceStatistics`, `DeleteDBInstanceCommandInput`, `Union2`, `ProjectsStore`, `InstantiationNode`, `CssToEsmImportData`, `SFDefaults`, `AppContainer`, `MulticallRequest`, `IMatchableOrder`, `PartitionConfig`, `Svg`, `UIApplication`, `ResolverRule`, `GlTfId`, `Transcript`, `BumpInfo`, `TaskSchedule`, `EnumDescriptorProto`, `S2DataConfig`, `React.ComponentPropsWithoutRef`, `GfxRenderInstList`, `MutableVideoPreferences`, `DescribeSecurityProfileCommandInput`, `Logo`, `Telemetry.TelemetryEvent`, `MeetingCompositePage`, `ListAction`, `ChannelTokenContract`, `Expansion`, `DirectionMode`, `LQueries`, `AuthCredentials`, `GenerateResponse`, `IChamber`, `IdentifierContext`, `PreviousSpeaker`, `SessionType`, `TerraformStack`, `NSURL`, `SpecList`, `CandleStick`, `StageSwitchCtrl`, `QlogWrapper`, `ApplicationTokenCredentials`, `AppointmentId`, `EpicSignature`, `TypeOf`, `IDocument`, `App.services.IHttpChannelService`, `TokenConfig`, `tslint.RuleFailure`, `FileSystemHelper`, `SettingsRootState`, `MdcTabScrollerAlignment`, `DirectoryUpdate`, `CustomAtom`, `CollisionInfo`, `AbstractUserProxy`, `TransformPluginContext`, `TabNavigationBase`, `ScriptTask`, `PointComposition`, `FromSchema`, `IAmazonLoadBalancer`, `Values.ReadyValue`, `IAnimationKey`, `FormControlState`, `NgxFileDropEntry`, `ListAssociatedResourcesCommandInput`, `PlayerState`, `TaskComponentState`, `StaticService`, `AccessTokens`, `PiEditConcept`, `TestComponent`, `PrintLabel`, `NlsBundle`, `ParsedTag`, `IApplicableSchema`, `SchemaEntry`, `CacheFileList`, `UberPBRMaterial`, `TranspileOptions`, `FuzzyLocale`, `ObjectContainerParams`, `NumberAttribute`, `ApolloQueryElement`, `IRelease`, `ServerHello`, `InputElement`, `FormInternal`, `FirebaseFirestore.Query`, `ErrorConstructor`, `ObjectListResult`, `JwtConfigService`, `Execution`, `AssociatedName`, `TRequest`, `ThyAutocompleteRef`, `CommandMetadata`, `ActivatedRoute`, `MultiStats`, `BaseTypes`, `IClientInteraction`, `GLM.IArray`, `GetUserInfoQuery`, `IAsfObjectHeader`, `JSONSchemaStore`, `ListChannelBansCommandInput`, `StepFunctions`, `Algebra.TripleObject`, `Ecs`, `CSSSnippet`, `HoldSettings`, `Ethereum`, `StringLiteralNode`, `PositionGrid`, `MDCRippleFactory`, `Jsonified`, `_app`, `IAuthFormContext`, `QueryObserverResult`, `BlogEntry`, `CompositeCollider`, `TypeVblDecl`, `LSConfigManager`, `AbortSignal`, `GlobalMaxPooling1D`, `FileParseResult`, `ClearCollections`, `FeederData`, `InterfaceWithConstructSignatureOverload`, `OperationCallbackArg`, `PutFileOptions`, `TreeSelectOption`, `ISqlite.SqlType`, `InitializeServiceCommandInput`, `FurParam`, `Either`, `Macro`, `ListAnswersCommandInput`, `ElementEvent`, `StaticSiteUserProvidedFunctionAppARMResource`, `Bug`, `MarkInterface`, `ThyDragOverEvent`, `UhkDeviceProduct`, `ApiController`, `RawSourceMap`, `DriftConfig`, `TradeFetchAnalyzeEntry`, `CategorizedClassDoc`, `ThyPopoverContainerComponent`, `RequestResponder`, `VersionVector`, `Eq`, `NodeDocument`, `LocalStorageAppender`, `ListMenu`, `messages.Duration`, `DanmakuDrawer`, `GraphQLObjectType`, `SourceOffset`, `ContainerDefinition`, `PrismaClientConstructor`, `TVShow`, `LicensingPlugin`, `StoredOrder`, `IBlockOverview`, `InMemoryEditor`, `ChartProps`, `UserRecord`, `CustomUser`, `ParseState`, `debug.Debugger`, `OpenSearchdslExpressionFunctionDefinition`, `ListRegistriesCommandInput`, `Types.CodeGenerator.CustomGenerator`, `FirstMate.Grammar`, `MockCSSStyleSheet`, `IValidationOptions`, `SeriesDataType`, `IContentVisitor`, `IGlobal`, `IStateGlobal`, `Workshop`, `TKey1`, `BuilderCanvasData`, `MessageService`, `ESLCarouselSlide`, `Refable`, `Simulation3D`, `FolderUpload`, `TransportRequestOptionsWithOutMeta`, `TableSchemaDescriptor`, `ElementQueryModifier`, `PDFDocumentProxy`, `TypeFlags`, `NetworkVersion`, `BackendConfig`, `ODataResource`, `SHA3`, `CRS`, `FeatureDescriptor`, `TeamDocument`, `GLTFFileLoader`, `BufferVisitor`, `AccessTokenRequest`, `ProxyRulesSubscription`, `ValidatePurchaseResponse`, `CommandItemDef`, `UpdateAction`, `CloudFormationClient`, `LifecycleState`, `RowInfo`, `SvgToFontOptions`, `MIRVirtualMethodKey`, `EmitterContext`, `IUiAction`, `IDeployment`, `PagingOptions`, `IDBTransaction`, `DataViewField`, `FeatureStabilityRule`, `DocumentedType`, `TransactionDescription`, `AMM`, `RenderQueue`, `ProofService`, `SummaryArticle`, `TopicsMap`, `AccountWithAll`, `REPL`, `SwiperProps`, `XmlSerializerOptions`, `ICacheConfig`, `TranslationUnit`, `WrappedEntity`, `ModelType`, `Markup`, `ServerType`, `PermissionTree`, `StreamEmbed`, `AlertServicesMock`, `DevicePixelRatioObserver`, `TooltipValueFormatter`, `SQSEvent`, `IKeyboardEvent`, `ServiceWorkerGlobalScope`, `TDiscord.TextChannel`, `Sudo`, `ComponentInternalInstance`, `SelectOptionComponent`, `TiledTMXResource`, `ParameterObject`, `GenesisConfig`, `ActiveErrorMessage`, `OnPostAuthHandler`, `ForgotPassword`, `PopupProps`, `RuntimeMappings`, `ForwardRefRenderFunction`, `ITimeOff`, `ArrayOperation`, `GetFunctionCommandInput`, `GetBucketPolicyCommandInput`, `DomainEventSubscriber`, `InputLink`, `DataColumnDef`, `SceneGraphNodeInternal`, `Position3DObject`, `ProgramInput`, `PayableTx`, `Entrypoint`, `DependencyItem`, `UserAccount`, `Basset`, `SubtleButton`, `DeserializeAggConfigParams`, `HTMLDOMElement`, `Highcharts.AnnotationsOptions`, `ResolvedUrl`, `RequestInfo`, `AbstractParser`, `KeyboardListenerAPI`, `PageData`, `PredictablePickleTestStep`, `GLbitfield`, `MatchersObject`, `multiPropDiff`, `MediaQuery`, `NormalizedScalarsMap`, `TlcCode`, `ComponentCompilerState`, `requests.ListSecurityAssessmentsRequest`, `TagsObject`, `SEGroup`, `Bits`, `ScreenElement`, `InsightLogicProps`, `INameDomainObject`, `ObjectBinding`, `KeyState`, `PublicShare`, `provider`, `DefinitionInfoAndBoundSpan`, `Rational`, `WorkflowHooks`, `NumberDataType`, `ExportNamedDeclaration`, `BreakpointKey`, `VpcSecurityGroupMembership`, `ConsensusContext`, `ISceneDataArray`, `ExpressionFunctionOpenSearchDashboards`, `IAppEnvVar`, `DateOrDateRangeType`, `StyledComponentWithRef`, `VirtualDevice`, `MinecraftVersion`, `CommandType`, `StyleUtils`, `OnSuccess`, `PartyName`, `FooState`, `FsApi`, `Modification`, `ICData`, `ChangeNode`, `IPoint`, `UseSocketResponse`, `DomainEventClass`, `MessageEmitter`, `HTMLTitleElement`, `requests.ListSoftwareSourcesRequest`, `MFARequest`, `DrawingId`, `polymer.Base`, `EvmAccount`, `SocketIO`, `cheerio.Element`, `FirestoreForm`, `ChartUsage`, `CollectionFn`, `fromReviewerStatisticsActions.GetReviewerStatisticsResponse`, `RichTextProps`, `AxisType`, `FrameContainer`, `FaasKitHandler`, `CloseEvent`, `FiniteEnumerableOrArrayLike`, `Package.ResolvedFile`, `MessageSignature`, `MessagingService`, `MinecraftVersionBaseInfo`, `TestResult`, `IPCMessagePackage`, `HotObservable`, `server.Position`, `DictionaryFileType`, `MonitorModel`, `MutationConfig`, `Mocker`, `ArgumentsHost`, `ProcessedTransaction`, `ViewerConfiguration`, `AssertStatic`, `ParsedArgv`, `FavoriteTreeItem`, `ConnectionNode`, `CreateEnvironmentCommandInput`, `SubscriptionOption`, `AnnotationTooltipState`, `ResourceObject`, `SwitchCase`, `InlineFieldDescriptor`, `ActiveSelection`, `ResolvedDependency`, `DisplayNode`, `ApplicationTargetGroup`, `RequestFn`, `DemoFunction`, `Formats`, `LogHook`, `HttpApi`, `QueryAllParams`, `requests.ListZonesRequest`, `CommandLineConfiguration`, `CreateUserRequest`, `Bidirectional`, `GeoUnitDefinition`, `VehicleInfo`, `InstalledClock`, `ConstantJsExpr`, `CLR0_ColorData`, `DecimalArg`, `VgAPI`, `NodeFactory`, `LogMessage`, `ReferenceDescription`, `LogParse`, `DescribeEventSubscriptionsMessage`, `PickRequired`, `Events.exitviewport`, `SafeAreaProps`, `RendererType`, `RawSavedDashboardPanelTo60`, `TypeaheadState`, `SelectorType`, `IConnectionFactory`, `RedactChannelMessageCommandInput`, `ChangelogJson`, `TimelineTotalStats`, `UserDataService`, `SvgTag`, `PluginRevertAction`, `RequestListener`, `Glyph`, `ScannedFeature`, `GfxPass`, `CoreState`, `Proc`, `UpdateExceptionListItemSchema`, `CreateJobTemplateCommandInput`, `RuleMeta`, `MediaQueries`, `Term`, `_HttpClient`, `tf.fused.Activation`, `RuntimeContext`, `DetectedLanguage`, `DaffCategoryFactory`, `Delaunay`, `Matches`, `ICommandHandler`, `MaybeDate`, `IndexUUID`, `requests.ListChannelsRequest`, `TickViewModel`, `SelectorDatastoreService`, `CanvasIcon`, `PublicIdentifier`, `Moniker`, `ComboBoxMenuItemGroup`, `LanguageServiceDefaults`, `ResolverProvider`, `DependencyPins`, `LogAnalyticsSourceFunction`, `CurrentAccountService`, `BreadcrumbContextOptions`, `IPartitions`, `FormCookbookSample`, `IMenuItemProps`, `ExportMap`, `CartEntity`, `Simple`, `StringOptions`, `requests.ListClustersRequest`, `ComplexType`, `CohortType`, `StateUpdater`, `GitOutput`, `DocType`, `AggsState`, `JGOFNumericPlayerColor`, `WirePayload`, `SignedMultiSigContractCallOptions`, `IConsumer`, `DataRange`, `tensorflow.IFunctionDef`, `ResolveFn`, `NamedExports`, `Pane`, `LESSParser`, `WiiSportsRenderer`, `PhysicalKey`, `HSD_TEInput`, `IRect`, `IDimension`, `DirtyStyle`, `ArrayType2D`, `HeritageClause`, `NativeFunction`, `SSOLoginOptions`, `PortalPoller`, `PDFBool`, `IExistenceDescriptor`, `FsItem`, `MutableRef`, `UseQueryResponse`, `PricePretty`, `ConversationV3`, `DebtItemInterface`, `NestedContentField`, `PostMessageOptions`, `FbForm`, `IRouteItem`, `LogEvent`, `BigNumberFive`, `AbstractObject3D`, `commander.Command`, `AsyncSourceIterator`, `VStackProps`, `HorizontalAnchor`, `ExchangePriceQuery`, `FtrConfigProviderContext`, `IntervalOptions`, `OAuthUserConfig`, `IXulElementSpec`, `PopoverPlacement`, `RootCompiler`, `SemanticTokenData`, `NameMap`, `MapPlayer`, `SVType`, `StylableSymbol`, `IRenderable`, `LayoutPaneCtrl`, `HttpPayloadTraitsCommandInput`, `WebSocketProvider`, `SaveGame`, `UpdateSchemaCommandInput`, `ListEndpointsCommandInput`, `QueryTree`, `IManifestBindArtifact`, `AuditService`, `GraphQLModulesModuleContext`, `PrimType`, `PubPointer`, `ConfigPath`, `NgrxAutoEntityService`, `HdPrivateNodeValid`, `ObjectPattern`, `CompositeCollection`, `GlobalJSONContainerStorage`, `AssetResolver`, `TooltipType`, `Forward`, `RepositoryFactory`, `ServerErrorInfo`, `CertificateManager`, `requests.ListIPSecConnectionsRequest`, `SlideComponent`, `RenderStatus`, `Git.GitVersionDescriptor`, `NwtExtension`, `CompressionOptions`, `TagMapper`, `HTMLObjectElement`, `ModuleThis`, `EndRecordingRequest`, `ImportOrExportSpecifier`, `BitStream`, `AuthInterface`, `MockHashable`, `NumberEdge`, `DeclarationStatement`, `ReuseTabService`, `TCase`, `MagentoCart`, `styleFn`, `BlobServiceClient`, `TypeDefinitionParams`, `ITemplatizedCard`, `TimeResolvable`, `LinearLayout`, `net.Server`, `DataLoaderOptions`, `TLMessage`, `FakeMetricsCollector`, `Music`, `ThyGuiderRef`, `MoveCommand`, `FilterContext`, `CompletionItemProvider`, `ResourceTimelineViewWrapper`, `backend_util.TypedArray`, `PersistentCache`, `CraftTextBlock`, `IShapeBase`, `ObjectShape`, `FeedFilter`, `MacAddressInfo`, `ElementStylesModifier`, `ResponseHeader`, `requests.ListGrantsRequest`, `FocusableElement`, `ValueMapper`, `ITimeOffCreateInput`, `ApiEnumMember`, `FeatureContext`, `InputNodeExpr`, `CustomerAddress`, `LayerArrays`, `Cancellable`, `TsoaRoute.Models`, `ListDatasetImportJobsCommandInput`, `Exact`, `ListDatasetsResponse`, `ListJobsCommandInput`, `IntrospectionQuery`, `PrefixUnaryExpression`, `EquivMap`, `ASTTransformer`, `BottomSheetParams`, `ViewRegionInfoV2`, `WFDictionaryFieldValueItem`, `PerspectiveDataLoader`, `IOptionsFullResponse`, `CartService`, `TmdbTvDetails`, `messages.TestStep`, `FishSprite`, `FunctionAnnotationNode`, `DataViewBaseState`, `IOpenApiImportObject`, `DappInfo`, `requests.ListClusterNetworksRequest`, `IMediatorMapping`, `Delay`, `NotebookFrameActions`, `ChipsItem`, `ResultEquipped`, `WriteGetter`, `MockNgZone`, `MonthAndYear`, `KeyListener`, `ReferenceInfo`, `DatabaseTable`, `ControllerInstance`, `PostList`, `TestCollection`, `CompilerEventFileAdd`, `ThemeProps`, `LoggerParameters`, `ToolkitInfo`, `t.Comment`, `PushNotificationData`, `MapLayerSource`, `SyncPeriod`, `Set`, `PropertyModel`, `NetworkProfile`, `VectorTileDataSource`, `CompiledResult`, `SelectAction`, `BaseStruct`, `JsonFormsAngularService`, `FontNames`, `WebGLContext`, `P`, `RootOperationNode`, `LoginTicket`, `ReboostPlugin`, `ActivationLayerArgs`, `MarkBuilder`, `HTTPClient`, `KeyMapping`, `IncomingWebhook`, `UnionMember`, `ConfigFile`, `WritableStreamBuffer`, `ApiTypes.Groups.MessagesById`, `IHttpResponse`, `StyleResourcesFileFormat`, `DeleteAssetCommandInput`, `AuthProvider`, `MyCustomObservable`, `Activity`, `SlaveTimeline`, `GenericLayout`, `InterfaceAliasExport`, `Car`, `PrerenderUrlRequest`, `QueryRequest`, `GitUri`, `RegEntity`, `GetSettingSuccessCallbackResult`, `SavedObjectsResolveImportErrorsOptions`, `QComponent`, `Field_Slot`, `DeleteClusterCommandInput`, `Parser`, `ColumnRow`, `typescript.CompilerOptions`, `AppDefinitionProps`, `ParameterTypeModel`, `W2`, `TransformComponent`, `AsyncCallback`, `HydrusFile`, `BoundSideType`, `Info`, `DescribeMLModelsCommandInput`, `SyscallManager`, `RenderingDevice`, `WorkflowStepOutputModel`, `GX.IndTexScale`, `CeramicSigner`, `SdkClientMetricFrame`, `Tray`, `GlobalEventHandlers`, `SearchFilter`, `SigninOrSignupResponse`, `IConfigurationSnippet`, `IndexMap`, `ExternalLoginProviderInfoModel`, `DeleteFileSystemCommandInput`, `XIdType`, `NucleusApp`, `NativeImage`, `IVanessaEditor`, `MessageThreadStyles`, `SFARenderLists`, `DisplayListRegisters`, `SelExpr`, `GitDSL`, `MultisigBitcoinPaymentsConfig`, `AtomShellType`, `RoutableTileNode`, `OrbitControls`, `ComponentProps`, `f64`, `AppJob`, `WellState`, `WrapperProps`, `Sketch`, `ApplicationLoadBalancedFargateService`, `Shader3D`, `CustomSetting`, `ONodeSet`, `UpdateQueryBuilder`, `SearchFiltersState`, `ReaderObservableEither`, `UseTimefilterProps`, `TermType`, `DeleteChannelCommandInput`, `DSVEditor.ModelChangedArgs`, `TableName`, `PostgresConnectionOptions`, `Collider`, `NotRuleContext`, `Delaunator`, `Survey.Question`, `NewLineToken`, `Watch`, `LinkLabelVM`, `LoginCommand`, `BlockState`, `MeterChange`, `PathType`, `TokenFilter`, `GalleryApplicationVersion`, `ZRText`, `CompositeOperator`, `UIFileHelper`, `CmsModel`, `PropertyMatcher`, `ICategoryBins`, `CompletionList`, `ISummaryTreeWithStats`, `ResourceHandlerRequest`, `NormalDot`, `PluginEvents`, `ExportType`, `LanguageCode`, `WatcherMap`, `StartFlowCommandInput`, `BodyDatum`, `Deque`, `MonitoringMessage`, `PseudoElementSelector`, `ExecuteShellCommandFunction`, `AutoTranslateSummaryReport`, `ExportAssignment`, `requests.CreateJobRequest`, `UploadItem`, `ScriptContainer`, `ViewMeta`, `TokenParams`, `SpringValue`, `JPAExtraShapeBlock`, `OpenAPIV3.ParameterObject`, `Storybook`, `INumberDictionary`, `MeasureMethod`, `EnumOption`, `ResetPasswordAccountsValidationResult`, `PermissionsData`, `SwitchNodeParams`, `SentryRequestType`, `browser.runtime.MessageSender`, `CustomToolbarItem`, `Angulartics2Matomo`, `SimpleSavedObject`, `XStyled`, `AutofillScript`, `AttachmentService`, `ColorRegistry`, `Nodes.NameIdentifierNode`, `ICurrentWeather`, `UtxoInfo`, `Setting`, `Style`, `ListBranchesCommandInput`, `ICountryGroup`, `Range3dProps`, `ConstructorType`, `AccountProps`, `Adapt.AdaptElement`, `ElementGeometryCacheOperationRequestProps`, `DeleteUserResponse`, `FastRTCPeer`, `DaoTokenWrapper`, `TreeSet`, `Common.ISuite`, `EmployeeStatisticsService`, `AcceptedNameType`, `nodes.Declaration`, `PropertyMetadata`, `ReacordTester`, `ParsedDid`, `PublishJob`, `ConfigBuilder`, `AnyNgElement`, `CreateReactClientOptions`, `OrderByClause`, `IRuleOption`, `internalGauge`, `ParamNameContext`, `EntityMapperService`, `CS`, `purgeCommandCriteria`, `APProcessorOptions`, `SExpressionTemplateFn`, `TrackingOptions`, `LoopMode`, `Nothing`, `Scroller`, `StyledVNode`, `ShardFailure`, `IChunkOffsetBox`, `IVisitor`, `DrawCommand`, `DataConnection`, `StatusCode`, `EncryptionMaterial`, `Breadcrumb`, `StaticProvider`, `UseLazyQueryOptions`, `UnaryOperator`, `CreatedOrder`, `_Record`, `PadplusMessagePayload`, `OnItemExecutedFunc`, `AddRepositoryPayload`, `messages.TestStepResult`, `ServiceEndpointPolicy`, `IAureliaProject`, `tr.events.Name`, `IGenericTag`, `requests.ListSourcesRequest`, `RawSavedDashboardPanel730ToLatest`, `StepSelection`, `CLM.ActionBase`, `OnConflictUpdateBuilder`, `WorkspaceMap`, `IEmployeeAppointmentCreateInput`, `ActionSheet`, `VisualizeUrlGeneratorState`, `RequestSelectorState`, `IDebugger`, `GetObjectRequest`, `TriggerData`, `IScriptCode`, `PackageTypeReport`, `GraphExportedPort`, `FluentIterable`, `WritableDraft`, `Animated.EndCallback`, `Article`, `CompatConfig`, `NameSpaceInterface.Interface`, `IProviderInfo`, `FIRDocumentReference`, `RedBlackTreeNode`, `GetByEmailAccountsRequestMessage`, `Datasources`, `ArenaSceneExtraProps`, `S3URI`, `i18n.Message`, `GUID`, `ProtectionRule`, `CopyTask`, `UpdateProjectCommand`, `MDCTextField`, `ChainIndexingAPI`, `SerializationOption`, `HsLayerUtilsService`, `StringEncoding`, `TypeVariable`, `TelegrafContext`, `ThreeSceneService`, `express.NextFunction`, `StrokeOptions`, `mm.INativeTagDict`, `OptionConfig`, `MapLike`, `SConnectableElement`, `QueryEnum`, `IReaderRootState`, `BaseResource`, `HttpCall`, `GameType`, `PaymentIntent`, `ListGrantsRequest`, `UseCaseLike`, `ComponentRuntimeMetaCompact`, `FactPath`, `MenuEvents`, `MerchantService`, `AttachmentResponse`, `SpotifyService`, `solG1`, `LiveListItem`, `AnnotationActionTypes`, `CancellationErrorCode`, `requests.ListOAuthClientCredentialsRequest`, `ServiceAccount`, `EmbeddableStateWithType`, `IdentityArgs`, `ProductVariant`, `CustomBlock`, `NotWrappable`, `MDCAlertControllerImpl`, `Nes`, `AuthorizedRequest`, `Resetter`, `TicketMod`, `BindingWhenOnSyntax`, `NativePlatformDefinition`, `ChatEvent`, `IConnectedNodes`, `AuthClientInterface`, `DebugProtocol.Variable`, `ConvertFn`, `ASSET_CHAIN`, `VisParams`, `IShaderMaterialOptions`, `VuexModuleConstructor`, `ILanguage`, `ISampleToChunkBox`, `ScrollByY`, `Bluebird`, `Enable`, `NSIndexPath`, `EntryNode`, `SignatureHelpItems`, `IRenderParameters`, `CONNECTION_STATUS`, `NonNullableSize`, `FocusedCellCoordinates`, `Challenge`, `MarkdownTableRow`, `SeriesComposition`, `CourseUser`, `EuiTheme`, `IncomingRequest`, `CanvasType`, `OasParameter`, `ValueAttributeObserver`, `NextPageWithLayout`, `UpdateProjectCommandOutput`, `Metrics`, `EntityResolver`, `IPackageDescriptor`, `ToggleableActionParams`, `ITiledObject`, `nsIFile`, `SParentElement`, `WeapResource`, `WidgetFactory`, `AgAxisLabelFormatterParams`, `SettingsRow`, `Caller`, `UpdatedLazyBuildCtx`, `Events.postframe`, `DataModel.Metadata`, `MODEL`, `EventEmitter2`, `ITemplates`, `SqlOutputContentProvider`, `SocketIOGraphQLClient`, `SignedMessageWithOnePassphrase`, `ITkeyError`, `SessionToken`, `SemanticTokensLegend`, `tabItem`, `row`, `TextStyleProps`, `WebSocket.CloseEvent`, `IterationState`, `SpannedString`, `IBoxPlotData`, `BlockWithChildren`, `BuiltIns`, `BreakOrContinueStatement`, `WrapEnum`, `VBox`, `FilesystemDirectoryNode`, `RowParser`, `MoonBoard`, `PeerContext`, `D3Interpolator`, `NavParams`, `UIMillStorage`, `PBBox`, `ValidationConstraints`, `FcModel`, `GraphQLService`, `MkReplaceFuncStore`, `AcceptResult`, `Tilemap`, `IEventHandlerData`, `LogGroup`, `IFabricWallet`, `https.Server`, `PartitionKeyParams`, `PartialCanvasThemePalette`, `Hotspot`, `IncrementalParser.SyntaxCursor`, `FlattenLayerArgs`, `Calendar_Contracts.CalendarEvent`, `AwilixContainer`, `ClassWeightMap`, `Date`, `DecimalAdjustOptions`, `EdgeLabels`, `Insertion`, `JSDocSignature`, `ContentDescriptorRequestOptions`, `PluginApi`, `AppInstance`, `KeyData`, `KvMap`, `ResourceItemXML`, `Deletion`, `DispatchPropsOfControl`, `SizeObject`, `LocalizableString`, `Z`, `TreeViewItem`, `PDFName`, `TAttrs`, `Ret`, `QueryPaymentsRequest`, `DateTimeService`, `CallbackHandler`, `PvsioEvaluatorCommand`, `FormlyFieldConfig`, `ISettingsIndexer`, `Consola`, `SearchFilterConfig`, `IRenderService`, `MessageTypes`, `GraphQLHOC`, `t.Context`, `DocTableLegacyProps`, `SavedObjectsImportRetry`, `IReducerMap`, `IStructuredLicense`, `DeleteProfile`, `Counter2`, `ISqlCommandParameters`, `CallableConfig`, `StoriesDefaultExport`, `ThemePalette`, `DeleteStreamCommandInput`, `SecretData`, `DropdownService`, `TypeCondition`, `ITodosState`, `DeliveryTarget`, `InsightModel`, `IReduxStore`, `RefCallback`, `MagnetarInstance`, `PermissionsResource`, `TsOptionEngineContext`, `IModelTransformer`, `Rect`, `GetBotChannelAssociationsCommandInput`, `RulesByType`, `PopoverContextValue`, `GfxVertexAttributeDescriptor`, `RequiredStringSchema`, `RTMClient`, `ValidatorOptions`, `CreateParameterGroupCommandInput`, `ArrowCallableParameter`, `Range3d`, `ts.TypeAssertion`, `DetectionResultRowIndicatorColumn`, `ModalProps`, `ResourceDefinition`, `BinarySearchTreeNode`, `DateWrapperFormatOptions`, `Clients`, `SpotSession`, `ModuleConfig`, `CustomCameraControls`, `QueryOptions`, `Move`, `SpawnOptions`, `AllureConfig`, `PannerNode`, `OpenSearchDashboardsDatatableRow`, `UIBezierPath`, `ApiNotificationSender`, `TypedUseSelectorHook`, `ManagementApp`, `MenuListProps`, `ContentSource`, `PeerCertificate`, `ImageGLRenderer`, `SortParam`, `DescribeReservedInstancesCommandInput`, `CredentialManager`, `UpdateWebhookCommandInput`, `Pocket`, `AttributeMap`, `MagickInputFile`, `Dialogue.Config`, `Highcharts.JSONType`, `ProjectTemplate`, `ListColumnSetting`, `MeetingHistoryState`, `SliderCheckPoint`, `ControllerProps`, `CrowbarFont`, `StudioVersion`, `LogInRequest`, `IBasicProtocolMessage`, `IGetExpenseInput`, `NoncondexpressionContext`, `RecordFormat`, `IProtonAccount`, `ExpressionFunctionOpenSearchDashboardsContext`, `ParseTreePattern`, `NgElementConstructor`, `MatSliderChange`, `RemoteSourceProvider`, `Insert`, `CreateConnectionRequest`, `ProjectActions`, `RandomSource`, `ITimeLog`, `PropName`, `Validation`, `ActionParamException`, `CoreTypes.PercentLengthType`, `UrlWithParsedQuery`, `HTMLScLoadingSpinnerElement`, `IBase`, `TermRows`, `ToneAudioNode`, `BlobInfo`, `SubMenuProps`, `AnimatableElement`, `DialogProps`, `requests.ListAppCatalogListingsRequest`, `MockReaction`, `CachedUpdate`, `GfxSamplerDescriptor`, `NeovimClient`, `AccessorDeclaration`, `RBNFSet`, `IContextView`, `IndicatorAggregateArithmetic`, `ReflectiveInjector`, `ProxyInstance`, `FireCMSContext`, `IEntries`, `IndexedColumn`, `ClientOptions`, `CloudServiceResponse`, `FasterqQueueModel`, `PrEntity`, `ModelTemplate`, `UpworkService`, `ServiceExitStatus`, `d.ComponentCompilerData`, `SendView`, `SidePanelRanking`, `Mutex`, `PropsWithUse`, `d.InMemoryFileSystem`, `ts.server.Project`, `PgNotifyContext`, `AddonActions`, `AAAARecord`, `EmitAndSemanticDiagnosticsBuilderProgram`, `flatbuffers.ByteBuffer`, `HTMLMediaElement`, `StripeAddress`, `PromisedAnswer`, `XYZProps`, `DiContainer`, `VectorView`, `PropertyTreeNodeHTMLElement`, `vscode.TextEdit`, `CommentData`, `K8sManagement`, `NETWORK_NAME`, `PermutationSegment`, `TSender`, `GenericDefaultSecond`, `types.TextDocumentIdentifier`, `HelpList`, `MDBModalRef`, `NumericB`, `PatternAsNode`, `tracing.ReadableSpan`, `RawShaderMaterialParameters`, `Classifier`, `MockedResponseData`, `AuthController`, `FIRAuthDataResult`, `EngineArgs.PlanMigrationInput`, `MagentoAggregation`, `TestExporter`, `AcronymStyleOptions`, `BackgroundState`, `QueuedEventGroup`, `FlushConfig`, `TavernsI18nType`, `CreateError`, `OrientedBox3`, `MethodArgsRegistry`, `ConfigValues`, `NodeEvent`, `BucketAggParam`, `CollisionSolver`, `DimensionDetails`, `NextCurrentlyOpened`, `FtrProviderContext`, `Netlify`, `CreateInstanceProfileCommandInput`, `CompiledExecutable`, `TaskArguments`, `FilterMode`, `CredentialResponseCoordinator`, `requests.ListFastConnectProviderVirtualCircuitBandwidthShapesRequest`, `GraphinProps`, `TargetTrackingConfiguration`, `PackageData`, `DaffLoginInfo`, `SwingRopePoint`, `SFAMaterial`, `G1`, `NodeStatus`, `FeaturePipelineState`, `TransferItemFlatNode`, `ReferencedSymbolDefinitionInfo`, `RpcConnection`, `BigBitFieldResolvable`, `IServiceProvider`, `EventActionHandler`, `ListBase`, `HashTag`, `esbuild.OnResolveResult`, `VideoConverterFactory`, `CreateServiceCommandInput`, `BrandC`, `Order`, `CRDTArray`, `MicrosoftSynapseWorkspacesSqlPoolsResources`, `TeleportService`, `MockBroadcastService`, `DirectiveDefinition`, `IServer`, `RMCommandInfo`, `IMidwayApplication`, `ServiceTreeItem`, `PanResponderInstance`, `yubo.MainReducer`, `RecentlyClosedEditor`, `BasePlugin`, `ScriptableContext`, `DomainCategory`, `ControlFlowEnd`, `SVAddr`, `TimelineNonEcsData`, `DocReference`, `NormalizedNodeType`, `ICandidateFeedback`, `SyncDB`, `MockStoreEnhanced`, `CollectionFactory`, `PipelineValue`, `AssertLocationV2`, `TFLiteModel`, `ProjectInformationStub`, `ManifestInstance`, `AdBreak`, `ToolManagerService`, `UtilitiesService`, `WebhookRequest`, `TypeAliasDeclarationStructure`, `DetectedCompiler`, `TsChart`, `RBNFDecimalFormatter`, `TileObject`, `LogService`, `ChannelStoreEntry`, `Level2`, `CommitDetails`, `IDeferredPromise`, `PresentationPreview`, `ProjectFn2`, `TFS_Core_Contracts.TeamContext`, `TelemetryPluginStart`, `QueryHistoryNode`, `ColumnApi`, `AttestationModel`, `Unwatch`, `ObservableEither`, `EventData`, `ValueOf`, `BatteryCCReport`, `UrlPattern`, `KnownMediaType`, `FailedRequestType`, `ComboEventPayload`, `BuildHandlerArguments`, `Should`, `ThingType`, `CodeSnippet`, `ILeaguePrices`, `PlatformPath`, `IPipeline`, `messages.Step`, `RedisService`, `KonstColor`, `RouteQuoteTradeContext`, `SecretsManager`, `DragRefConfig`, `VideoFormat`, `IterableFactory`, `HandlerFn`, `ImageAndTrailImage`, `ProviderObservedParams`, `AnyWire`, `ExtractorMessage`, `ScaleOptions`, `FindRoute`, `MinecraftFolder`, `LchaColor`, `IViewPortItem`, `DeleteProfileCommandInput`, `MDCActivityIndicator`, `IFibraNgRedux`, `TransactionFactory`, `paper.PathItem`, `ShadowCastingLight`, `FieldValue`, `DotenvParseOutput`, `JSONRPCResponse`, `WheelDeltaMode`, `ex.PostDrawEvent`, `IInternalParticipant`, `CDP.Client`, `FlatTree`, `ConfigValueChangeAction`, `SAO`, `Card`, `DealService`, `$N.IBaseNode`, `CellEditor.CellConfig`, `Foam`, `ITrackDescription`, `types.AzExtLocation`, `CpuState`, `ConcreteLaunchOptions`, `Oid`, `MatchOptions`, `AttachedPipettesByMount`, `BabelDescriptor`, `DeleteResourcePolicyCommandOutput`, `ListComprehensionNode`, `ng.IRootScopeService`, `IMapSourceProvidersConfig`, `ResolveModuleIdResults`, `IBifrostAccount`, `StringToNumberSyntax`, `TextAlignment`, `Dialogic.IdentityOptions`, `PartialCliOptions`, `ModelNode`, `ArianeeTokenId`, `MapSimulation3D`, `ActionButton`, `ConfigActionTypes`, `SetStatus`, `UserExtendedInfo`, `TestPhysicalObject`, `TestAssertionStatus`, `RopInfo`, `MeshPhongMaterial`, `capnp.Pointer`, `HdErc20PaymentsConfig`, `SendCommandCommandInput`, `FeatureFilter`, `ITemplateId`, `FinalTask`, `ActionHandler`, `TestDataService`, `RestoreResults`, `EqualityDeciderInput`, `Phaser.GameObjects.GameObject`, `DocumentDataExt`, `NavProps`, `XPCOM.nsISupports`, `ITenant`, `CancelJobCommandInput`, `CreateDatabaseResponse`, `DnsResponse`, `RuntimeEngine`, `Overrides`, `TSelector`, `FabricEnvironment`, `StatefulSet`, `QueryKeySelector`, `Searcher`, `SimpleRenderer`, `TSpy`, `IAccessor`, `BarcodeFormat`, `GL`, `ReaderObservable`, `TestMarker`, `MonacoEditorModel`, `IFlexProps`, `IIdentity`, `ColorRGBA`, `ILayoutContextProps`, `CreateWorkflowCommandInput`, `ClassDeclaration`, `Asm`, `ListVaultReplicasRequest`, `KEXFailType`, `TrackedImportSymbol`, `MockValidatorsContract`, `TemplateEngine`, `RdsMetricChange`, `ChangeSetItem`, `PluginObj`, `Chai.AssertionStatic`, `ESCalendarInterval`, `ScreenType`, `ByteStr`, `Cue`, `StatsChunk`, `OptimizeCssOutput`, `CallbackMethod`, `CreateRegionPureReturnValue`, `requests.ListInstanceDevicesRequest`, `NeedleResponse`, `CreateVpcLinkCommandInput`, `TraceData`, `DatasourceSuggestion`, `IOptimized`, `DeepReadonlyObject`, `RequestInterface`, `SessionRefreshRequest_VarsEntry`, `ast.LookupNode`, `Konva.Stage`, `Liquidator`, `InMemoryPubSub`, `Compressors`, `PiLogger`, `TSClient`, `ContextualIdentity`, `ObjectCacheEntry`, `EventFieldInfo`, `ast.RunNode`, `QueryEngineRequestHeaders`, `NotificationHandler0`, `DateFormatOptions`, `StructureTower`, `EggAppInfo`, `CustomDocumentStoreEntry`, `MenuSurface`, `FileSystemEntry`, `ex.Engine`, `MDCNotchedOutlineAdapter`, `AbstractLogger`, `ThyDragDropEvent`, `MidiNote`, `ScenarioService`, `TaroText`, `IconsName`, `ListStacksRequest`, `PickerController`, `App.windows.IWindowModuleMap`, `CohortState`, `Cypress.PluginConfig`, `SubtitlesFileWithTrack`, `RoarrGlobalState`, `CalculatedBlock`, `TProvider`, `CreatePortalCommandInput`, `typeOfRow`, `PutEmailIdentityFeedbackAttributesCommandInput`, `ArtColumn`, `SubtitlesTrack`, `MdcChipAction`, `AsyncCPUBackend`, `ProviderMessage`, `Ver`, `deployData`, `IOneArgFunction`, `ApolloClient`, `LocalizedCountry`, `InternalTransition`, `FontProps`, `ILiteral`, `IVector2`, `DirectiveNode`, `SearchContext`, `d.LoggerTimeSpan`, `HsStylerService`, `OpPathTree`, `Phrase`, `RSPOutput`, `IValue`, `DeleteRouteCommandInput`, `EventName`, `vscode.DiagnosticCollection`, `ScreenshotCache`, `Expect`, `RequestPresigningArguments`, `MotionState`, `DetectEntitiesCommandInput`, `FirebaseAuth`, `MindNodeModel`, `SpaceStyleProps`, `DescribeTaskCommandInput`, `RegexDialect`, `PartialEntityCollection`, `ProviderWithScope`, `IHttpRequestOptions`, `CommonWrapper`, `MultipleDeclaration`, `EntityBuilder`, `ScanSegment`, `Skeleton`, `SignerPayloadJSON`, `BezierCurveBase`, `GenericDraweeHierarchyBuilder`, `ResourcePack`, `BridgeDeploy`, `Runner.Utils`, `CommandCreator`, `GetOperationRequest`, `CreateProcessOption`, `DashboardListingPage`, `AzureCustomVisionProvider`, `vscode.Range`, `DaffCartShippingRateFactory`, `Composite`, `AllowedModifyField`, `NestFastifyApplication`, `WFSerialization`, `EmbeddedOptions`, `TestReadable`, `Distortion`, `StatsGetterConfig`, `AppIdentity`, `ts.ArrayLiteralExpression`, `SkygearError`, `ActivityStreamsModel`, `PanGestureHandlerStateChangeEvent`, `RewriteRequestCase`, `ExpressRouteCrossConnection`, `EmbeddingLayerArgs`, `PrismaClientInitializationError`, `AppController`, `AccountType`, `PostCollector`, `SEOProps`, `MSIVmTokenCredentials`, `IItemRenderData`, `NexusInterfaceTypeDef`, `CmsEditorContentModel`, `Rx.Notification`, `DailyApiRequest`, `Palette`, `Texlist`, `EffectOptions`, `ILayout`, `PluginHooks`, `Raffle`, `CustomDomain`, `ViewerModel`, `ARAddOptions`, `ReplayEntity`, `DashboardType`, `ng.IHttpPromiseCallbackArg`, `B1`, `LabelAccessor`, `HitTestResult`, `GetApplicationResponse`, `HoldingUpdatedArg`, `OtCommand`, `ErrorLocation`, `ast.NodeList`, `ScalarActivity`, `HandlerStateChangeEvent`, `IndexedGeometry`, `SequenceKey`, `ConditionOperatorName`, `PBXFile`, `DefaultRootState`, `ProxyObject`, `NamespaceExportDeclaration`, `CBlock`, `d.RenderNode`, `TabNavigationState`, `TemplateConfig`, `GaxiosPromise`, `AxeResultConverterOptions`, `CollateContext`, `UserScriptGenerator`, `Listing_2`, `OutputConfig`, `ChatBoxStateModel`, `JobType`, `OrderStatus`, `GenericAPIResponse`, `HotkeysService`, `Dexie`, `FieldPlugin`, `http.ServerRequest`, `ExtensionService`, `HSD_TObj_Instance`, `DestinationSearchResult`, `InsightsResult`, `RequestService`, `HistoryService`, `HttpRequester`, `DescribeConnectorProfilesCommandInput`, `Session.ISession`, `TallyType`, `G2TimelineData`, `BackgroundTrack`, `Neuron`, `AsyncCommandResult`, `InputCurrencyOutput`, `ApolloPersistOptions`, `HTMLDocument`, `CreateLoadBalancerCommandInput`, `IntervalContext`, `PublishArgs`, `AxisAlignedBox3d`, `ChatThreadClient`, `XMLElementUtil`, `UpdateTemplateCommandInput`, `IJobPreset`, `JSONSchema4`, `DirectoryNode`, `LobbyHouse`, `TrackedStorage`, `PeriodModel`, `PieLayerState`, `superagent.Response`, `Force`, `RgbVisConfig`, `MapSet`, `SearchParams`, `T0`, `StreamWithSend`, `SettingValue`, `ListRenderItemInfo`, `PlansCategories`, `GrammarToken`, `FetchService`, `DeviceState`, `ReactQueryConfig`, `ProxyRequest`, `DeleteTokenCommandInput`, `MatFormField`, `PathProps`, `CombatEncounter`, `ParseTreeResult`, `WebSqlTx`, `SubmissionDetailEntity`, `PopoverOptions`, `BorderRadius`, `DockerApi`, `ComponentDoc`, `UntagResourceCommand`, `TreeNodeItem`, `ConcurrentWorkerSet`, `ICreateResult`, `BinOp`, `CPS`, `XmlMapsXmlNameCommandInput`, `VRMHumanoid`, `VNode`, `ResolvedFunctionType`, `FastFormFieldComponent`, `XSDXMLNode`, `DeclarationReference`, `HttpResponse`, `OutputFlags`, `FunctionServices`, `EventsFnOptions`, `apid.GetRuleOption`, `BuildLevel`, `ContextState`, `IOpenAPI`, `cytoscape.SingularElementArgument`, `ProductProps`, `Import.Options`, `GanttViewOptions`, `ExampleFlatNode`, `GitHubActions`, `ReleaseTag`, `GuildConfig`, `AnkiConnectRequest`, `Vocabulary`, `B15`, `CommandParams`, `ListApplicationsCommand`, `LocalWallet`, `InterfaceWithDictionary`, `DegreeType`, `StoreSetter`, `GestureResponderEvent`, `EbsBlockDevice`, `ScoreStrategy`, `OptionEquipped`, `WaveShaperNode`, `XRWebGLLayer`, `ImportDeclaration`, `ShellExecResult`, `PermissionLevel`, `CaseOrDefaultClause`, `AsBodiless`, `Webhook`, `StateDictionary`, `SequenceComponent`, `MyModule`, `SettingsFile`, `AdminState`, `VNodeArrayChildren`, `MultiSigHashMode`, `IFilter`, `MessageModel`, `OpenAPI.Schema`, `ClassList`, `NamespaceOperatorDecl`, `WechatQRCodeEntity`, `SVBool`, `WebsocketInsider`, `LiveEventMessage`, `ProseNodeType`, `BoundEventAst`, `SendPropDefinition`, `NodeConfig`, `UseMap`, `CustomVariant`, `Discord.Guild`, `LogAnalyticsSourceMetric`, `LocationAccessor`, `TypeScriptSubstitutionFlags`, `HalLink`, `DeviceSummary`, `FunctionToActionsMap`, `ListTemplatesCommandInput`, `PiElementReference`, `IRequestResponse`, `TransitionFn`, `WebpackPluginInstance`, `CacheContainer`, `AggregatedApiCall`, `WebsocketClient`, `SwimlaneActionConnector`, `ParamMetadata`, `CylinderGeometry`, `ScanResultResponse`, `ReviewerReadModel`, `ResetAction`, `CourseService`, `providers.Log`, `RGroup`, `WaitForYellowSourceState`, `MutationHookOptions`, `FilterOf`, `evaluate.Options`, `TagEventType`, `AmdModule`, `LightArea`, `StartExperimentCommandInput`, `MouseButton`, `SubscriptionHolder`, `Tensor3D`, `OpenApiParameter`, `EmotionCache`, `MapSubLayerProps`, `IVimStyle`, `utils.RepositoryManager`, `EdiDocumentConfiguration`, `StripeElements`, `interfaces.Lookup`, `SignedDebtOrder`, `TrialType`, `AccountState`, `ValidatorFunction`, `FunctionData`, `MagickFile`, `SGraph`, `IDateColumn`, `StatusEntry`, `Passenger`, `AudioItem`, `tBootstrapFn`, `LiteralObject`, `code.TextDocument`, `DialogForm`, `InitiateOptions`, `WetLanguage`, `BaseWeb3Client`, `QuerySnapshot`, `SchemaModel`, `Continuation`, `DeploymentExecutor`, `UiRequest`, `d.OptimizeCssOutput`, `ExpressionRendererRegistry`, `NodeCryptoCreateDecipher`, `PivotGroupByConfig`, `OptionsProps`, `GradientStop`, `PortalOutlet`, `Path7`, `XHRoptions`, `TYPE`, `KnownTokenMap`, `SpinnerService`, `CalendarViewEventTemporaryEvent`, `Puzzle`, `SecureStore`, `ImportedNamespace`, `LongNum`, `Score`, `IExecutionContext`, `ButtonState`, `Service`, `BrowserEvent`, `IMappingFieldInfo`, `HelpCenterAuthorService`, `RecordList`, `Konva.Shape`, `WsPresentationService`, `RegexComponent`, `PdfObjectConverter`, `Prompter`, `NavigationBarItem`, `PromptItemViewModel`, `Loc`, `ExpressionsSetup`, `CreateDataSourceCommandInput`, `ListNodePoolsRequest`, `PolicyRates`, `LunarYear`, `FieldDeclaration`, `VideoFile`, `IModulePatcher`, `MockERC20TokenContract`, `LogFn`, `SwitchCallback`, `JsonRpcHandlerFunc`, `TexCoord`, `TemplatingEngine`, `BadgeProps`, `ISiteDesign`, `GeoProjection`, `ThyPopoverRef`, `TrustToken`, `TokensPrices`, `JSX.Element`, `ParameterComputeType`, `StateChannel`, `SpecFun`, `ParseSourceSpan`, `Runner`, `ExpandedAnimator`, `GetChannelMessageCommandInput`, `SharedContents`, `PlanetaryTrack`, `GetBucketLifecycleConfigurationCommandInput`, `FindProjectsDto`, `IntLiteralNode`, `VectorKeyframeTrack`, `KeyProvider`, `IPathMapping`, `ContainersModel`, `OverridableComponent`, `CompoundMeasurement`, `IInternalEvent`, `ScoreHeader`, `GameConfig`, `shell.Shell`, `BabelPlainChain`, `TimestampShape`, `ITenantManager`, `INativeTagDict`, `Deno.ListenOptions`, `Proxy`, `PropConfigCollection`, `d.FsReaddirItem`, `WebView`, `CasePostRequest`, `TestFunctionImportSharedEntityReturnTypeParameters`, `ChatResponse`, `HeaderViewProps`, `AllocationItem`, `ProtocolConformance`, `Int16`, `InspectFormat`, `Viewpoint`, `VoteChoices`, `ITypedResponse`, `thrift.IStructCodec`, `BasePoint`, `ReleaseGoldConfig`, `OnGestureEvent`, `Is`, `ExternalWriter`, `ChainNodeFactory`, `SwappedToken`, `OpenApiDocument`, `NotAuthorizedException`, `THREE.BufferGeometry`, `PubsubMessage`, `Calendar_Contracts.IEventQuery`, `ABLParameter`, `NotifyQueueState`, `TypeAllocator`, `CLIArgumentType`, `CausalRepoBranchSettings`, `ThemableDecorationRenderOptions`, `IUnitModel`, `EvaluatedExprNode`, `ISessionBoundContext`, `IGraph`, `ImmutableObjective`, `ListProjectsRequest`, `FieldModel`, `PutEmailIdentityMailFromAttributesCommandInput`, `Point3F`, `T6`, `GfxVertexBufferDescriptor`, `ZWaveFeature`, `ITrackStateTree`, `ToolbarIconButtonProps`, `EdiSegment`, `TranslationAction`, `ParameterInvalidReason`, `SnapshotOptions`, `BalmEntry`, `FloatOptions`, `IAttachment`, `ExtensionPackage`, `AgreementData`, `DocumentModel`, `WearOsListView`, `VisibilityState`, `MigrateAction`, `MockRepository`, `ContractDBTransaction`, `ListNode`, `GlobalSettings`, `ToolbarTest`, `IMdcSegmentedButtonSegmentElement`, `TickAutomationEvent`, `HostLabelInput`, `DaemonConfig`, `TaskUser`, `ExcaliburGraphicsContextOptions`, `TypedKeyInfo`, `EmailTemplateService`, `NumberType`, `HTMLIFrameElement`, `DaffProduct`, `RouterStateSnapshot`, `Pluggable`, `ListOperationsCommandInput`, `AvailabilityStatus`, `MiddlewareMetadata`, `IRequestContext`, `ReindexService`, `AppEvent`, `ReadLine`, `TextureInputGX`, `SharedElementNode`, `X12Segment`, `WithdrawalMonitorObject`, `TransactionResponse`, `IPrimaryKey`, `ISparqlBindingResult`, `EventbusService`, `HTMLCmpLabelElement`, `schema.Document`, `PrivateThreadAndExtras`, `SubCommand`, `TNSCanvasRenderingContext`, `TransactionUnsigned`, `RealtimeEditMode`, `ImportParts`, `MeetingAdapterStateChangedHandler`, `ProxyServer`, `sast.Node`, `UrlService`, `Gradient`, `CacheData`, `xml.Position`, `ExecEnv`, `AnomalyRecordDoc`, `AggTypesDependencies`, `MirrorDocumentSnapshot`, `StateSnapshot`, `TopLevelDeclarationStatement`, `IRequestOption`, `AaiChannelItem`, `PartiallyEmittedExpression`, `FSService`, `PromiEvent`, `FontFace`, `FieldDefn`, `Graphics.Texture`, `SourceRule`, `TypescriptAst`, `CurrencyValue`, `IDraggableData`, `DDiscord`, `IFunctionCallArgument`, `ec`, `ListChannelMessagesRequest`, `FileSystemReader`, `ColumnInfo`, `long`, `PopulatedTagDoc`, `Entity.Account`, `PartialErrorContinuation`, `BasicCCReport`, `OverflowModel`, `ListManagementAgentInstallKeysRequest`, `AmmContractWrapper`, `SelectMenuInteraction`, `Ycm`, `ProfileService`, `GetCoordinate`, `DoubleMapCallback`, `JsonaValue`, `ConditionalBooleanValue`, `PropertyOptions`, `EventProvider`, `SxToken`, `TranslateContainerConfig`, `LogConfiguration`, `ValueMetadataNumeric`, `DescribeEndpointsResponse`, `ts.ForOfStatement`, `ObjectStorageSourceDetails`, `UAParserInstance`, `TemplateAnalyzer`, `CreateClusterCommandOutput`, `NgForageConfig`, `ServiceRecognizerBase`, `StagePanelManager`, `OptionNode`, `BScrollOptions`, `QuerySettings`, `IExpressionLoaderParams`, `InternalComputedContext`, `RegistrationDTO`, `EventmitHandler`, `DB`, `Precondition`, `AppPage`, `CCValueOptions`, `WriteFileOptions`, `Rand`, `IAvatarBuilder`, `ProtocolConformanceMap`, `DocsService`, `CaseExpr`, `Indent`, `ResolvedFile`, `CallSignatureInfo`, `AppEvent.Stream`, `FrameworkOptions`, `EmitFileNames`, `SavedObjectsClientWrapperFactory`, `LabelNode`, `DataLakePrincipal`, `WorkerServiceProtocol.RequestMessage`, `FnN`, `WrappedAnalyticsEvent`, `ContentShareObserver`, `MixedIdType`, `NodeToVisit`, `CustomerDTO`, `ControlProps`, `SyncResult`, `DeleteTagsCommand`, `ExecutorOptions`, `TSParseResult`, `ResourceInUseException`, `PartialBotsState`, `RootComponentRegistry`, `Canvg`, `EditorRange`, `LowAndHighXY`, `Greeter`, `RedHeaderField`, `FormField`, `ICalAttendee`, `CdkTreeNodeDef`, `ClassVarInfo`, `ProofBranch`, `ProjectionOptions`, `TearrData`, `TTurnAction`, `Postprocessor`, `CSSSource`, `ProgressData`, `DataWithPosition`, `MetaSchema`, `monaco.editor.IEditorMouseEvent`, `JSX.TargetedEvent`, `PragmaValueContext`, `SimpleNotification`, `UserContextType`, `Rect2D`, `ICourseModel`, `FormContext`, `PositionPlacement`, `OmvFeatureModifier`, `MatchRule`, `DefaultEditorAggParamProps`, `TileBoundingBox`, `MemberAccessNode`, `IDType`, `NavigationPublicPluginSetup`, `AuthStrategy`, `GenericAnalyzer.Dictionary`, `CheckIdTaskDto`, `WhitePage`, `FirenvimElement`, `MutationEvent`, `JsonValue`, `ConfigurableConstraint`, `NumericalRange0`, `EquipmentDelay`, `HashedItemStore`, `d.BuildConditionals`, `DidChangeConfigurationParams`, `ListApplicationVersionsCommandInput`, `MarkdownTheme`, `ServerCapabilities`, `SimpleMap`, `FileOpenFlags`, `ApplicationInfo`, `Highcharts.AnnotationPointType`, `PaymentResource`, `ProcessHandler`, `UpdateImportInfo`, `BlinkerDevice`, `X12Parser`, `BannerState`, `CreateViewNode`, `IClassParts`, `NormalizedComponentOptions`, `Timeout`, `CalibrationState`, `ExistsExpression`, `ThyNavLinkDirective`, `ListSchemasResponse`, `DOMStringList`, `GithubRelease`, `AugmentedProvider`, `D2rStash`, `CellStyle`, `ResourceManagementClient`, `ExtractGetters`, `CompletionResults`, `TabName`, `ShallowMerge`, `CreateTargetResponderRecipeDetails`, `FeltReport`, `ClientReadableStream`, `NormalizedFilter`, `ServerDto`, `AddApplicationCloudWatchLoggingOptionCommandInput`, `def.View`, `ControlComponentProps`, `TypedFormGroup`, `BitbucketUserEntity`, `requests.ListAlertRulesRequest`, `ILinkedListNode`, `ClassEntry`, `CardInterface`, `LooseObject`, `IdentityMetadataWrapper`, `GfxQueryPoolType`, `IMyFavouriteItem`, `GfxSwapChain`, `ControllerInterface`, `IXElementResult`, `PermutationListEntryWithTrackingData`, `AST.MustacheStatement`, `BucketAggTypeConfig`, `PathSegment`, `ExchangePositionInput`, `TimeoutTask`, `DropedProps`, `LayerInfo`, `ProtocolRequestType0`, `DynamicEntityService`, `App`, `DAVCalendar`, `ObservableSet`, `CompletionParams`, `TLabelName`, `CreateSchemaCommandInput`, `MatchmakerAdd`, `PiBinaryExpression`, `PassphraseError`, `PriceLineOptions`, `MetadataField`, `IOrganization`, `ts.LiteralType`, `CompactOrCondition`, `HubLinksWebPart`, `Q.Promise`, `ChannelAnnouncementMessage`, `ResultValue`, `PolynomialID`, `PluginsContainer`, `LoggingEvent`, `ScriptKind`, `FetcherOptions`, `Submesh`, `UnitConversionSpec`, `OnChangeType`, `TypedQuery`, `ThresholdedReLULayerArgs`, `RequestMessage`, `ActivityPropertyDescriptor`, `CfnRole`, `UserFunctionSignature`, `A3`, `TActorParent`, `PickScaleConfigWithoutType`, `Writer`, `TreeSitterDocument`, `ColorKey`, `Tutorial`, `MeetingSessionStatusCode`, `BrowseEntrySearchOptions`, `NodeCanvasRenderingContext2D`, `Toolkit`, `Multiaddr`, `IndicatorQueryResp`, `AdapterPool`, `SpawnResult`, `CachedValue`, `IPerfMinMax`, `ExecuteCommandParams`, `MintInfo`, `Aai20SchemaDefinition`, `emailAuthentication.Table`, `VocabularyEntryDetail`, `ListSuppressionsRequest`, `SanitizedAlert`, `ScopedObjectContext`, `SessionStore`, `DeleteVpcLinkCommandInput`, `DesktopCommand`, `Popup`, `LocalizedText`, `Paper`, `EndpointInput`, `VirtualCloudNetwork`, `DatabaseCredentials`, `VirtualContestInfo`, `PropertyDescriptor`, `ICodeEditor`, `ShapeAttrs`, `requests.ListPreauthenticatedRequestsRequest`, `InstallState`, `WorkspaceData`, `ConfigParameterFilter`, `messages.Tag`, `angular.IDeferred`, `TableFactory`, `SceneRenderer`, `IDiscordPuppet`, `LocalizeRouterSettings`, `StripeEntry`, `LedgerDigestUploadsName`, `MutableChange`, `MyView`, `SectionType`, `BreakpointKeys`, `CompileKey`, `JSONInput`, `ChromeNavControl`, `ITKeyApi`, `DrawCall`, `VaultData`, `BinarySwitchCCReport`, `UserRole`, `TestCLI`, `JsonRpc`, `NotificationLevel`, `ModeAwareCache`, `WorkspaceChange`, `React.HTMLAttributes`, `BlankLineConfig`, `GQtyConfig`, `PaginationModel`, `vscode.SymbolInformation`, `TodoComment`, `SVNumeric`, `MIRType`, `DurableOrchestrationClient`, `DeleteDedicatedIpPoolCommandInput`, `InstanceState`, `GraphicsComponent`, `CeloContract`, `SetLanguage`, `FieldFormatMap`, `ElementNode`, `Apple2IO`, `IGLTFLoaderData`, `ListUI`, `IpcMain`, `WalletEventType`, `SimpleExprContext`, `CreateProfileCommandInput`, `CreateAccessPointCommandInput`, `AzurePipelinesYaml`, `HistoryManager`, `ExtenderHandler`, `GetPackageVersionHistoryCommandInput`, `PathToProp`, `HandleEvent`, `MdcSnackbarConfig`, `NewPerspective`, `MenuNode`, `Vec2Like`, `SimpleAllocation`, `DaprManager`, `BarChartDataPoint`, `QueryExecutorFn`, `StateFromFunctionReturningPromise`, `ExpandedNodeId`, `ContextMenuFormProps`, `IGlobalEvent`, `tsc.Type`, `IgApiClient`, `PngEmbedder`, `MultiChannelAssociationCCAPI`, `ZeroXOrder`, `Todo_todo`, `CallbackContext`, `Columns`, `Newable`, `Fruit`, `GltfLoadOption`, `ExecException`, `SpatialDropout1D`, `ExcalideckEditorState`, `NormalizedIdentifierDescriptor`, `UseFetchReturn`, `ISubscribable`, `ConfiguredProject`, `SelectedItem`, `ReverseQueryInterface`, `IProcesses`, `Obstacle`, `SourceAwareResolverContext`, `ThisAddon`, `auth.AuthenticationDetailsProvider`, `TSLintAutofixEdit`, `PanelSocket`, `DiagnosticsLogger`, `IPriceAxisView`, `AggsSetup`, `SetterOrUpdater`, `IntPairMap`, `tf.Tensor2D`, `StandartParams`, `Int64`, `IItemAddResult`, `webpack.Stats`, `State.Transaction`, `def.Vec4`, `PutConfigurationSetSendingOptionsCommandInput`, `EmitterConfig`, `Events.postupdate`, `DefsElementMap`, `Shall`, `ConnectionTransport`, `OperatorFunction`, `ModalHelper`, `FocusZone`, `BuilderProgram`, `RenderingContext`, `DraggedItem`, `Notifire`, `YoutubeRawData`, `EntitySprite`, `TestModel`, `ScriptParametersResolver`, `XUL.chromeWindow`, `UpdateManyParams`, `RuleDefinition`, `P2PNodeInfo`, `CreateDomainCommandInput`, `KeyPairTronPayments`, `IDataType`, `StructuredAssignementPrimitive`, `OptionGroups`, `IDocumentOptions`, `FetchError`, `NodeListOf`, `PaletteConfig`, `UgoiraInfo`, `StoreKey`, `MessageSender`, `HttpResponseMessage`, `TextInputProps`, `OcpuUtilizationInfo`, `Collision`, `StoreDefinition`, `TestElement`, `AlterTableExecutor`, `FolderOrNote`, `IOAuth2Options`, `IFontFaceOptions`, `Current`, `IFormPageState`, `BitwiseExpressionViewModel`, `CustomPaletteState`, `WordcloudPoint`, `ColorSet`, `FileRef`, `DeleteClusterCommandOutput`, `RBNFCollector`, `LabeledStatement`, `DeepMapAsyncResult`, `HeaderInfo`, `FeaturesService`, `NodeDefaultCryptographicMaterialsManager`, `GraphDataset`, `IMethod`, `WorkflowClient`, `JsxSelfClosingElement`, `NetworkRecorder`, `Valve`, `SampleCartProduct`, `BinaryReader`, `ActionTree`, `ConverterLogger`, `ListManagementAgentImagesRequest`, `TextEditorPropertiesMain`, `WaitOptions`, `CentralSceneCCConfigurationSet`, `d.OutputTargetDistLazy`, `InvalidFieldError`, `AnimationClip`, `HTTPServer`, `PrRepoIndexStatistics`, `OrgID`, `interfaces.Container`, `IResult`, `ITrackSequence`, `FormatValue`, `EventChannel`, `MessageSeverity`, `VarInfo`, `CryptoFishContract`, `SqrlFeatureSlot`, `GetEnvironentsForProjectEnvironmentResult`, `LayoutResult`, `DueState`, `DryContext`, `ErrorCacheDelta`, `DeploymentStatus`, `ServiceId`, `RTCDtlsTransport`, `Conferences`, `GeometryCommand`, `EncryptedPassphraseObject`, `EventCategoriesMap`, `GraphType`, `WriteTransaction`, `VisTypeIconProps`, `Xml`, `MutationObserverWatcher`, `GenderRepartitionType`, `LFO`, `ClusterVulnerabilityReport`, `SettingsComponent`, `CopyDBClusterSnapshotCommandInput`, `MenuInfo`, `SavedObjectsRawDoc`, `StreamModelWithChannel`, `NodeStore`, `AlterTableNode`, `ISelector`, `A5`, `ISqlEditorResultTab`, `ResponseInterceptor`, `drive_v3.Drive`, `CertificateOptions`, `IActionItemUUID`, `VieraTV`, `RunConfiguration`, `DsDynamicInputModel`, `ISiteDefinitionDocument`, `PutResourcePolicyResponse`, `RobotsTxtOpts`, `FilePreviewDialogConfig`, `IApplicationContext`, `IDateFilter`, `CacheConfig`, `DiscoverIndexPatternProps`, `ListPoliciesResponse`, `CreateEncryptedSavedObjectsMigrationFn`, `IPackageVersionInfo`, `DisplayObjectTransformationProcess`, `NodeController`, `ProductDetailPage`, `Promised`, `SignedMessageWithTwoPassphrases`, `BidirectionalMergeMode`, `JsonLayout`, `AnyJson`, `DescribeEventsResponse`, `TextDocumentItem`, `ClientMenuOrderIdDTO`, `PageListItemProps`, `React.SVGProps`, `RegionGetter`, `IPickState`, `NodeEventHandler`, `CompilerFileWatcherCallback`, `OnFetchEventFn`, `BuildComparator`, `PrismaClientUnknownRequestError`, `ResultView`, `PropertyDocumentationBlock`, `ParamsOf`, `CTX`, `PopoutComponentEvent`, `ITaskRunnerDelegates`, `FleetConfigType`, `GestureConfigReference`, `SpatialControls`, `Loaded`, `Profiles`, `PostCondition`, `CascadeTestResult`, `TransceiverController`, `JsonRpcRequest`, `fc.Arbitrary`, `AffineTransform`, `BaseIO`, `p5.Graphics`, `Hunk`, `SwankRawEvent`, `TransactionAuthField`, `CoreRouteHandlerContext`, `ResizeObserverMock`, `SwitchEventListener`, `AxisComposition`, `SeekQueryResult`, `IStreamPolygon`, `GeometryHandler`, `OptimizerVariable`, `ShaderSemanticsEnum`, `TsunamiContext`, `AccountSteam_VarsEntry`, `PluginActionContext`, `DetectorEnum`, `MetadataRegistryState`, `DataFetcher`, `IUserGroupOptions`, `UndelegateBuilder`, `SubscriberAndCallbacksFor`, `Bettor`, `RadarColumnSeries`, `sinon.SinonStub`, `ListAssociationsCommandInput`, `React.SVGAttributes`, `FargateService`, `Validity`, `InternalStyle`, `Interfaces.RequestConfig`, `AppStateTypes`, `StartDeps`, `RouteWithValidQuote`, `MonitorSummary`, `CausalRepoClient`, `QueryServiceSetupDependencies`, `IdSet`, `ComboType`, `CasparCGSocketResponse`, `ListrObject`, `ProductRepository`, `ListProps`, `Traversable1`, `Hashable`, `VueWrapper`, `ICompiler`, `TimeOpNode`, `PerfEntry`, `SearchRecord`, `VerifyStream`, `SegmentId`, `AppWindow`, `IBranchListItem`, `Mocha.Done`, `SqlEntityManager`, `ReportIndicator`, `ProviderUserBulkRequest`, `Calculator.Client`, `CreateExperimentCommandInput`, `FluidBox`, `RenderContextBase`, `Video`, `TilemapSeries`, `SubMiddlewareBuilder`, `General`, `SpawnSyncOptions`, `TemplateExpression`, `OpenApi`, `SecurityRequirement`, `LabIcon`, `FlowParameter`, `Tx.Options`, `ReactiveControllerHost`, `StoreLike`, `ANodeExprLValueVar`, `GfxIndexBufferDescriptor`, `ConfigChoice`, `RawSeries`, `Core.Rect`, `HandlerType`, `AggregateValueProp`, `ElementsDefinition`, `IRequire`, `Progresses2Runners`, `NumberFormatOptions`, `IChunkHeader`, `Faction`, `Targets`, `ESTree.ImportDeclaration`, `ContentProps`, `IToolbarItemProps`, `CapacityProviderStrategyItem`, `YTMember`, `AttrValuesStore`, `StyleNode`, `RouteExecutionFromOutput`, `TournamentRecordList`, `Model.Book`, `PvsFile`, `ServiceJSON`, `ImageUrlOptions`, `VerifyCallback`, `PIXI.InteractionEvent`, `ThyAnchorLinkComponent`, `ListStreamsCommandInput`, `EntityStateResponse`, `PaymentData`, `IMap`, `FrescoError`, `CommandFlags`, `BackendSrv`, `MessageEmbed`, `PacketNumber`, `AtomOrString`, `MergeDeclarationMarker`, `IDatArchive`, `IErrData`, `QueryLeaseResponse`, `testing.ApplicationEnv`, `IPaneRenderer`, `ClientFileSearchItem`, `DebouncedFunction`, `Browser.WebIdl`, `Ajv`, `IICUMessage`, `AsyncLogger`, `PopupAlignment`, `Parsers`, `ReturnNode`, `DisplayContext`, `FunctionsMetadata`, `requests.ListRunLogsRequest`, `CameraOptions`, `FeedService`, `PointInTimeFinder`, `Tip`, `DiscoverLegacyProps`, `MockTokenTransferProxyContract`, `ContainerContent`, `FeatureFlags`, `IThread`, `TypeC`, `UninstallEventData`, `SessionDescription`, `PipelineTarget`, `CategoryStub`, `Yendor.BehaviorTree`, `Orientation`, `TokenlonInterface.TxOpts`, `ComponentRendering`, `FocusRingOptions`, `OpConfig`, `IScene`, `WorkingDayOfYearByMonth`, `IConfig`, `SVGO`, `SavedObjectsFindResponse`, `BedrockFile`, `VariableColor`, `DataModel.ColumnRegion`, `DrawParams`, `vscode.Webview`, `CtrExpBool`, `PubSubListener`, `ValidatePurchaseHuaweiRequest`, `KeysSource`, `SceneGroup`, `PureSelectors`, `SendOverrides`, `CompilerFsStats`, `DMMF.SchemaArgInputType`, `ConfigFactory`, `ts.Modifier`, `VisualizationsAppExtension`, `TabComponent`, `Markdown`, `MappedType`, `RequiresRuntimeResult`, `AStarNode`, `GroupedObservable`, `VertexAttributeGenDef`, `Float32BufferAttribute`, `MemberFieldDecl`, `ISettingsContext`, `TextRow`, `TransactionLog`, `ClassTransformOptions`, `HTMLTableColElement`, `JsxText`, `ObjExplorerObjDescriptor`, `ITriggerContructorParams`, `BreakNode`, `jdspec.SMap`, `HeftEvent`, `d.RuntimeRef`, `FailedImport`, `ExecContext`, `PayoutMod`, `AksClusterConfig`, `Matrix4`, `Period`, `RequestParameters`, `Positioned`, `NVMEntryName`, `SvgViewerConfig`, `IABIMethod`, `ISection`, `ParsedDocument`, `HiddenProps`, `CmsEntry`, `TestImage`, `BarTuple`, `GitlabAuthTokenRepository`, `DTO`, `CustomTransformers`, `GameResult`, `ScriptTarget`, `SchemaValidationResult`, `IColumnConfig`, `MockAlexa`, `BridgeableChannel`, `Program`, `IConnectionPageProps`, `IDataFilterResultValue`, `MutationTuple`, `PDFAcroListBox`, `string`, `JQLite`, `TraceContext`, `TimeOptions`, `ClusterConfig`, `AuthenticationInstruction`, `FIRDocumentSnapshot`, `PFS_Config`, `HomeView`, `BuildConfiguration`, `ClassEntity`, `BlockHeader`, `StoreType`, `Recipe`, `InsertContext`, `PQP.Language.Type.TPrimitiveType`, `ScheduledOperationDetails`, `IntegerRangeQuantifier`, `SWRConfiguration`, `SectionOptions`, `StateDeclaration`, `DbSeed`, `MatOptionSelectionChange`, `MiddlewareFn`, `IBaseAddressAsyncThunk`, `PyteaWorkspaceInstance`, `CliGlobalInfo`, `DocumentationResult`, `BaseBigNumber`, `SheetsArray`, `DatabaseIndexingService`, `ServiceInterface`, `DistrictsDefinition`, `ICollectionTrigger`, `TypedRequest`, `IJobFile`, `InjectedMetamaskExtension`, `IVisualizerStyle`, `MappedStates`, `MentionInfo`, `GCFBootstrapper`, `MockContainerRuntimeFactoryForReconnection`, `TreeRepository`, `CryptoKey`, `Hardfork`, `browser`, `IInviteGroupUsersOptions`, `Node.JSON`, `GetStagesCommandInput`, `SfdxFalconRecipeJson`, `BookmarkIdMapping`, `TheBigFanStack`, `PlanarMaskBaseTool`, `CfnApi`, `ICourse`, `MaybeVal`, `CubemapSky`, `IEnemy`, `FileError`, `SetNode`, `ForgeModMcmodInfo`, `ReadableStream`, `Validators`, `MultiKey`, `IReducerContext`, `ScrollbarOptions`, `DatabaseObject`, `ConsoleMessageType`, `CreatePageReq`, `Contacts`, `TransformableInfo`, `ModelInstance`, `ResponseToActionMapper`, `TextPossibilities`, `AnalyzerFileInfo`, `DateTimePatternFieldType`, `Functor`, `SEMVER`, `RefLecture`, `TypedEmitter`, `SnapshotMetadata`, `InputSpec`, `FileSystemManager`, `HandleType`, `VersionResult`, `DOMNode`, `DecodeResult`, `Viewer.SceneGroup`, `MiddlewareCallback`, `IndexData`, `DaffPaypalTokenResponse`, `FlamegraphNode`, `VoidType`, `ParamSpecValue`, `CompiledComponent`, `TileAniSprite`, `AstEntity`, `SetToken`, `OutlineDoOauthStep`, `TsCohortDateRangeComponent`, `MessageBoxReturnValue`, `ObjectExplorerService`, `BlockFragment`, `DecoratorConfiguration`, `React.ForwardRefRenderFunction`, `ForwardRefComponent`, `ElementPosition`, `QueryArray`, `UVTX`, `InternalQueryHandler`, `BuddyWorks`, `APIProvider`, `PieSeries`, `CommandsCache`, `JGadget`, `StartCallOptions`, `InvalidVPCNetworkStateFault`, `BufferGeometry`, `StringifyContext`, `HDOMImplementation`, `RenderTargetTexture`, `HKT`, `RuleCondition`, `NavigationOptions`, `IViewEntity`, `MergedProblem`, `CacheBehavior`, `FBXReaderNode`, `WriteTransactionReply`, `CRDPChannel`, `IAggType`, `EnhancedStore`, `SizeT`, `SchemaRegistry`, `ModelMetadata`, `CSI`, `HashPair`, `ImageView`, `ParsedMail`, `ApplicationSettings`, `FormSubmissionState`, `InsertionEdit`, `LoggerAdapter`, `SpaceId`, `LitecoinBalanceMonitorConfig`, `Coords`, `RoleListContext`, `ChainParam`, `td.Action1`, `PhaseEvent`, `Sourcelike`, `interfaces.IExtensionConfiguration`, `KSolvePuzzleState`, `AppxEngineStep`, `ISwidget`, `RTCRtpHeaderExtensionParameters`, `DescribeScheduledActionsCommandInput`, `IPizzasTable`, `protos.common.MSPPrincipal`, `Skill`, `SortingType`, `browser.management.ExtensionInfo`, `PanGestureHandlerGestureEvent`, `BufferType`, `LSTM`, `ExpressionRenderer`, `DescribeDomainAutoTunesCommandInput`, `CharsetNameContext`, `ISnippet`, `ExpressRequest`, `TypeArray`, `DeleteQueryBuilder`, `UIView`, `SessionInfo`, `ModuleLoader`, `AnimationControls`, `DataUnitUp`, `DocNode`, `FieldInfo`, `SocketClient`, `requests.ListAutoScalingPoliciesRequest`, `TObjectProto`, `RemixConfig`, `CanAssignFlags`, `MDCTextFieldFoundation`, `DebugProtocol.DisconnectArguments`, `PropDecorator`, `IntegerParameterRange`, `DeleteAppInstanceUserCommandInput`, `RedirectOptions`, `DeviceManager`, `TComponent`, `ToolsWorkspaceCommandResponse`, `VanessaDiffEditor`, `Datapoint`, `HistoryLocation`, `GanttItemInternal`, `DescribeConfigurationCommandInput`, `ApplicationType`, `INanoDate`, `CredentialsOptions`, `IListenerOptions`, `VizChartPanel`, `ChlorinatorState`, `CdsNavigationStart`, `PageFlip`, `BMMessage`, `VariantForm`, `NavbarElementProps`, `Method`, `MapInfo`, `TVEpisodeDAO`, `FormatContext`, `CancelFnType`, `PackageType`, `SetupPlugins`, `HierarchyIterable`, `IHawkularAlertQueryResult`, `IRepository`, `APIGatewayProxyEventV2`, `INavLink`, `ThyDialogConfig`, `NormalizedProvider`, `AmmFakeInstance`, `DisassociateMembersCommandInput`, `AuthStateType`, `IActor`, `OidcClientSession`, `StringDecoder`, `EngineOpt`, `IndexSignatureDeclaration`, `ZeroPadding2D`, `IRunData`, `ConnectionRecord`, `ClassWithMethod`, `FrameNodePort`, `PatternUnknownProperty`, `requests.ListWindowsUpdatesRequest`, `TBuffer`, `TexMtxMapMode`, `Intersection`, `DataGrid.Style`, `PlaneData`, `DeploymentExtended`, `B6`, `DomainType`, `BaseProperty`, `ComponentFactoryResolver`, `AuthorizationMetadata`, `Timeline.State`, `DAVResponse`, `SimulcastLayers`, `OneToOneOptions`, `PerformanceResourceTiming`, `VariantAnnotation`, `IIOPubMessage`, `Hertz`, `GitBlameLines`, `Kleisli`, `SignupResponse.AsObject`, `PropertySchema`, `DecodedDeviceType`, `ThyCollapsePanelComponent`, `ListJobRunsRequest`, `GetKeyboardResponseOptions`, `IEmailProvider`, `IntervalTree`, `INumberFieldExpression`, `firebase.firestore.WhereFilterOp`, `Formatters`, `IConnection`, `XrmStatic`, `SelectNode`, `FilteredPropertyData`, `PageCloseOptions`, `ScriptDataStub`, `GPUDevice`, `UnionOrFaux`, `MenuDataAccessor`, `ListJobsRequest`, `RC`, `EmbeddableOutput`, `ScriptSource`, `EnclosureShape`, `DeleteQuery`, `Histogram`, `ComputedGeometries`, `BrowserContext`, `IStream`, `ClassifiedParsedSelectors`, `InfrastructureRocket`, `PureVisState`, `UILayoutViewController`, `WithNodeKeyProps`, `ParquetField`, `ValueCtx`, `ViewportService`, `Motor.StopActionValue`, `RingBuffer`, `pulumi.Output`, `QName`, `INotification`, `WebGL2RenderingContext`, `LatexAst`, `ValidatorResponse`, `BotsState`, `T7`, `SbbDialogConfig`, `instantiation.IConstructorSignature3`, `CredentialCreationOptions`, `IHillWarriorResult`, `RepositorySettingsValidation`, `FunctionDeclarationStructure`, `IThriftField`, `P.Logger`, `ERC721`, `ThemeFromProvider`, `Inputs`, `AudioData`, `evt_sym`, `ScrollAreaContextValue`, `TableStringWriter`, `IMusicRecordGrid`, `WebSocketMessage`, `FolderWithSubFolders`, `PerfGroupEntry`, `Protocol`, `TimelinePath`, `Ring`, `HTMLDataListElement`, `ReflectionObject`, `TSocketPacket`, `GMxmlHttpRequestResponse`, `DescriptorProto_ReservedRange`, `JsonRPC.Request`, `ExternalFile`, `ExceptionListItemSchema`, `FailoverGroup`, `SideBarView`, `ReferenceToken`, `Header`, `UpdateConfigurationResponse`, `DebugThread`, `api`, `AttributeDefinition`, `ValidationRecord`, `ServiceSetup`, `SoftwarePackage`, `formField`, `ValidationError`, `ActionsStage`, `TriggerEventCommand`, `MessageIDLike`, `ToolbarItem`, `TaskPoolRunResult`, `ServerLock`, `AddRepositoryCommand`, `AuthorisationStore`, `ParticipantListParticipant`, `NzCellFixedDirective`, `VoteAccountAsset`, `IntervalTimeline`, `VertexList`, `ShippingState`, `Mesh`, `SavedObjectsStart`, `RangeEntry`, `TilingScheme`, `DOMWrapper`, `LinearFlow`, `PromiseReadable`, `Map`, `NotDeciderInput`, `StyleRendererProtocol`, `PermissionObjectType`, `GeneratorVars`, `CalendarManager`, `StyleBuildInfo`, `JSMService`, `InstantiationContext`, `ParagraphProps`, `YieldExpression`, `HistoryStore`, `StylableResults`, `TypedHash`, `VideoInputType`, `DiscordEvents`, `ContentBlock`, `PublicKeyInfo`, `DestinationConfiguration`, `DiagnosticRuleSet`, `AuthTokenInfo`, `ValidationBuilder`, `GroupUserList`, `ILayoutRestorer`, `ObjectMapper`, `PhrasesBuilder`, `SuiCalendarItem`, `TLIntersection`, `planner.PlannerConfiguration`, `Stat`, `IR.BasicBlock`, `PackedBubbleChart`, `Wrapap`, `Eris.Message`, `LinkedWorkTree`, `Organisation`, `ResourceModel`, `IFluidDataStoreRuntime`, `ExtractRef`, `Vec4Sym`, `AggregateField`, `BottomBarItem`, `ResizeObserverService`, `PlayerPosition`, `DateRangeShortcut`, `ChartEvent`, `RegisteredDelegate`, `NgForage`, `IBlockType`, `KeybindingRegistry`, `QueryLang`, `Lesson`, `LayoutItem`, `ConnectionInformation`, `ImageScrollBar`, `DescribePackagesCommandInput`, `FabSpecExports`, `Spotilocal`, `Node.NodeMessage`, `ProtoFab`, `requests.ListGoodBotsRequest`, `CurlyOptions`, `GaugeVisualizationState`, `PolyBool.Shape`, `QueryParserVisitor`, `TypeAliasInfo`, `MediaView`, `CreateOfficeHour`, `ErrorOptions`, `CommentPattern`, `DedentToken`, `KernelSpec`, `AriaDescriber`, `INormalizedMessage`, `SendResult`, `MediaPlayer`, `TemplateIntegrationOptions`, `TVEpisode`, `JSONSchema7`, `MockToken`, `ContainerOS`, `SyncHandlerSubsetOf`, `MIROp`, `OptionalMaybe`, `LayerNode`, `AuthStateModel`, `IndexResponse`, `WebpageMetadata`, `NoticeEntity`, `SkillService`, `LinkChain`, `BlockFactory`, `CRUDEvents`, `PartBody`, `InterfaceBuilder`, `Multisig`, `ParticlesFlyerView`, `DashboardContainer`, `Sessions`, `TestTag`, `QuickReplyItemProps`, `TheCloudwatchDashboardStack`, `EmitParameters`, `sdk.IntentRecognitionCanceledEventArgs`, `MIRRecordType`, `Anthroponym`, `ITrackCallback`, `OsmWay`, `CloneFunction`, `ControlParams`, `QPixmap`, `ResolvedPackage`, `SPBatch`, `BlockModel`, `UpdateTagDto`, `Screens`, `RequestConditionFunctionTyped`, `Playlist`, `UpdateEmailTemplateCommandInput`, `BaseFilterInput`, `IHttpPostMessageResponse`, `ForEachPosition`, `BoardState`, `ECSEntity`, `RemirrorManager`, `ContractEntry`, `FindCursor`, `InspectionFailure`, `ParseNodeType`, `AxisContext`, `FormItem`, `MenuTargetProps`, `UnixTime`, `CDPTarget`, `VisualConstructorOptions`, `MediaKeyComponent`, `CustomUrlAnomalyRecordDoc`, `GetPrTimelineQuery`, `ConditionalTypeNode`, `monaco.editor.IReadOnlyModel`, `AsyncMachine`, `Vorgang`, `VdmNavigationProperty`, `WorkRequestLogEntry`, `MixItem`, `TagFilter`, `DeleteLoadBalancerCommandInput`, `models.IArtifactProvider`, `JssContextService`, `Frustum`, `LoudMLDatasource`, `Activator`, `IUIEvent`, `RuleSummary`, `MemberRef`, `PlayerPieceLocation`, `BodyOnlyAcceptsNumbers`, `RoleDto`, `OutputTargetDocsReadme`, `d.CompilerModeStyles`, `ComparableValue`, `Classifications`, `MediaProps`, `UseRefetch`, `mongoose.Model`, `ChainConfig`, `ParserType`, `Deno.Process`, `DataValues`, `HomePublicPluginSetup`, `AuxBot3D`, `SerializeOutput`, `UpdateUserProfileCommandInput`, `CallIdRef`, `JWTTokenModel`, `SessionOptions`, `AccountBalancesResult`, `RestRequestMethod`, `ConversationContent`, `CustomPaletteParams`, `ArangojsResponse`, `CrochetPackage`, `CodeVersions`, `BaseAddress`, `TimedVariableValue`, `Dice`, `C2`, `PanelOptions`, `IHTMLElement`, `jest.Mocked`, `vscode.QuickPick`, `HTMLIonLoadingElement`, `ObjectTypeComposerFieldConfigDefinition`, `GitCommit`, `ANK1`, `LineupPlayerPosition`, `AutoforwardState`, `CreateConnectionCommandInput`, `JsonHttp`, `CodeGenModel`, `VideoGalleryStream`, `TSrc`, `IProtoBlock`, `ListDomainsCommandInput`, `GPUImageCopyTexture`, `GenericMessage`, `ReplaceResult`, `OrganizationRepository`, `AccountHasFundsFn`, `SerializedChangeSet`, `DeploymentEntry`, `GameRegistry`, `Transpose`, `DefinitionProvider`, `builder.UniversalBot`, `IconRegistryService`, `PublicKeySection`, `VoiceState`, `JobService`, `localVarRequest.Options`, `ResolveXName`, `BitArray`, `ResourceId`, `INPUT_SIZE`, `ResponderActivityType`, `CliAction`, `SecurityKey`, `Tardigrades`, `FSNetworkRequestConfig`, `InterpolatorFactory`, `BBox_t`, `QueryStatus`, `FSTree`, `LibraryBuilderImpl`, `Texture2D`, `FlexPlacement`, `NodeOptions`, `ITilemap`, `MangaListStatusFields`, `ProofRecord`, `Email`, `DataPositionInterface`, `VertexInfo`, `AccountSteam`, `SinonMock`, `uinteger`, `PackageDiffImpl`, `NarrativeSchema`, `ColliderData`, `SMTPServerSession`, `TextureBlock`, `IfNode`, `ContractClass`, `SourceEditorArgs`, `Future`, `Subscription`, `IFloatV`, `CancelWorkRequestResponse`, `LiveShare`, `ValidationErrorPath`, `YearAggregations`, `ProxyServerSubscription`, `ts.CompletionInfo`, `CurveLocationDetailPair`, `EventLocation`, `Trie`, `HTMLScLegendElement`, `ParsedPlacement`, `typedb.DBMethod`, `ISettingRegistry.ISettings`, `GetListParams`, `IOptimizelyFeature`, `DependencyKey`, `EnvVars`, `App.services.IUriService`, `Subtract`, `UpdateCourseOverrideBody`, `IWallet`, `CodeFixContext`, `BoundPorts`, `GetUserSettingsReadModel`, `Rectangular`, `ReactTestRenderer.ReactTestRenderer`, `OpenFileDialogProps`, `ArrayDiffSegment`, `TestSource`, `StartJobRunCommandInput`, `TypedComponent`, `S3StorageProvider`, `CartState`, `LabaColor`, `SparseGrid`, `SegmentAPISettings`, `LoadParams`, `Length`, `ProxyableLogDataType`, `TestModuleMetadata`, `IGetJobPresetInput`, `Knex.Raw`, `ContextualTestContext`, `Unsubscriber`, `CssAnimationProperty`, `TimeLimitItem`, `SUCUpdateEntry`, `ICategoryInternalNode`, `FlagshipTypes.Config`, `requests.ListCpeDeviceShapesRequest`, `ILineTokens`, `OffchainTx`, `ModuleSymbolTable`, `WeierstrassPoint`, `ImGui.Access`, `Paginator`, `FlowLogInformation`, `ts.IndexSignatureDeclaration`, `DurationMs`, `CompileResult`, `ParameterizedString`, `IGetLanguagesResponse`, `ActionSource`, `MemoryStorageDriver`, `ExploredCohortState`, `theia.Disposable`, `AuthContext`, `Chat`, `RenderLeafProps`, `NodeWithOrigin`, `SignatureVerifier`, `ClassScheme`, `DependencyList`, `ComponentBuilder`, `ts.TypeReferenceNode`, `CommandLineOption`, `JSDocParameterTag`, `I2CWriteCallback`, `ContextContributor`, `DecodedIdToken`, `BatchRequest`, `IRow`, `NetGlobalMiddleware`, `ValueRef`, `ParseConfigHost`, `Priority`, `IParsedError`, `MapService`, `Reffer`, `CommunityDataService`, `GeometricElement2dProps`, `TElement`, `ItemSliding`, `DeployedCodePackage`, `ImportInfo`, `ParamItem`, `EmptyClass`, `USBInterface`, `ClassPeriod`, `GossipFilter`, `TileLayer`, `CyclicDependencyGraph`, `ts.JsxAttribute`, `GitHubAPI`, `d.WatcherCloseResults`, `FormatId`, `InitSegment`, `DateOption`, `TagToken`, `LegacyField`, `JPAChildShapeBlock`, `BinaryWriter`, `monaco.languages.LanguageConfiguration`, `VFC`, `ItemDefinition`, `IFilterProps`, `AsyncState`, `ITopDownGraphNode`, `ImplementedFunctionOptions`, `PiLanguage`, `Model.Page`, `MainHitObject`, `ServeOptions`, `S3Client`, `DateValue`, `ServiceClientCredentials`, `AllOptions`, `OutputTarget`, `MemberForm`, `XYChartSeriesIdentifier`, `Kernel`, `Wah`, `SubgraphPlaceholder`, `TransformerDiagnostics`, `ClaimItem`, `LoginStatusChecker`, `IAddressState`, `IExpectedVerifiableCredential`, `GestureController`, `MassetMachine`, `AccountApple`, `TinymathFunction`, `FailoverDBClusterCommandInput`, `ActionResultComboCtx`, `ScaleCreationContext`, `TimelineTheme`, `NgParsedDecorator`, `IVariable`, `BoolLiteralNode`, `I18nConfig`, `ExpressionRunnerShorthandConfig`, `ICombinedRefCheck`, `ListTournamentRecordsRequest`, `vd.createProperties`, `SeriesCompareFn`, `ListComprehensionForNode`, `RefreshAccessTokenAccountsRequestMessage`, `IOHandlerForTest`, `NodeName`, `BackupFile`, `JobLogOption`, `LogAnalyticsSourceEntityType`, `IMutableVector4`, `FolderDetector`, `NullConfiguration`, `ARAddImageOptions`, `GraphQLScalarTypeConfig`, `TransactionOp`, `RequireNode`, `WorkspaceSymbolParams`, `SPClientTemplates.RenderContext_FieldInForm`, `RenderableOption`, `ResolverResolveParams`, `WebConfig`, `IDomMethods`, `FieldFormatConvertFunction`, `IGroupInfo`, `TMessageContent`, `Aggregation`, `GluegunPrint`, `AuthenticationParameters`, `requests.ListVolumeGroupsRequest`, `Cypress.PluginEvents`, `CodeGenResult`, `SNSInvalidTopicFault`, `LocalVarInfo`, `SObjectConfig`, `QualifiedNameLike`, `ANTLRBackend`, `LambdaRestApi`, `GetFederationTokenCommandInput`, `ConfigConfigSchema`, `KibanaPrivileges`, `AddressBalance`, `IRefCallback`, `ts.ResolvedModule`, `ReadModelQuery`, `FilterDef`, `TPlacementMethodArgs`, `SoftwareKeyProvider`, `IDocumentStorage`, `ConfigAggregator`, `MaskingArgs`, `E2`, `ErrorMessageProps`, `TimeStamp`, `SymbolKind`, `ResourcePolicy`, `DocgeniContext`, `FieldSchema`, `LoopOutParameter`, `BillName`, `ItemWithAnID`, `UnionTypeNode`, `JSZipObject`, `ForwardRefExoticComponent`, `BlockStateRegistry`, `ObjectDictionary`, `HTMLIonActionSheetElement`, `core.BTCGetAccountPaths`, `IDoc`, `SingleConnection`, `TileCoordinate`, `ShareService`, `Worksheet`, `UICollectionViewFlowLinearLayoutImpl`, `IAstMaker`, `PointerInput`, `ZeroBalanceFn`, `ExpressionWithTypeArguments`, `NVMJSON`, `DiscordMessage`, `SwatchBookProps`, `PushSubscription`, `NodeConstructor`, `DeploySuccess`, `FileIdentifier`, `TwingFilter`, `SubmitFeedbackCommandInput`, `ModelPredictArgs`, `ISampler2DTerm`, `ShadeCoverOptions`, `AndroidPermissionResponse`, `PositionRange`, `WatcherFolder`, `AmbientZone`, `CodeAction`, `PlatformEvent`, `Chest`, `LocaleProps`, `Looper`, `AuthType.Standard`, `V2BondDetails`, `NSMutableURLRequest`, `IState`, `SignedState`, `DefaultExecutor`, `MiniNode`, `ast.NodeAttributes`, `IdentityTest`, `DirectionType`, `DraftEntityInstance`, `MenuModel`, `ToString`, `StashResult`, `ImageCanvas`, `utils.BigNumberish`, `PetService`, `ButtonTween24`, `ComputedField`, `IAureliaProjectSetting`, `IStatistics`, `IPath`, `Base`, `Reason`, `FilterMeta`, `ArtifactDelta`, `CCashCow.Payment`, `ServiceLogger`, `DebugBreakpointDecoration`, `ArgumentParser`, `CategorySortType`, `GraphQLTypeResolver`, `IMessageEvent`, `FileModel`, `GitAuthor`, `OtokenFactoryInstance`, `ResolveResponse`, `IOptionFlag`, `DomPath`, `MutationCallback`, `GX.TevColorChan`, `ListDetectorsCommandInput`, `ListProjectsCommandInput`, `FunctionBinding`, `V1PersistentVolume`, `OrganizationState`, `PartialApplicationConfig`, `CurvePrimitive`, `SingleTablePrettyfier`, `Claimants`, `AdonisApplication`, `Cave`, `WikiItem`, `JsonStringifierParserCommonContext`, `SMTPServer`, `ImportResolverFactory`, `AuthContextState`, `PlayMacroAction`, `PaginationNavProps`, `thrift.TField`, `Decision`, `ActionStatusEnum`, `Orphan`, `QueryInterface`, `VocabularyStatus`, `Neutrino`, `WalkNext`, `NgGridItemPosition`, `ErrorChain`, `RowNode`, `MDCBottomNavigationBar`, `Numeric`, `SceneFrame`, `ConfigsService`, `IRequestUserInfo`, `React.ReactElement`, `CreateUserProfileCommandInput`, `DomainService`, `ListWorkRequestsRequest`, `MouseEventHandler`, `GX.TexGenType`, `requests.ListSubscriptionsRequest`, `NamedTupleMember`, `ActionsConfig`, `EdgeMemento`, `Endpoint`, `JsonContact`, `HttpEnv`, `TaskService`, `PokemonType`, `PlatformService`, `IMetricsRegistry`, `Workspaces`, `RlpItem`, `SBDraft2CommandOutputParameterModel`, `MovieOpts`, `GossipPeer`, `OffsetPosition`, `NexusGraphQLSchema`, `GetPublicAccessBlockCommandInput`, `SourceBreakpoint`, `CRG1File`, `ParsedQuery`, `Matrix2d`, `PendingTransaction`, `FormatterOptions`, `FocusedElement`, `ITelemetryLogger`, `IndicatorForInspection`, `PackageManagerPluginImplementation`, `MangaFields`, `AutoOption`, `TNSPath2D`, `SeriesPlotRow`, `WalkerArgs`, `ShaderNode`, `FeatureSymbology.Overrides`, `DbIncrementStrategy`, `ProcessedBundle`, `ProgressToken`, `RouterInstruction`, `TargetType`, `CreateJobDetails`, `GlobOptions`, `RequirementBaseModel`, `AttachmentItem`, `TSInstance`, `NotebookWorkspaceName`, `PlayerIndexedType`, `SubtitlesCardBase`, `RenderSource`, `Genre`, `ITokenMatcher`, `BlendMode`, `ResultData`, `CommandLineOptions`, `FlatTreeControl`, `MessageContent`, `IKey`, `IRandomAccessIterator`, `Erc20Mock`, `GraphQLInterfaceType`, `DeleteLoggingConfigurationCommandInput`, `MediaChange`, `CreateReplayDto`, `HttpContextContract`, `ListCustomPluginsCommandInput`, `JsExpr`, `RnM2Material`, `CoverageCollection`, `SelectionItem`, `IRawBackupPolicy`, `ThyPopoverConfig`, `React.CompositionEvent`, `BookingsModel`, `Foo`, `ReadFileOptions`, `FormatMessage`, `ATNConfigSet`, `CompileRepeatUtil`, `ISearchRequestParams`, `ServerSideProps`, `SizeData`, `PipelineId`, `PkgJson`, `ExpandedTransitionListener`, `ParentComponent`, `NotImplementedYetErrorInfo`, `EtjanstChild`, `ProjectBuildOptions`, `PlainObject`, `N6`, `CreateAttendeeRequestItem`, `SubscriptionClient`, `CustomIntegrationRegistry`, `ThySkeletonComponent`, `I18NextPipe`, `core.Connection`, `LocatorDiff`, `Options`, `CliParam`, `CommandOutputBinding`, `MonitoringOutputConfig`, `IDataFrame`, `PhysicalElement`, `CollapsibleListProps`, `MessageActionRow`, `Merge`, `Catalog`, `DogePaymentsUtilsConfig`, `Messaging`, `vscode.TextEditor`, `ControllerConfig`, `MatchResult`, `BaseContract`, `CalendarManagerService`, `Incident`, `ReuseTabNotify`, `ElementInstance`, `ProcessingPayload`, `CompositeDraftDecorator`, `STIcon`, `ECDb`, `KernelInfo`, `SchematisedDocument`, `ArrayProperty`, `TranslationFacade`, `AnyRect`, `LayoutSettings`, `PointMarkerOptions`, `ReturnTypeFunc`, `RegistryMessage`, `ObjectCacheState`, `MixArgs`, `Highcharts.VMLDOMElement`, `LangChangeEvent`, `ModelSnapshotType`, `AggField`, `FrontMatter`, `Invite`, `EventProcessor`, `sdk.TranslationRecognitionResult`, `FastifyTypeBoxHandlerMethod`, `Intent`, `GregorianDate`, `Track`, `ZoweUSSNode`, `tfc.io.IOHandler`, `VerifyOptions`, `FileIconService`, `ChannelMessageSend`, `StepNode`, `ProvenClaim`, `ContentDirection`, `IChildrenItem`, `OutputTargetEmptiable`, `FormMethods`, `RequestBase`, `PopupMessage`, `Protocol.Input.DragData`, `ParsedSelectorAndRule`, `RegisteredSchema`, `thrift.TType`, `PromiseEmitter`, `StringCodeWriter`, `TransactOptions`, `ProposalTemplateService`, `Peripheral`, `ComponentTester`, `ISetOverlapFunction`, `UpdateFileService`, `IColorEvent`, `MonitoringGroupContext`, `PlanService`, `TaskInstance`, `LocationType`, `KC_PrismData`, `ProjectMode`, `NamedCollection`, `GithubUserRepository`, `CombatStateMachineComponent`, `SettingRepository`, `FlushMode`, `AnimGroupData`, `TreeListComponent`, `TName`, `EosioTransaction`, `TypeSourceId`, `ChangeHandler`, `CookieManager`, `AsyncIterator`, `Rect2`, `LifecycleChannel`, `TextFieldWithSelectionRange`, `ConditionFn`, `SourceDataItem`, `Logger`, `IGetTimeLogConflictInput`, `FormAction`, `SourceTargetFileNames`, `UIBeanHelper`, `LineAnnotationSpec`, `PublishResponse`, `HttpInterceptController`, `SymlinkInode`, `XSelectNode`, `IDependency`, `Preferences`, `MicroframeworkSettings`, `BlinkerResponse`, `ComputedBoundsAction`, `DropTableNode`, `FnAny`, `GetFileOptions`, `Quantity.REQUIRED`, `AggregateSpec`, `restify.Request`, `OpenPGP.key.Key`, `FindOneOrFailOptions`, `MongooseSchema.Types.ObjectId`, `CreateElementRequiredOptions`, `ZodUnion`, `AccordionProps`, `Applicative2`, `GReaderConfigs`, `ValueMetadataBuffer`, `RtcpSourceDescriptionPacket`, `SvelteElement`, `NetType`, `ExtensionState`, `CreateExtensionPlugin`, `pd.E2EPageInternal`, `ClientAuthentication`, `MemoryView`, `panel_connector.MessageHandler`, `AdapterGuesser`, `FormFieldConfig`, `PoolType`, `LoadOptions`, `DatasetMemberEntry`, `TionDeviceBase`, `EnvOptions`, `JsonRPC.Response`, `Subspace`, `SQLTransaction`, `BaseDbField`, `GroupCurrencyCode`, `Requester`, `AccountParser`, `Clock`, `DebugProtocol.StepOutResponse`, `MXFloatingActionButtonLocation`, `Comment`, `ListAvailabilityHistoriesRequest`, `FromYamlTestCaseConfig`, `WSClient`, `Unknown`, `PackagesWithNewVersions`, `DayPickerContextValue`, `Sort`, `DecodedJwt`, `ImportGroup`, `JobState`, `TypePairArray`, `FakeContract`, `WebSocketConnectCallbacks`, `cp.ChildProcess`, `FeatureAst`, `BandHeaderNS.CellProps`, `ErrorStateMatcher`, `CrudGlobalConfig`, `RegisterCr`, `EditorManager`, `PlatformType`, `ProxyRequestResponse`, `LogLayout`, `QueryRef`, `OutputTargetDistLazy`, `ShortTermRetentionPolicyName`, `TargetedEvent`, `MapProps`, `UnknownParticipant`, `PublicMethodsOf`, `AWSAccount`, `EngineAttribute`, `Guild`, `ICliCommandOptions`, `ForNode`, `LabelBullet`, `ArcProps`, `PlaceholderMapper`, `types.ScriptType`, `TelemetryRepository`, `Response.Response`, `ForInitializer`, `ParsedMapper`, `WebsocketRequest`, `HealthCheck`, `TransferHotspotV2`, `KeyMap`, `ExposureMode`, `ServerView`, `IMetricsService`, `Locker`, `ListBotsCommandInput`, `AddPermissionCommandInput`, `PatchOptions`, `HStatus`, `DTONames`, `ThyUploadResponse`, `ISubmitData`, `NpmPackage`, `Ribbon`, `CardContext`, `P2P`, `InternalKey`, `AnalyzerState`, `Types.OutputPreset`, `StaffService`, `AudioBuffer`, `ExpectedTypeResult`, `VisualUpdateOptions`, `AssertionExpression`, `d.OutputTargetDistCollection`, `CustomLoader`, `PortalConfig`, `MdcSwitch`, `CLR0_MatData`, `StatusProps`, `ProofNodeX`, `BrowserDownloads`, `ConnectionInfoResource`, `ListCertificateAuthoritiesCommandInput`, `BigFloat53`, `DoneCallback`, `XliffMerge`, `RandomUniformArgs`, `VectorLayer`, `LoginScript`, `ListrTask`, `CAC`, `vscode.Progress`, `Lint`, `requests.ListVlansRequest`, `t_b79db448`, `SearchQueryUpdate`, `DataBlock`, `TDiscord.Client`, `StylePropConfig`, `IIPCClient`, `ConfigurationCCAPISetOptions`, `PriceAxisViewRendererCommonData`, `CommonDialogService`, `Raw`, `IAddressSpace`, `MarkerProps`, `Refactoring`, `NET`, `KeywordErrorCxt`, `JWTService`, `GfxRenderPipelineDescriptor`, `UpdateError`, `EventNameFnsMap`, `AccountsScheme`, `QuadrantRefHandler`, `NumberToken`, `OutputDataConfig`, `GetOptions`, `Ruleset`, `IndexingStatusResolver`, `ILogOptions`, `ActionOptions`, `NormalisedSearchParams`, `WorkspaceMiddleware`, `BaseRedirectParams`, `IOrganizationBinding`, `MetaClient`, `Exit`, `MintAssetRecord`, `Jump`, `iff.IChunkHeader`, `HypermergeUrl`, `DescribeAppInstanceAdminCommandInput`, `JSONSchemaRef`, `HostWindowService`, `DatasetSummary`, `Recording`, `CreateSampleFindingsCommandInput`, `MeetingParticipants`, `Bytes32`, `MutationElement`, `ClipsState`, `AssembledTopicGraphics`, `ActorType`, `SpaceSize`, `ListThemesCommandInput`, `BodyPixConfig`, `FieldFormatsContentType`, `Payport`, `RenderPage`, `GoldenLayout.ContentItem`, `RawTypeInfo`, `ITelemetryProperties`, `AnyNativeEvent`, `ThreadKey`, `DeleteRequest`, `TEUnaryOp`, `EditableProps`, `EffectContext`, `NzMessageService`, `TimePickerControls`, `Active`, `ITransValueResult`, `DeleteApplicationCommandInput`, `TokenManager`, `apid.RecordedTagId`, `MainAreaWidget`, `TLocaleType`, `ConfigurationsClient`, `ICommonHeader`, `d.OutputTargetDistTypes`, `StoreObjectArg`, `AndroidChannelGroup`, `PointerEventHandler`, `MinHeap`, `Device`, `EmacsEmulator`, `AfterWinnerDeterminationGameState`, `workerParamsDto`, `Milestone`, `CosmeticFilter`, `HeadElement`, `StartStop`, `ConfirmHandler`, `GetDMMFOptions`, `EntityProps`, `UnparsedSource`, `OnChangeValue`, `TestingRunOptions`, `SponsorOptionsOpts`, `ChartElementSizes`, `PeopleEmitter`, `ShortcutType`, `PBXGroup`, `MDCMenuSurfaceAdapter`, `Real_ulonglong_numberContext`, `SocketServer`, `ts.SemanticClassificationFormat`, `Events.predebugdraw`, `DepositTransaction`, `VirtualApplianceSite`, `TLE.Value`, `... 28 more ...`, `ICombiningOp`, `ObjectCacheService`, `MarkMessageAsSeenCommand`, `IPipe`, `FunctionMethodsResults`, `IEtcd`, `ListAppInstanceAdminsCommandInput`, `RendererAPI`, `SendEmailCommandInput`, `WordcloudUtils.PolygonPointObject`, `PacketRegistry`, `DebugProtocol.NextArguments`, `ChunkExtractor`, `RegExpReplacement`, `EmitBlockKind`, `ODataResponse`, `AutoSubscription`, `Caret`, `InvalidDatasourceErrorInfo`, `UpdateGatewayCommandInput`, `TableContext`, `SortedSet`, `ChildReferenceDetail`, `IsMutedChangedListener`, `CachedResource`, `DataService`, `Csp`, `IAmazonInstanceTypeOverride`, `RSAKey`, `TocState`, `sdk.DialogServiceConnector`, `DeployView`, `IIStateProto`, `Keystore`, `CdkColumnDef`, `TodoTaskList`, `ListItem`, `DataArrayTypes`, `HeaderSetter`, `StatResult`, `SnapshotProcessor`, `Threshold`, `FileCompletionItemManager`, `DoublyLinkedListNode`, `HeadlessChromiumDriver`, `IPlayerActionCallback`, `GetParameters`, `R.List`, `MetadataValueFilter`, `MediaRule`, `IZoweTree`, `IUIAggregation`, `ChildProcess`, `chrome.windows.Window`, `TableFinder`, `UserSettingsStorage`, `IExternalDeviceId`, `FilesMatch`, `ValidationErrorItem`, `GroupType`, `IItemTemplate`, `NvLocation`, `ts.ResolvedModuleWithFailedLookupLocations`, `SetupOptions`, `EpicMiddleware`, `JPAEmitterWorkData`, `tf.Tensor`, `AsToken`, `CertaConfig`, `AuthenticationProviderOptions`, `ReportManager`, `SharesService`, `RSAEncryptionParams`, `AppMountParameters`, `EvaluatedTemplateArgument`, `DefaultSequence`, `ICCircuitInfo`, `IFilterArgs`, `ASTResult`, `MockTrueCurrency`, `IPortal`, `GlobalStorageOptionsHandler`, `RoleValidationResult`, `nodeFunc`, `SyncMode`, `IAgent`, `SharingSessionService`, `Abbreviation`, `ListWorkspacesRequest`, `ContractParameter`, `UsePaginatedQueryReducerAction`, `TreeMate`, `SearchOptions`, `SwiftDeclarationBlock`, `ElementAspect`, `BootstrapOptions`, `GetResourceCommandInput`, `CertificateRule`, `DecodedAttribute`, `XPCOM.ContentFrameMessageManager`, `Long`, `IBaseEdge`, `Vector2d`, `ArrayIterator`, `nodeFetch.RequestInit`, `StoryObj`, `IntPairSet`, `SourceMapper`, `ArtifactEngine`, `u64`, `VertexType`, `MonitoredElementInfo`, `IHandlebarsOptions`, `ProductOperations`, `ComparisonOptions`, `StoryArchive`, `TtLCreatorOptions`, `JSONScanner`, `EditorConfiguration`, `models.NetCore`, `GetUsersRequest`, `MDCRadioAdapter`, `IOracleListener`, `EventTrigger`, `BeEvent`, `GeneratorTeamsAppOptions`, `RequestMethodType`, `CppSettings`, `ICreateOrgNotificationResult`, `FabricWalletRegistryEntry`, `ChangeDescription`, `View1`, `D3Selector`, `ScriptVersionCache`, `DeepType`, `StoreData`, `IAssetsProps`, `CriteriaNode`, `FileMetadata`, `FontStyle`, `QueryFilterType`, `Seg`, `PrimitiveNonStringTypeKind`, `TContainer`, `ContentManagementService`, `AlertNavigationRegistry`, `PoiLayer`, `CallError`, `ExpectApi`, `TokenGroup`, `IDriver`, `ODataQueryMock`, `FeedProviderType`, `TodosPresentST`, `RuleSet`, `ProfileResponse`, `CustomAvatarOptions`, `ISubject`, `FastPath`, `IPascalVOCExportProviderOptions`, `ICordovaLaunchRequestArgs`, `ActorRef`, `RemoveBuffEvent`, `CacheWithRedirects`, `DecryptedMessage`, `LoggingServiceConfiguration`, `NgxFeatureToggleRouteGuard`, `RoomReadyStatus`, `TransactionJSON`, `ReplacePanelAction`, `FormGroup`, `RemoteStoreOptions`, `IssueIdentifier`, `MinimalCancelToken`, `JsxTagNameExpression`, `IPrivateKey`, `ScriptElementKind`, `LabStorageService`, `SurveyMongoRepository`, `DescribeUserResponse`, `ComponentCompilerStaticEvent`, `TypeAttributeMapBuilder`, `CommandEventType`, `SubTiledLayer`, `AddressHashMode.SerializeP2PKH`, `BRRES.RRES`, `FileStream`, `EditLog`, `RelationInput`, `FormDependency`, `Filters`, `server.ManualServerConfig`, `WhiteListEthAsset`, `TokenDict`, `FieldDestination`, `IRole`, `CHILD`, `RequestPrepareOptions`, `CreateBundle`, `Chain`, `selectionType`, `ITBConfig`, `RawBackStore`, `DocumentStateContext`, `Entities`, `MagicLinkRequestReasons`, `PageMeta`, `LinkedIdType`, `PlanetApplicationRef`, `ImageHelper`, `DocumentTypeDef`, `ErrorDetail`, `DiscoveredMethodWithMeta`, `Messenger`, `ProgressState`, `RecordRepresentation`, `LanguageModel`, `events.Name`, `ButtonItem`, `DraftEditor`, `Conv2DInfo`, `GDQOmnibarMilestoneTrackerPointElement`, `TestCreditCardPack`, `InjectorModule`, `ComponentCompilerTypeReferences`, `ParseValue`, `UserProfile`, `O2MRelation`, `JimpImage`, `ConfigLogger`, `RefreshToken`, `AngularFireOfflineDatabase`, `UseProps`, `GlobalStringInterface`, `VerifyUuidDto`, `VisualViewport`, `Wei`, `Pod`, `Flo.EditorContext`, `RequestHandlerContext`, `JestTotalResults`, `IRenderLayer`, `TwitchBadge`, `IMapper`, `RepoInfo`, `LoadSettings`, `RequireOrIgnoreSettings`, `ParsedHtmlDocument`, `V1ClusterRoleBinding`, `GeoUnitIndices`, `java.lang.Object`, `DeleteClusterCommand`, `ObjectProps`, `ZoneType`, `SecuredFeature`, `SubmitFnType`, `BlockLike`, `PerformStatArgs`, `Interpolation`, `HSVColor`, `DashboardAppLocatorDefinition`, `RectAnnotationStyle`, `TimeConstraint`, `GunGraphNode`, `EzApp`, `vBlock`, `ColumnDefinitionNode`, `WikiFile`, `GroupUserList_GroupUser`, `GeoCoordinates`, `NxValues`, `echarts.EChartsOption`, `TeamList`, `SavedObject`, `SignedByDBInterface`, `RemoveNotificationChannelCommandInput`, `IStudy`, `xLuceneVariables`, `EntityHydrator`, `NumberValidator`, `UiKit.BlockContext`, `SPADeploy`, `TSelectedItem`, `TagService`, `CustomEvent`, `TSunCardConfig`, `MouseEventToPrevent`, `ShaderType`, `RebootDBInstanceCommandInput`, `IPushable`, `Sequence`, `DeleteSourceServerCommandInput`, `uproxy_core_api.CreateInviteArgs`, `CursorPosition`, `ClassDecorator`, `DrawState`, `DisposableSet`, `CommandPacker`, `RGBValue`, `DataGrid`, `UrbitVisorState`, `TGroupBy`, `Validate`, `FaunaRoleOptions`, `LoadBalancer`, `GraphMode`, `RecordsQuery`, `NavigationScreenProp`, `Milliseconds`, `ValidatedJobConfig`, `AccountAndPubkey`, `IInterpolatedQuery`, `AbiCoder`, `Api`, `MockTask`, `ConvertOptions`, `Remote`, `Origin`, `FilterOptions`, `EnvironmentAliasProps`, `ts.VariableDeclarationList`, `EdmxEnumType`, `PackageExpanded`, `WorkspaceSnaphot`, `ShoppingCartItem`, `PLSQLRoot`, `ParquetWriterOptions`, `FileSpan`, `ProjectData`, `io.IOHandler`, `INgWidgetContainerRawPosition`, `ClassAndStylePlayerBuilder`, `ENDDirective`, `ListRulesCommandInput`, `TreeStateObject`, `sdk.Recognizer`, `Errback`, `CardComponent`, `LiteralContext`, `Messages.BpmnEvents.TerminateEndEventReachedMessage`, `ProjectRiskViewEntry`, `ReporterConfig`, `Client`, `PathUpdater`, `FocusType`, `NestExpressApplication`, `HK`, `ActiveWindow`, `AppInstanceEventType`, `LanguageEffects`, `FetchListOptions`, `CollectionDependencyManifest`, `InitializerMetadata`, `ContainerNode`, `WalletI`, `LocationOffset`, `ChoiceValue`, `WFWorkflowAction`, `requests.ListBastionsRequest`, `TestSuiteInstance`, `IpcService`, `PluginResultData`, `NgModuleDefinition`, `LoaderEvent`, `ReactDataGridColumn`, `NetworkgraphPoint`, `TestScriptError`, `Commit`, `DeviceID`, `IScribe`, `BenchmarkData`, `AnyObjectNode`, `MDCChipActionType`, `MessengerTypes.PsidOrRecipient`, `ResolvedConfiguration`, `Lexer`, `IOptionTypes`, `IVariableDefinition`, `FirebaseDatabaseService`, `KubeConfig`, `Tangent`, `IChainableEvent`, `Events.pointerdragstart`, `EquipmentStatus`, `LeftObstacleSide`, `user`, `postcss.Declaration`, `SocketIO.Server`, `ScaleGroup`, `ChildRuleCondition`, `PolygonProps`, `InitializeStateAction`, `SapphireDbOptions`, `IClusterHealthChunkQueryDescription`, `d.FsItems`, `ClientInstance`, `LSTMCellLayerArgs`, `WaveType`, `FeatureInterface`, `BoundSphere`, `MonitoringConfig`, `ITypeFactory`, `ShippingService`, `TransformConfigUnion`, `Hsva`, `ICommandResult`, `UpdateCategoryDto`, `IGetTimeLimitReportInput`, `apid.ChannelId`, `WriterToString`, `StartMeetingTranscriptionCommandInput`, `IEntryDefinition`, `RemoteSeries`, `PointGeometry`, `ProgressBarService`, `StackPath`, `ColliderShape`, `ParsedDID`, `TagsProps`, `ts.ImportEqualsDeclaration`, `IAdjacencyCost`, `CollaborationWindow`, `DesignerNodeConn`, `OverlayReference`, `IProjectCard`, `ApplicationCloseFrame`, `SourceCodeLocation`, `FunctionCallContext`, `Encoding`, `DndEvent`, `LoaderFunction`, `FoldingRange`, `DropDown`, `Body2DSW`, `IRequestApprovalCreateInput`, `Separator`, `AcLayerComponent`, `WorkflowStepInputModel`, `CosmosdbAccount`, `FilesystemProvider`, `TabEntity`, `DIRECTION`, `IntervalTimelineEvent`, `WaitForEvent`, `PaymentChannelJSON`, `TransactionBuilder`, `IClusterDefinition`, `JsonRpcRequestPayload`, `requests.ListReplicationSourcesRequest`, `TimelineTrackSpecification`, `AggsCommonSetupDependencies`, `SerializedNodeWithId`, `CasesClient`, `Json`, `MatDatepickerIntl`, `Fetch`, `HTMLAudioElement`, `StakingTransactionList`, `ModelArtifacts`, `SerialAPICommandMachineParams`, `DataFrameAnalyticsListRow`, `UpdateChannelParams`, `ShaderVariant`, `AnimatedSprite`, `SvgPoint`, `TcpConnection`, `TransformCallback`, `DatabaseInterface`, `AGG_TYPE`, `BookingState`, `OotOnlineStorage`, `IFreestylerStyles`, `SCClientSocket`, `EntityState`, `ExternalProps`, `mergeFunc`, `MutableTreeModel`, `AnnotationLineProps`, `Allowance`, `SVGFilterElement`, `CrossProductNode`, `DescribeVolumesCommandInput`, `TrieMap`, `SubgraphDeploymentID`, `JoinerCore`, `DialogConfig`, `ParsedCssFile`, `ILease`, `TreemapSeriesNodeItemOption`, `TestDuplex`, `AiService`, `IIonicVersion`, `Models.OrderStatusReport`, `FieldUpdates`, `MUserId`, `AztecCode`, `MatchmakerTicket`, `IBatch`, `RTCPeer`, `FoldCb`, `Measurable`, `LoginPage`, `MoveT`, `ReleaseResource`, `SingleKeyRangeSet`, `CategoriesState`, `AboveBelow`, `MockCloudExecutable`, `ParsedMessagePartPlaceholder`, `ConfigurationContext`, `ParserService`, `YggdrasilAuthAPI`, `ParsedJSXElement`, `IP`, `NgxMdService`, `SettingNavigation`, `MediaDiagnosticChangedEventArgs`, `ExampleProps`, `ResponderHelper`, `InspectTreeResult`, `parseXml.Element`, `InputType.StyleAttributes`, `PlotConfigObject`, `Jwk`, `ESAssetMetadata`, `ELang`, `MapsVM`, `SafeAny`, `StateCreator`, `MultiSelectRenderProps`, `EventFactory`, `GetStaticProps`, `HttpWrapper`, `Scene3D`, `meow.Result`, `ListPingMonitorsRequest`, `Spaces`, `NullConsole`, `SqlStatisticsTimeSeries`, `FlattenedFunnelStep`, `Projects`, `SFAAnimationController`, `ITypedNode`, `IArticle`, `TPagedList`, `LabelValuePair`, `IMiddlewareProvider`, `IDateFnsLocaleValues`, `ObservableQueryValidatorsInner`, `CardAndModule`, `EslingPlugin`, `URI`, `RawShaderMaterial`, `CreateTokens`, `CompositeTraceData`, `WithBigInt`, `FormGroupState`, `GetServiceRoleForAccountCommandInput`, `MetricAggParam`, `AADResource`, `TsChipComponent`, `EchartsTimeseriesChartProps`, `V1PodList`, `AnyConfigurationSchemaType`, `DecimalFormatter`, `UserManagementService`, `cc.RenderTexture`, `RouteComponent`, `ParticipantsRemovedListener`, `NewMsgData`, `PureReducer`, `Handlebars.HelperDelegate`, `Requests`, `GlobalGravityObj`, `Radio`, `MerkleProof`, `MapPolygonSeries`, `IRChart`, `MessengerTypes.SendOption`, `ReadonlyNonEmptyArray`, `WalkerCallback`, `MetaKey`, `ChemControllerState`, `Modules`, `ComponentCompilerData`, `LinesTextDocument`, `AgCartesianChartOptions`, `Candle`, `TasksService`, `OperatorAsyncFunction`, `QueryHookOptions`, `CompilerOperation`, `Follower`, `WebResource`, `SubmissionServiceStub`, `AxisLabelOptions`, `TextAnimationRefs`, `LegacyService`, `EzRules`, `GenericConstructor`, `IEntityMetaOptions`, `BrowserHelper`, `ConfigDeprecation`, `UhkBuffer`, `Events.collisionstart`, `CommentResponse`, `RenderElementProps`, `instantiation.IConstructorSignature7`, `IDownloadOptions`, `API.storage.IPrefBranch`, `TaskParameter`, `CardView`, `ICredential`, `UploadedVideoFileOption`, `ApiCallByIdProps`, `PortingProjects`, `IGraphicOption`, `LogChildItem`, `DeletePermissionPolicyCommandInput`, `FactoryContextDefinition`, `SelectionSet`, `ObjectType`, `EveesMutation`, `IBoot`, `LayoutStyleProps`, `CompilerState`, `TabData`, `CoExpNum`, `NextFn`, `SecurityUtilsPlugin`, `GlobalMaxPooling2D`, `IChangeHandler`, `CurrencyMegaOptions`, `TPageWithLayout`, `PrimitiveFixture`, `Delta`, `MobileCheckPipe`, `TransformerStep`, `IStateTreeNode`, `ParsedResponse`, `FileChangeEvent`, `child.ExecException`, `CategoryPage`, `CalculatedColumn`, `providers.TransactionResponse`, `QueryCacheResult`, `GetAppInstanceRetentionSettingsCommandInput`, `XYArgs`, `GitHubService`, `requests.ListWafTrafficRequest`, `LatLng`, `SceneActuatorConfigurationCCReport`, `ResolveNameByValue`, `ConnectionHealthPolicyConfiguration`, `ModuleManager`, `IAPIFullRepository`, `UserRegisterData`, `BlogPostService`, `Line3`, `CanvasFontFamilies`, `SortedQuery`, `Stringifier`, `WebSocketEventListener`, `MemberAccessFlags`, `Applicative1`, `StageInterview`, `TabbedTable`, `ActionConfig`, `TraderWorker`, `Subscribe`, `ElectronLog`, `ProjectEntity`, `ComponentRegister`, `NoteCollectionService`, `PDFNumber`, `CreateBackupCommandInput`, `DisplayState`, `EventBinderService`, `LevelService`, `UpdateEvent`, `GetIn`, `SplittedPath`, `requests.ListSnapshotsRequest`, `PackageLockPackage`, `typedb.DBType`, `ZoneChangeOrderModel`, `OrbitCoordinates`, `NormalizedFormat`, `MaybeNestedArray`, `d.SitemapXmpResults`, `DataviewSettings`, `BoxObject`, `CanvasRenderer`, `IKeyPair`, `ListAst`, `IJWTPayload`, `NormalizeStyles`, `MaskServer`, `ExampleSourceFile`, `RestoreDBClusterFromSnapshotCommandInput`, `CounterfactualEvent`, `ApiErrorMessage`, `FormatProps`, `GraphPartitioning`, `DatasetManager`, `SwimlaneRecordPayload`, `TxLike`, `EventEmitter.ListenerFn`, `DescribeAlarmsCommandInput`, `AthleteSettingsModel`, `ServiceQuotas`, `DynamoDB.BatchWriteItemInput`, `UseSelectStateOutput`, `JPARandom`, `SQL`, `FlowLabel`, `TileCoords2D`, `InternalErrorException`, `CustomIntegrationsPluginSetup`, `CssClass`, `ITransitionPage`, `IFieldExpression`, `ProviderInfrastructure`, `RequestModel`, `Zeros`, `SyntaxKind`, `NodeModuleWithCompile`, `FzfResultItem`, `ITableAtom`, `OperationContract`, `DelayLoadedTreeNodeItem`, `DataTypesInput.Struct2Struct`, `PullRequestNumber`, `ModuleSpecifierResolutionHost`, `Opcode`, `ViewerRenderInput`, `CompilerEventFsChange`, `ITestAppInterface`, `ProfileModel`, `InvalidateAPIKeyResult`, `Contexts`, `ModelService`, `LegendPath`, `RuntimeTreeItem`, `IndexPatternsServiceDeps`, `IChannelModel`, `ReadonlyObjectKeyMap`, `Dialogue`, `Viewport`, `RegisteredServiceUsernameAttributeProvider`, `LookupKey`, `KeyboardListener`, `PrimitiveType`, `ParameterStructures`, `FormfieldBase`, `ExecutedQuery`, `SprintfArgument`, `ReflectionProbe`, `QueryConfig`, `Zone`, `AzExtTreeItem`, `WebhookClient`, `TwingFunction`, `PatternMappingEntryNode`, `KintoClientBase`, `LinearRegressionResult`, `RedisClientType`, `CaseConnector`, `OperatingSystem.macOS`, `Vec4Term`, `MessageSentListener`, `Mat4`, `RecurringCharge`, `ListTemplateVersionsCommandInput`, `CustomFunction`, `WexBimRegion`, `TimesheetFilterService`, `ActiveQuery`, `NameT`, `BeforeUnloadEvent`, `QueuedEvent`, `VerificationToken`, `FormInstance`, `LogData`, `ImagePicker`, `ts.ExportDeclaration`, `reduxLib.IUseAPIExtra`, `UpdateApplicationDetails`, `ValuesMap`, `IOrganizationProjectsFindInput`, `React.DragEventHandler`, `IVectorSource`, `ForkName`, `PageContainer`, `MdcChip`, `ArgsMap`, `CreditWords`, `IServerSideGetRowsParams`, `CachedBreakpoint`, `d3Transition.Transition`, `SharedFileMetadata`, `AstModule`, `TestingGroup`, `TransitionProps`, `EditorInterface`, `ExecutionActivity`, `Cardinality`, `GroupActorType`, `ModeManager`, `Not`, `IPersonDetails`, `ICertificate`, `FSNetwork`, `DescribeDatasetGroupCommandInput`, `vscode.CompletionItem`, `PatternAtomNode`, `SerializedValue`, `Shim`, `IMessage`, `HammerInstance`, `ViewerPreferences`, `GroupByColumn`, `Path8`, `CacheInstance`, `GqlContext`, `TreeCursor`, `SpreadAssignment`, `MockSdkProvider`, `ElementAnimateConfig`, `InterfaceWithDeclaration`, `IWorld`, `ExecuteOptions`, `IdentityService`, `SoFetchResponse`, `Song`, `TransportResult`, `NoiseSocket`, `IOrderedGroup`, `React.ElementType`, `GeometrySector`, `MiStageState`, `SocketType`, `CreateManyDto`, `THREE.Color`, `DocumentRegistry`, `SubscriptionsClient`, `PortRecordMap`, `StoreContext`, `telemetry.Properties`, `AssetOptions`, `DeployingWallet`, `ProjectSpecBase`, `DFChatArchiveEntry`, `requests.ListAutonomousContainerDatabasesRequest`, `DriverSurface`, `BlockNumberPromise`, `HTMLSlotElement`, `MenuI`, `UpdateContext`, `SBGClient`, `BlockCipher`, `OrderedDictionary`, `d.NodeMap`, `EventInteractionState`, `Computation`, `Angulartics2AppInsights`, `CanaryConfig`, `PackageToPackageAnalysisResult`, `IResizeInfo`, `TemplateStore`, `ICoinProtocol`, `JsonLdDocumentProcessingContext`, `AlgoFn`, `Classify`, `FaastModuleProxy`, `MigrateEngineLogLine`, `TabDataType`, `RegisteredModule`, `CustomGradientFunc`, `FormPage`, `ExpressRouteCircuit`, `Realm`, `TabPane`, `t.Transformed`, `ColumnSummary`, `StageDataHolder`, `GetReviewersStatisticsCollectionPayload`, `SimpleLinkedTransferAppState`, `NamedExportBindings`, `ConnectionType`, `Backbone.ObjectHash`, `Flo.ElementMetadata`, `FileState`, `RequestDetailsState`, `ControlCenterCommand`, `EmbeddableSetupDependencies`, `ValidResource`, `WithEnum`, `DefaultTreeElement`, `CrudRequestOptions`, `VisTypeAliasRegistry`, `EndpointClass`, `keyboardKey`, `WindowOptions`, `CommandLineOptionOfListType`, `BaseEditor`, `DomainEvent`, `DataUp`, `AstLocation`, `CalendarHeatmapData`, `AbstractSqlModel`, `RuntimeConfiguration`, `IChainConfig`, `ServicePort`, `CredentialService`, `ResetButtonProps`, `LoggerInstance`, `ts.LanguageService`, `Delayed`, `SaveOptions`, `ExpressionContext`, `IfStatementContext`, `MarkdownSerializerState`, `MUserAccountId`, `Itinerary`, `BaseFrame`, `IAngularEvent`, `RequiredAsset`, `ClientRequestSucceededEventArgs`, `ServerHelloVerifyRequest`, `MakeRestoreBackup`, `LeakyReLU`, `CCResponsePredicate`, `MaskListProps`, `ObservableUserStore`, `GeneratePipelineArgs`, `WriteTransactionRequest`, `HelpfulIterator`, `ToastController`, `EncryptOptions`, `QuestWithMetadata`, `TagnameValue`, `OrganizationPolicyType`, `UsersDetailPage`, `CopyrightInfo`, `MarkSpecOverride`, `Home`, `WorkItemService`, `UntypedProductSet`, `DecodeInfo`, `Natural`, `IProduct`, `IExperiment`, `TargetResponderRecipe`, `Primary`, `IFluidDataStoreFactory`, `React.ComponentProps`, `ResultWithType`, `ObservableApplicationContextFactory`, `MergeDomainsFn`, `TypedPropertyDescriptor`, `ConfigurationScope`, `SceneBinObj`, `AccountAssetDTO`, `IUserModelData`, `JsonObjectProperty`, `HttpAdapterHost`, `AdaptServer`, `WalletBalance`, `requests.ListModelDeploymentsRequest`, `CustomField`, `SettlementEncoder`, `TileProps`, `loader.LoaderContext`, `AxisSpec`, `AxisLabel`, `CosmosClient`, `MultiPickerOption`, `WidgetOptions`, `Then`, `ModifyEventSubscriptionMessage`, `IORedisInstrumentationConfig`, `SceneManager`, `PearlDiverSearchStates`, `BitmapData`, `Body`, `ReboostInstance`, `MDL0Renderer`, `U8.U8Archive`, `ChatParticipant`, `ActionProps`, `chokidar.FSWatcher`, `TupletNumber`, `UsageCollector`, `android.graphics.Typeface`, `FlexProps`, `BufferUseEnum`, `ClippedPolyfaceBuilders`, `AnchoredOperationModel`, `FeeLevel.Medium`, `QuerySuggestion`, `RepositoryData`, `ConfigChecker`, `MappedSetting`, `pxtc.CallInfo`, `DocParagraph`, `PreferenceScope`, `SnapshotDb`, `BuilderRun`, `NextHandleFunction`, `ParsedLog`, `Num`, `SavedObjectMigrationFn`, `RetryHandler`, `ReduceOptions`, `Layer`, `NavigationState`, `GuildService`, `StepRecoveryObject`, `CardService`, `ActionWithPayload`, `CheckBox`, `ProxyValue`, `PostComment`, `TileState`, `STPPaymentIntent`, `WorldReader`, `FramePublicAPI`, `ValidationEventTypes`, `ICompositionBody`, `GenericList`, `Repo`, `BatchedFunc`, `IDeployedApplicationHealthStateChunk`, `RepositoryEntity`, `JsonDocsComponent`, `tf.GradSaveFunc`, `MosaicPath`, `ChannelLeave`, `AnimatorState`, `HistoryStatus`, `ClassNode`, `NodeParser`, `MdcFormField`, `OrganizationEntity`, `PublishedStoreItem`, `d.CopyTask`, `IBuildStageContext`, `HttpError`, `child.ChildProcess`, `theia.Command`, `ITerminalOptions`, `DragEvent`, `BaseArrayClass`, `ParentSpanPluginArgs`, `ImportNameInfo`, `DeleteBucketPolicyCommandInput`, `ContractWrapper`, `PrettySubstitution`, `ManagedShortTermRetentionPolicyName`, `LevelGlobals`, `GalaxyMapIconStatus`, `EvaluateHandleFn`, `PermutationVector`, `ConfiguredPlugins`, `Declarations`, `NestedMap`, `MultiValue`, `PrismaConfig`, `NetworkId`, `FindArgs`, `AccountCustom_VarsEntry`, `ImageFov`, `StoreNames`, `VaultVersion`, `android.view.MotionEvent`, `ProtocolClient`, `ArrayConfig`, `BuildOutput`, `StateTimelineEvent`, `FormArray`, `NavigatedData`, `StripeShippingMethod`, `UpdateSettingModelPayload`, `Food`, `JSDocTypeLiteral`, `Imported`, `DeleteCertificateResponse`, `IStageConfigProps`, `FieldResultSetting`, `XPCOM.nsIURI`, `HalOptions`, `NoteModel`, `CalcAnimType`, `requests.ListShapesRequest`, `Sha256`, `UpdateJobCommandInput`, `SessionConfig`, `DraggableDirective`, `EdgeDisplayData`, `MergeBlock`, `ExecutionParams`, `Async`, `RequestCallback`, `GithubUser`, `AllowedKeyEntropyBits`, `CallableContext`, `EntityCollectionResolver`, `MaximizePVService`, `ImmutableStyleMap`, `TargetStr`, `SimpleChange`, `TextInsertion`, `DeviceSelection`, `SequenceConfiguration`, `LLRBNode`, `ISPRequestOptions`, `MenuType`, `ng.IScope`, `FeatureAppearance`, `GuidString`, `IScriptInfo`, `MaterialInstance`, `TheBasicMQStack`, `CkbMintRecord`, `LoginSuccess`, `ScriptObject`, `StoredCiphertext`, `EditorMode`, `Zip`, `SwitcherFields`, `PollingInterval`, `ListType`, `User`, `CheckAvailabilityProps`, `LookaroundAssertion`, `JsonTokenizer`, `FileDataSource`, `CallInfo`, `AxisLabelCircular`, `FbFormModelField`, `ComponentProperty`, `GetUpgradeStatusCommandInput`, `ExtendedAdapter`, `TxIn`, `RootStoreState`, `RadioValue`, `InstanceResult`, `STXPostCondition`, `TinymathAST`, `ParsedRange`, `MIRAssembly`, `Aspect`, `AdditionEdit`, `GroupParameters`, `PatternLayout`, `ConcreteComponent`, `IPropertyData`, `UpdateDeviceCommandInput`, `Concatenate`, `Second`, `JSX.HTMLAttributes`, `CustomHTMLElement`, `TPayload`, `DataTypeNoArgs`, `StorageHeader`, `DiagnosticCollection`, `ViewMode`, `ValidityState`, `FontData`, `VanessaTabItem`, `Observed`, `Registerable`, `GfxTextureDimension`, `CredentialOfferTemplate`, `HandlerCallback`, `RendererLike`, `EsDataTypeUnion`, `IStoreData`, `Rounding`, `Configuration`, `UpdatePackageCommandInput`, `WithBoolean`, `TT`, `StandardizedFilePath`, `ProtocolRunner`, `HotkeySetting`, `d.TransformOptions`, `EngineerSchema`, `StoryProps`, `UserLoginData`, `PointerDownOutsideEvent`, `OsdUrlTracker`, `MigrateCommand`, `CommandPayload`, `MenuItemProps`, `MyCompanyConfig`, `MIRFunctionParameter`, `HeaderGroup`, `AthenaRequestConfig`, `GraphQLResolverMap`, `IModalServiceInstance`, `PaymentsErrorCode`, `AuthError`, `CommandArg`, `Slots`, `AddressType`, `JKRCompressionType`, `StartDeploymentCommandInput`, `MainAccessResponse`, `CompositeType`, `BisenetV2CelebAMaskOperatipnParams`, `S3.GetObjectRequest`, `CoralContext`, `d.ListenOptions`, `GraphQLNonInputType`, `IExtensionMessage`, `InterfaceDefinitionBlock`, `ValueParserParams`, `ManagedID`, `RedBlackTreeIterator`, `WindowLike`, `TSESTree.ClassDeclaration`, `ParquetBuffer`, `TableBuilder`, `Ex`, `ITelemetryGenericEvent`, `ConventionalCommit`, `NetworkParams`, `RectF`, `Preparation`, `Apollo.Apollo`, `LanguageServiceExtension`, `ReportingEventLogger`, `MetaFunction`, `IOSNotificationPermissions`, `StructureTypeRaw`, `RewardTransactionList`, `RangeBucketAggDependencies`, `OtherNotation`, `Searchable`, `FormSection`, `MyObserver`, `IsBindingBehavior`, `DebugProtocol.SetVariableArguments`, `Enhancer`, `Transport`, `OrthogonalArgs`, `keyType`, `IUriMap`, `ButtonProps`, `TsExpansionPanelComponent`, `FnO`, `Models.WebHook`, `StartImportCommandInput`, `ReknownClient`, `Pbf`, `ChartLine`, `ConnectionState`, `TemplateTermDecl`, `Accessibility`, `GoalService`, `angular.ITimeoutService`, `IArrayType`, `AccessibilityKeyHandlers`, `MagicSDKWarning`, `SessionDataResource`, `NFT1155V2`, `NumericArray`, `requests.ListWhitelistsRequest`, `phase0.BeaconBlockHeader`, `WebViewMessageEvent`, `tf.Tensor5D`, `CachedType`, `OsmNode`, `CreateTransformer`, `SQLDatabase`, `StatusBarWidgetControl`, `IframeController`, `StoreCollection`, `SeriesMarkerRendererDataItem`, `ITenantSetting`, `BalmError`, `AllPlatforms`, `RailsFile`, `DataColumn`, `SpriteManager`, `CrudTestContext`, `Newline`, `GlobalConfiguration`, `SyslumennAuction`, `IFormatProvider`, `CompleteOption`, `SelectionSetToObject`, `WavyLine`, `ActivableKey`, `AbstractClass`, `Mouse`, `CloseEditor`, `ProgramProvider`, `VECTOR_STYLES`, `VerticalRenderRange`, `KeyIndexImpl`, `Dispatcher`, `E2EElement`, `AdminCacheData`, `MdcDialogRef`, `TypeSpec`, `DataCache`, `BBox`, `TargetConfig`, `vscode.OutputChannel`, `WhileStatement`, `TypeDBClusterOptions`, `AnyExpressionFunctionDefinition`, `BatchChangeSet`, `DockType`, `PushDownOperation`, `CacheVm`, `RepositoryInfo`, `Rgba`, `ISpec`, `IVersionedValueWithEpoch`, `TinaCMS`, `FormFieldErrorComponent`, `ServiceTemplate`, `StageName`, `ScriptParameter`, `TimeSpan`, `PickerOptions`, `YAMLNode`, `google.maps.Polygon`, `IAjaxSuccess`, `kind`, `ComponentPublicInstance`, `ParameterScope`, `Album`, `TestConfiguration`, `ActorContext`, `columnTypes`, `FileSystemFileHandle`, `ListComponent`, `ProgressReporter`, `BarLineChartBase`, `EngineWindow`, `Week`, `Bitmap`, `PokemonIdent`, `MinimongoDb`, `sdk.TranslationRecognitionCanceledEventArgs`, `RichLedgerRequest`, `VanessaGherkinProvider`, `BaseResourceHandlerRequest`, `ClientRemote`, `DaffAddressFactory`, `Parsed`, `StatusMessage`, `OutOfProcessStringReader`, `DragHelperTemplate`, `UriCommandHandler`, `DAL.KEY_5`, `AppStackMajorVersion`, `CategoryList`, `RendererFactory2`, `TradeDirection`, `IModdleElement`, `ExtHandler`, `DescribeNamespaceCommandInput`, `IFoundCursor`, `AutoInstrumentationOptions`, `ComponentCompilerLegacyContext`, `requests.ListDbSystemsRequest`, `FunctionOrConstructorTypeNode`, `PathHeadersMap`, `ComponentCompilerEvent`, `PieChartData`, `StageContentLayoutProps`, `InitializeHandlerOptions`, `CephLandmark`, `RosException`, `ts.NavigationTree`, `ListsSandbox`, `UpdateFileSystemCommandInput`, `RequestedCredentials`, `EventRequest`, `CommandService`, `AnimatorPlayState`, `IgetOpenRequests`, `EventResult`, `MediaRecorder`, `UrlSegment`, `JsDoc`, `TydomDeviceSecuritySystemData`, `Quality`, `ConfigParser`, `ManipulatorCallback`, `StringValueToken`, `TableDefinition`, `ConfirmDialogProps`, `SliceNode`, `ParseScope`, `ExecOpts`, `UniswapFixture`, `CheckFlags`, `ContactId`, `Json.ArrayValue`, `StyleRule`, `NodeRequest`, `TileIndex`, `SupClient.AssetSubscriber`, `StorageError`, `StepType`, `VariableNode`, `ConnectivityInfo`, `MessageFormatter`, `RNCookies`, `MdcTopAppBar`, `ProjectSettings`, `RxTranslation`, `DeleteProjectCommandOutput`, `Wire`, `ValidationVisOptionsProps`, `Enums`, `DelegateTransactionUnsigned`, `ActiveContext`, `FrameworkType`, `DebugConfigurationModel`, `MigrationDefinition`, `ISnapshotTreeWithBlobContents`, `GetInsightsCommandInput`, `KeyFunction`, `BlockTag`, `PermissionOverwriteResolvable`, `TypeMatcher`, `ApiDefService`, `MarginPoolInstance`, `DataViewBase`, `RelativePosition`, `IntentSummary`, `RendererContext`, `WordType`, `GLboolean`, `Serials`, `HintItem`, `requests.ListComputeImageCapabilitySchemasRequest`, `TransitionAnimation`, `BrowserError`, `ThunkArg`, `RepeatVector`, `IParserState`, `GuildMessage`, `GetThunkAPI`, `IPageContainer`, `TinaCloudCollection`, `DynamoDbDataSource`, `MapFn`, `PiEditUnit`, `ArrayType`, `ForkTsCheckerWebpackPluginState`, `ServiceWorker`, `FlattenContext`, `Opts`, `MethodGetRemainingTime`, `messages.SourceReference`, `Completion.Item`, `msRest.OperationURLParameter`, `StatsError`, `RPCMethodDescriptor`, `child_process.SpawnOptions`, `ZWaveLogInfo`, `BaseAuthState`, `FocusTrapFactory`, `WorkArea`, `XRView`, `IpcMainListener`, `ShippingAddress`, `BagOfCurves`, `VariableValueTypes`, `SourceBufferKey`, `FrameControlFactory`, `StubStats`, `ADialog`, `PersistenceProvider`, `ReferencedFields`, `FieldsAndMethodForPositionBeforeCurrentStrategy`, `RoomEntity`, `VectorPosition`, `AppElement`, `DSL`, `UpdateRegexPatternSetCommandInput`, `HTMLFrameElement`, `ICellRenderer`, `JestPlaywrightConfig`, `EditText`, `MatBottomSheetRef`, `APIs`, `StreamReport`, `Column`, `RNSharedElementStyle`, `ListGatewaysCommandInput`, `InspectionTimeRange`, `ObservableQueryBalanceInner`, `IconShapeTuple`, `RawRule`, `RobotApiResponse`, `LoggingConfiguration`, `TaskInfo`, `GX.PostTexGenMatrix`, `NotifyMessageType`, `CommandOption`, `CdsControl`, `HelloService`, `TSReturn`, `SiteInfo`, `CustomSmtpService`, `AggParamsItem`, `RecursiveArray`, `IHook`, `AssociateServiceRoleToAccountCommandInput`, `PayloadHandler`, `SwUrlService`, `RegularPacket`, `Templates`, `NodeJS.ReadWriteStream`, `IGlTFModel`, `JwtAdapter`, `ParseResponse`, `ProjectIdAndToken`, `SExpr`, `PainterElement`, `UseHydrateCacheOptions`, `EntityModel`, `Listener`, `DirectiveArgs`, `GlobalStoreDict`, `MatchPresenceEvent`, `MeshPrimitive`, `NexusObjectTypeDef`, `DeferredNode`, `AdminProps`, `IColumnDesc`, `IResolveDeclarationReferenceResult`, `ITouchEvent`, `ImageMapperProps`, `TRPCResult`, `requests.ListManagementAgentsRequest`, `OrderedStringSet`, `GraphInputs`, `CacheIndex`, `EntryHashB64`, `WatchStopHandle`, `IResizedProps`, `SimpleBBox`, `ODataParameterParser`, `RepositoryChangeEvent`, `RNode`, `BaseMemory`, `IFileSnapshot`, `AlarmAction`, `SelectableObject`, `SceneGfx`, `DynamicFormArrayGroupModel`, `JobDetails`, `u64spill`, `S.State`, `TemplateRef`, `PeerTreeItem`, `TalkOpenChannel`, `ImportDefaultSpecifier`, `Encounter`, `messages.DocString`, `GDQLowerthirdNameplateElement`, `RebaseConflictState`, `RepositoriesStore`, `RollupConfig`, `Mocks`, `ImageDecoder`, `StreamInfo`, `SitemapXmpResults`, `NodeKey`, `IAppStore`, `Signals`, `RouteModules`, `ExpNumSymbol`, `RepoSnapshot`, `SCN0_AmbLight`, `CacheTransaction`, `Suggestions`, `IOrganizationDocument`, `CurrentUserService`, `Geography`, `NotificationAction`, `ModelDeploymentType`, `ServerConnection.ISettings`, `StringLookup`, `GameBits`, `express.Express`, `WaitForScript`, `GetNamespaceResponse`, `ContainerInspectInfo`, `CounterState`, `StateDefinition`, `WebApi`, `DefaultFilterEnum`, `P2SVpnGateway`, `BucketAggType`, `ITimelineModel`, `MeshPhysicalMaterial`, `DatabaseVulnerabilityAssessment`, `EntityT`, `LinkedService`, `Requirement`, `ICSR`, `SoftVis3dShape`, `DiceRollerPlugin`, `SSHConfig`, `number`, `Hapi.ResponseToolkit`, `NgxDateFnsDateAdapter`, `PeekZFrame`, `d.ExternalStyleCompiler`, `SlotFilter`, `ReadContext`, `OAuthConfigType`, `ApplicationWindow`, `ExportSummary`, `TestNodeProvider`, `EntityRepository`, `BottomTabBarProps`, `MediaDevices`, `TextDocumentShowOptions`, `ToolbarProps`, `Base16Theme`, `LocalMicroEnvironment`, `AppBarProps`, `ComponentState`, `ODataQueryOptionsHandler`, `ts.FormatCodeSettings`, `schema.Specification`, `ObjectSelectionListState`, `WalletConnectConnector`, `IUsageMap`, `CutLoop`, `CardData`, `TransposedArray`, `TaskScheduling`, `DecoratedComponentClass`, `CreateModelResponse`, `IParameterValuesSourceProvider`, `E2EScanScenarioDefinition`, `WalletEntry`, `TypeEquality`, `InMemoryOverlayUrlLoader`, `ModuleStoreSettings`, `SFCDeclProps`, `BridgingPeerConnection`, `DeleteRepositoryCommand`, `CipherImportContext`, `ScoreService`, `ColumnId`, `CssItem`, `RestClient`, `StoryFn`, `d.ComponentOptions`, `StatBuff`, `TaskLogger`, `IQueryParamsResult`, `LiskErrorObject`, `google.maps.LatLng`, `Highcharts.DataGroupingApproximationsArray`, `MatchPathAsyncCallback`, `ITargetGroup`, `SandDance.VegaDeckGl.types.LumaBase`, `ScreenContextData`, `WebappClient`, `ImageObject`, `ModifyEventSubscriptionCommandInput`, `IRenderTask`, `CalculationYear`, `UpdateQuery`, `MicrosoftSynapseWorkspacesResources`, `ProposeCredentialMessage`, `UnregisterCallback`, `IModifierKeys`, `Parser.Infallible`, `BTCAccountPath`, `RouteAnimationType`, `CommanderOptionParams`, `TimeOffRequest`, `GameOptions`, `TerminalWidget`, `Submission`, `CSSSelector`, `LaxString`, `TranslationEntry`, `requests.ListBackupDestinationRequest`, `NodeEntry`, `HttpResponseOK`, `DownloadService`, `SpringConfig`, `ThunkDispatch`, `RPCMessage`, `TokenType`, `AlertMessage`, `MediaConfig`, `td.SMap`, `ExpressionModel`, `IAheadBehind`, `LoggerProvider`, `CPU`, `ClassExpression`, `EntityContainer`, `ws`, `DeleteSiteCommandInput`, `DialogComponent`, `ProfileServiceProxy`, `FilesystemNode`, `Couple`, `GeoJSON.Feature`, `CreateProgram`, `TFJSBinding`, `requests.ListExternalPluggableDatabasesRequest`, `RawPermissionOverwriteData`, `VarExpr`, `TableBatchSerialization`, `JsonWebKey`, `LVal`, `AnyArray`, `EventListenerOptions`, `JSXIdentifier`, `ErrorSubscriptionEvent`, `MessageTarget`, `lua_State`, `DesktopCapturerSources`, `ParsedConfirmedTransaction`, `winston.Logger`, `TrackParseInfo`, `DataProperty`, `NumOrString`, `ActivityInterface`, `ast.BinaryNode`, `HierarchyRpcRequestOptions`, `Concat`, `CreatePolicyVersionCommandInput`, `Day`, `CrochetRelation`, `VertexFormat`, `Elements.RichTextElement`, `ContextMenuItem`, `ts.FunctionExpression`, `NotificationSettings`, `Models.Exchange`, `IHistoryFileProperties`, `Notified`, `ExportedDeclarations`, `RenderableElement`, `FullIndexInfo`, `CallbackT`, `UsageStats`, `ExtraSessionInfoOptions`, `EntityConstructor`, `ChildInfo`, `JsonType`, `MgtFileUploadItem`, `Pager`, `NVMEntry`, `TransformStream`, `DistrictsGeoJSON`, `ReflectiveKey`, `Writeable`, `CourseType`, `HydrateStyleElement`, `GetPolicyRequest`, `CkElementContainer`, `TestInterface`, `ITaskSource`, `IStatusFile`, `AuditEvent`, `RecordingOptions`, `core.BTCInputScriptType`, `Events.postdebugdraw`, `SuperClient`, `MongooseModel`, `GradSaveFunc`, `SchemePermissions`, `LibResolver`, `ExploreOptions`, `RPCDescriptor`, `MatBottomSheetConfig`, `MockDialogRef`, `ObjectStorageClient`, `ERC20Mock`, `TwistyPlayerModel`, `Gender`, `SchemaDef`, `Cartesian3`, `SessionGetter`, `WsConnectionState`, `GitFileStatus`, `LineAnnotationStyle`, `CBPeripheral`, `VisualObjectInstanceEnumeration`, `ChartModel`, `ProxyServerType`, `ng.ILocationService`, `ShipBlock`, `DDL2.OutputDict`, `CreateRequestBuilder`, `PathAddress`, `IAvatarProps`, `ChannelData`, `CityPickerColumn`, `DeletedAppRestoreRequest`, `AngularFireAuth`, `LocalStorageService`, `OpenYoloCredentialRequestOptions`, `FilesState`, `BuildrootAction`, `HttpsFunction`, `ICore`, `ScatterSeries`, `ReuseItem`, `React.ChangeEventHandler`, `Cookies`, `ServiceControlPolicyResource`, `GitPullRequestWithStatuses`, `BatchNormalizationLayerArgs`, `IStashTab`, `CryptoFactory`, `PartyMatchmakerAdd_NumericPropertiesEntry`, `IAutoEntityService`, `SQS`, `ObjectMap`, `SliderBase`, `Servers`, `ITestStep`, `RobotHost`, `GlobalCredentials`, `WasmQueryData`, `GetPermissionPolicyCommandInput`, `ErrorSubscriptionFn`, `BotonicEvent`, `ICategoryCollection`, `OpenSearchDashboardsReactContext`, `MoonbeamDatasource`, `ActionTicketParams`, `RE6Module`, `FieldNode`, `HttpMetadata`, `Fig.Spec`, `net.Socket`, `ExpressionRenderError`, `iElementInfo`, `TStyleSheet`, `UpdateAppInstanceUserCommandInput`, `PyrightPublicSymbolReport`, `MetadataArgsStorage`, `RawMetricReport`, `AsyncSink`, `UiActionsService`, `ViewProps`, `ethers.providers.BlockTag`, `TableSearchRequest`, `Inspector`, `LogsConfig`, `ScaleBand`, `UrlFormat`, `ArenaAllocationResult`, `QCfg`, `SlideDefinition`, `ParserMessageStream`, `EditionId`, `TreeState`, `ModalDialogParams`, `WebpackConfig`, `IFilterTarget`, `SeedOnlyInitializerArgs`, `SvgItem`, `HardhatRuntimeEnvironment`, `P2PMessagePacket`, `BodyProps`, `a.Expr`, `LogWriteContext`, `Spine`, `WildcardProperty`, `Quill`, `IAddresses`, `LocalTitle`, `ListJobRunsCommandInput`, `HIRNode`, `BreadcrumbsProps`, `FabRequestResponder`, `Procedure`, `PoolClient`, `DaffCartStorageService`, `IHttpClientResponse`, `TemplateArguments`, `SecurityDataType`, `WebPhoneSIPTransport`, `DeleteRequestBuilder`, `Hunspell`, `PageContext`, `ColorPoint`, `PagesLoaded`, `SideType`, `MessageStateWithData`, `IBankAccount`, `FeedFilterFunction`, `ParsedAccountBase`, `AnimGroup_TexMtx`, `ListDatasetEntriesCommandInput`, `SakuliCoreProperties`, `QState`, `ObjectOf`, `ResizeChecker`, `ConfigParameters`, `K3dClusterNodeInfo`, `EnvironmentResource`, `SelectToolConfig`, `$T`, `d.PrerenderUrlResults`, `AvailableProjectConfig`, `S3`, `LayoutService`, `PlanPriceSpecManager`, `ReputationToken`, `IZoweUSSTreeNode`, `Twit`, `RefList`, `HTTPNetworkInterface`, `PolicyResponse`, `GcListener`, `PvsDefinition`, `nsIURI`, `SignedOrder`, `ConeRightSide`, `NamespaceGetter`, `BlenderPathData`, `NormalizedReadResult`, `PushPathResult`, `ReadModelInterop`, `ELanguageType`, `FullDir`, `GeometryData`, `BlockchainWalletExplorerProvider`, `POCJson`, `NonMaxSuppressionResult`, `GraphQLFieldConfig`, `SessionTypes.RequestEvent`, `SavedObjectAttributes`, `CronExpression`, `forceBridgeRole`, `TestExplorer`, `MiddlewareMap`, `LodopResult`, `MultiValueProps`, `ScmFileChangeNode`, `DominoElement`, `ShareStore`, `FileList`, `ModelDispatcher`, `MockComponent`, `BrowserFields`, `EquipmentService`, `OpenApiApi`, `ControllerClass`, `EdgeGeometry`, `GlitzClient`, `CommonLayoutParams`, `ClientData`, `ErrorAction`, `AdditionalProps`, `PermissionsService`, `Cartographic`, `ContinueResponse`, `GeoLevelInfo`, `ChatErrors`, `PartialLax`, `unitOfTime.Base`, `DescribeAppInstanceUserCommandInput`, `Port`, `TabElement`, `AnimationComponent`, `JoinPredicate`, `IBucketAggConfig`, `StorageIdentifier`, `PackageRelativeUrl`, `PrivateUserView`, `Comparator`, `Gate`, `CartoonOperatipnParams`, `This`, `BucketSegment`, `StripeSetupIntent`, `Types.IResolver`, `LspDocuments`, `RobotApiErrorResponse`, `SymbolicTensor`, `ContinuousParameterRange`, `TwingNodeExpression`, `IssuerPublicKeyList`, `SentInfo`, `t.IfStatement`, `ProjectInterface`, `CommonInterfaces.Plugins.IPlugin`, `RendererOptions`, `AsyncStateNavigator`, `ICurrentArmy`, `Ticket`, `ViewDefinitionProps`, `UnixTerminal`, `ProsodyFilePaths`, `GetRuleGroupCommandInput`, `SetModel`, `GeneratedQuote`, `NodeSDK`, `ToastRequest`, `FetcherField`, `ScaleOrdinal`, `IProjectInfo`, `ColorOverrides`, `IInterpreterRenderHandlers`, `FieldEntity`, `nockFunction`, `ISettingStorageModel`, `FeederPool`, `VirtualScope`, `FileResource`, `JulianDay`, `GitCommittedFile`, `IThrottler`, `reminderInterface`, `Animated.Animated`, `IBazelCommandAdapter`, `GameEvent`, `E`, `Environments`, `Printable`, `CompaniesService`, `NativeSyntheticEvent`, `NavigationNavigator`, `KeccakHash`, `ApplicationTypeGroup`, `MergeableDeclarationSet`, `DeleteAppCommandInput`, `requests.ListInstanceAgentPluginsRequest`, `TxMassMigration`, `NotificationProperty`, `SocketConnection`, `StdFunc`, `Tagging`, `TileMetadataArgs`, `ValidationProblemSeverity`, `IView`, `LoadBalancerListenerContextProviderPlugin`, `SnippetString`, `FilterOperator`, `EdmT`, `DeleteUserCommandInput`, `UseTransactionQueryOptions`, `RangeRequest`, `VersionEdit`, `StyletronComponent`, `BorderRadiusDirectional`, `reduxLib.IState`, `PropItem`, `LambdaServer`, `GenericIndexPatternColumn`, `DescribeFargateProfileCommandInput`, `CanvasTypeHierarchy`, `HTMLVideoElement`, `Fillers`, `W6`, `FundingCycleMetadata`, `IRawLoadMetricReport`, `NetworkName`, `Stereo`, `StreamOptions`, `TagSpec`, `VisitOptions`, `WithExtendsMethod`, `StringBuilder`, `EntContract`, `ScrollerAnimator`, `SObjectDescribe`, `OAuthCredential`, `TagValue`, `Sha512`, `FixedDepositsService`, `NormMap`, `AnalyticsModule`, `ShowConflictsStep`, `Matrix3x3`, `GravityArgs`, `FeatureProps`, `MIRPrimitiveListEntityTypeDecl`, `ModelCompileArgs`, `MongoQueryModel`, `FeeRate`, `Conversation`, `EsAssetReference`, `AllowArray`, `PingPayload`, `Alignment`, `IProc`, `PermissionsCheckOptions`, `CreateHotToastRef`, `TRANSFORM_STEP`, `VariantGeometry`, `LegendOptions`, `IAsyncEqualityComparer`, `RouteValidationResultFactory`, `Node3D`, `ContractsState`, `requests.ListAutonomousDatabasesRequest`, `UserThemeEntity`, `ILectureModel`, `Pattern`, `ColumnConfig`, `RBXScriptConnection`, `HelmRelease`, `interfaces.BindingWhenOnSyntax`, `MatchedFlow`, `GetDomainNameCommandInput`, `HandlerNS.Event`, `HTMLAttribute`, `FacetsState`, `QUnitAssert`, `IFollow`, `LazyCmpLoadedEvent`, `EditValidationResult`, `ScriptingLanguage`, `WriteLock`, `LegacyCallAPIOptions`, `Babel`, `Blip`, `ValueMetadata`, `iTunesMusicMetaProvider`, `PersonEntity`, `MdxListItem`, `RuleFunctionMeta`, `ng.ui.IStateProvider`, `Assembly`, `MessagesService`, `VcsItemConfig`, `TTK1`, `MemberRepository`, `MaxAge`, `ModuleBuilderFileInfo`, `TransactionVersion.Mainnet`, `TModule`, `TypeScriptVersion`, `ExpressionAstFunctionBuilder`, `Spherical`, `restm.IRestResponse`, `RawRuleset`, `PublicApi`, `FileBrowserItem`, `SimulcastUplinkObserver`, `SafeVersion`, `Locale`, `d.HttpRequest`, `GX.CompCnt`, `MediaStreamOptions`, `LspDocument`, `TranslationGroup`, `GraphicContentProps`, `ConsolidatedCertificateRequest`, `ISortOptions`, `LoggingConfig`, `IStrokeHandler`, `Dummy`, `AudioRule`, `VorlonMessage`, `ISocketBase`, `FrontCardsForArticleCount`, `RedisCache`, `d.JsonDocsProp`, `Col`, `SeparatedNamedTypes`, `interfaces.Binding`, `DAL.DEVICE_ID_COMPASS`, `NSDateComponents`, `ChangeListener`, `IStatusButtonStyleProps`, `WebAccount`, `OfAsyncIterable`, `TransactionSegWit`, `TestKafka`, `LeftRegistComponentMapItem`, `ExprListContext`, `UserInfoResource`, `WrappedWebSocket`, `TreeModel`, `TableComponentProps`, `IMusicMeta`, `types.signTx`, `DispatchOptions`, `TabularSource`, `admin.firestore.DocumentSnapshot`, `IGradient`, `PlanSummaryData`, `SYMBOL`, `TEObject`, `VideoModes`, `EFood.Session`, `IConnect`, `SkeletonHeaderProps`, `GraphqlApi`, `FilterTrailersStatusValues`, `SwaggerPathParameter`, `ts.Program`, `Options.Publish`, `ComponentMetaData`, `IDriverInfo`, `OsmRelation`, `JSEDINotation`, `CallCompositeStrings`, `Substitution`, `JsonAPI`, `BotMiddleware`, `CharacterSet`, `ExpressRequestAdapter`, `ObserveForStatus`, `WebSiteManagementModels.Site`, `AttributeParser`, `PluginDefinition`, `NamedFluidDataStoreRegistryEntries`, `CustomSkillBuilder`, `FilmQueryListWrapper`, `PermissionConstraints`, `MatTableDataSource`, `DeleteJobResponse`, `Flags`, `Floating`, `SnapshotAction`, `FilterEvent`, `ITileDecoder`, `ResolvedConfigFileName`, `LightSet`, `GitStatusFile`, `NumberValueSet`, `HipiePipeline`, `PrintStackResult`, `IBuildConfig`, `AttestationsWrapper`, `ma.TaskLibAnswers`, `TreeGridTick`, `EventInterpreter`, `IBoxSizing`, `RendererElement`, `ToastType`, `FutureWalletStore`, `AnyResource`, `CubicBezierAnimationCurve`, `angular.auto.IInjectorService`, `L2Args`, `InvocationContext`, `UserConfigDefaults`, `ArDriveAnonymous`, `WebsiteScanResultProvider`, `HostString`, `TestSandbox`, `MsgPieces`, `GetReviewerStatisticsPayload`, `ExprEvaluatorContext`, `TmdbMovieResult`, `HttpResponseRedirect`, `LeakDetectionSignal`, `FloatingLabel`, `d.FsReaddirOptions`, `PropertyResolveResult`, `MatcherGenerator`, `DashboardProps`, `IFileModel`, `SwipeActionsEventData`, `CommerceTypes.CurrencyValue`, `UpdateDestinationCommandInput`, `ComponentReference`, `AmqpConnection`, `YearCell`, `FirmwareUpgradeIpcResponse`, `IMenuItem`, `ProcessInfo`, `Label`, `TimeoutRacer`, `RumSessionManager`, `StartRecordingRequest`, `MutableSourceCode`, `ListConfigurationSetsCommandInput`, `BaseSkillBuilder`, `IChannelsDatabase`, `DocumentSpan`, `OverlapRect`, `KanbanRecord`, `Name`, `CartesianTickItem`, `PassNode`, `ApplicationService`, `LegacyTxData`, `DataFrameAnalyticsStats`, `GenericNotificationHandler`, `Dependency1`, `SerializedStyles`, `BuildrootUpdateType`, `Icu`, `alt.Player`, `IRegisterNode`, `ClipShape`, `ExecutionOptions`, `Endpoints`, `IBuildTaskPlugin`, `SignShare`, `Path2D`, `Electron.BrowserWindowConstructorOptions`, `BuilderOptions`, `BasicColumn`, `OmitInternalProps`, `NavigatorOptions`, `IsWith`, `IWmPicture`, `PowerAssertRecorder`, `Callbacks`, `HapiHeaders`, `AppStateType`, `SRule`, `ContextMenuProps`, `InstallForgeOptions`, `IUserPP`, `AnalyticsConfig`, `TemplateProviderBase`, `AssociationValue`, `azure.Context`, `Vector4`, `ColorType`, `PaymentResponse`, `ZipLocalFileHeader`, `btVector3Array`, `PatchFunction`, `EventSystemFlags`, `SummaryCalculator`, `IChannelAttributes`, `NotificationsStart`, `ResponsiveProp`, `MenuID`, `SpaceBonus`, `LitElement`, `ProviderPosition`, `ParseAnalysis`, `ObjectFieldNode`, `BotSpace`, `MDL0`, `CreateReplicationConfigurationTemplateCommandInput`, `Captcha`, `CreateIPSetCommandInput`, `SolcOutput`, `CurveChain`, `NotificationPermission`, `TestSink`, `OptionalObject`, `ThemeCoreColors`, `ContextWithFeedback`, `ArrayWrapper`, `InternalSession`, `URLQuery`, `SidebarProps`, `BackgroundFilterSpec`, `DebugProtocol.LaunchResponse`, `LocatorExtended`, `MDCChipCssClasses`, `AttrParamMapper`, `PuppetCacheContactPayload`, `BlockchainExplorerProvider`, `ExpressionsCompilerStub`, `DBOp`, `Tensor6D`, `AttributePub`, `CodeActionsOnSave`, `PerformanceObserverEntryList`, `IError`, `React.UIEvent`, `videoInfo`, `TaskProps`, `BotAction`, `SavedObjectsResolveResponse`, `ObjectSchemaProperty`, `ITodoState`, `SerializableValue`, `IStateCallback`, `CodePointPredicate`, `IotRequestsService`, `InputToken`, `IdentityClient`, `ISnippetInternal`, `JPABaseParticle`, `MediaPlaylist`, `UniqueSelectionDispatcherListener`, `IMainClassOption`, `Watermark`, `IVideoService`, `InMemoryProject`, `RegionLocator`, `DynamoDB.PutItemInput`, `UsersController`, `InsertEvent`, `Metadata_Add_Options`, `SubSymbol`, `ShapePath`, `EventCategory`, `CacheStorageKey`, `ITestScript`, `Creator`, `DocumentChangeAction`, `cg.Color`, `OrderForm`, `ArgumentsCamelCase`, `PanelLayout`, `WebGLComponent`, `tfconv.GraphModel`, `IScreenInstance`, `SerialBuffer`, `Vp8RtpPayload`, `AbstractToolbarProps`, `ProtocolMapperRepresentation`, `HdEthereumPayments`, `SortableEdge`, `DAL.DEVICE_OK`, `CodebuildMetricChange`, `GfxAttachmentP_WebGPU`, `MonoTypeOperatorAsyncFunction`, `ZoneModel`, `PA`, `AttendeeModel`, `SitecorePageProps`, `MiddlewareArray`, `IdentityView`, `SKLayer`, `TransformProps`, `LoggerText`, `OptionEntry`, `FN`, `QueryEngineBatchRequest`, `GrpcConnection`, `OptionService`, `OptionalKind`, `DBDoc`, `BuildConditionals`, `BatchRequestSerializationOptions`, `SavedObjectsRemoveReferencesToOptions`, `XHRResponse`, `ExpressionOperand`, `IBufferView`, `ReCaptchaInstance`, `TSDNPromise.Reject`, `ListingNodeRow`, `OptionsNameMap`, `ClientMetricReport`, `MDCChipActionFocusBehavior`, `DAL.DEVICE_ID_MSC`, `NestedRoutes`, `TestLedgerChannel`, `OAuthClient`, `GetItemFn`, `FileCodeEdits`, `ModuleInstanceState`, `ManifestMetaData`, `FunctionalComponent`, `OperationURLParameter`, `AlternatingCCTreeNode`, `ApolloResponse`, `DateFnsConfigurationService`, `IDiagram`, `ListImagesResponse`, `TestContextData`, `EmitFiles`, `IWebPartContext`, `SuiteThemeColors`, `IAttrValue`, `FlattenedXmlMapWithXmlNameCommandInput`, `ANodeStm`, `ContractReceipt`, `ModeName`, `ResourceDetails`, `ElementAnalysis`, `IProtoNode`, `Factory`, `LayerRecord`, `TLE.StringValue`, `Symbol`, `TfCommand`, `BufferWriter`, `StackNavigationProp`, `XPCOM.nsIChannel`, `DataTexture`, `lsp.Position`, `Cheerio`, `ITransform`, `ThematicDisplayProps`, `RequestForm`, `ListTagsForResourceOutput`, `GroupTypeUI`, `requests.ListRunsRequest`, `ITEM_TYPE`, `IRGBA`, `IModuleMinificationResult`, `ListGroupUsersRequest`, `FacetOption`, `SecondaryIndexLayout`, `VpcTopologyDescription`, `ResourceState`, `RedisCommandArguments`, `L`, `AuthGuard`, `CustomBinding`, `NoelEvent`, `WebpackError`, `CallClient`, `ILoggedProxyService`, `InstanceContainer`, `Ping`, `FileSystemProviderWithOpenReadWriteCloseCapability`, `Arg`, `Model`, `MonacoEditor`, `$p_Declaration`, `ReferenceMonthRange`, `ScaleModel`, `Settings`, `CredOffer`, `requests.ListAutonomousDatabaseDataguardAssociationsRequest`, `TabContainerPanelComponent`, `PageObject`, `Map4d`, `IncrementalNodeArray`, `StoreResource`, `FactionMember`, `TableCellPosition`, `requests.ListDomainsRequest`, `SourceService`, `ParsedSource`, `CollatedWriter`, `FormAzureStorageMounts`, `FreeBalanceState`, `GraphicStyles`, `TestHotObservable`, `ReportId`, `Sash`, `StructuredError`, `HardwareModules`, `EventInput`, `WorkRequest`, `MeshNormalMaterial`, `GX.BlendFactor`, `ListDomainsCommandOutput`, `Money`, `MessageBuilder`, `PrismScope`, `MdcRipple`, `AsyncResult`, `TransformOption`, `CallProviderProps`, `PackageName`, `OriginalDocumentUrl`, `ThyResizeEvent`, `StorageAccount`, `SearchUsageCollector`, `IDatabaseConfigOptions`, `TriumphCollectibleNode`, `TspanWithTextStyle`, `Layout`, `UseCase`, `AssertionLocals`, `Binary`, `Extract`, `grpc.ServiceError`, `SelectableTreeNode`, `YVoice`, `OperationTypes`, `nsIDOMWindowUtils`, `HttpCode`, `CommandLineTool`, `SessionImpl`, `BooleanCB`, `LightingFudgeParams`, `ItemBuilder`, `ICrop`, `Categories`, `models.RegEx`, `SetbackState`, `SymbolType`, `Datatype`, `PursuitRow`, `FileDescriptorProto`, `FSNoteStorage`, `InversifyExpressServer`, `PngPong`, `DeleteUserCommandOutput`, `DateAxis`, `UnaryOpNode`, `ResolveablePayport`, `viewEngine_ViewRef`, `IAccountInfo`, `ESLSelectOption`, `PatchFile`, `CustomImage`, `Resolve`, `TreeWalker`, `ParserInfo`, `QuestionCollection`, `StackActionType`, `NavigableHashNode`, `CloseButtonProps`, `ScriptObjectField`, `IModelRpcProps`, `CreateImportJobCommandInput`, `CountArguments`, `AppStoreModel`, `IApplication`, `CustomContext`, `PreviewSettings`, `Pagination`, `CronOptions`, `Shelf`, `LGraph`, `VcsAccount`, `SuccessAction`, `IFieldMap`, `Id`, `DescribeDatasetCommand`, `PhoneNumber`, `SagaActionTypes`, `AlertService`, `ModList`, `SmartHomeHandler`, `SCNVector3`, `VirtualApplication`, `StorageInterface`, `redis.ClientOpts`, `RemoteParticipant`, `ByteString`, `ParsedTestObject`, `IAdministrationItemRoute`, `ConfigSchema`, `IHotspotIndex`, `TestNodeList`, `RepositoryService`, `HierarchyProvider`, `CodeUnderliner`, `ConstRecord`, `ProposalManifest`, `ExtractGroupValue`, `ActionsRecord`, `DocsTargetSpec`, `OpenerOptions`, `Math.Vector3`, `MediationStateChangedEvent`, `BrowserRequest`, `IDetailsProps`, `web3.Connection`, `ChainID`, `Injectable`, `DecodedLog`, `AllowedLanguage`, `IParagraphMarker`, `DescribeClustersRequest`, `WaitTaskOptions`, `Links`, `NullableSafeElForM`, `PopoverProps`, `Fail`, `SplitDirection`, `VideoDeviceInfo`, `SpyObject`, `SubgraphDataContextType`, `BlobStore`, `TitleService`, `BoneSlot`, `ParsedUtil`, `Lumber`, `SweetAlertOptions`, `ApiOptions`, `PrintExpressionFlags`, `Region`, `WaitTask`, `ProdoPlugin`, `Autocomplete`, `Matcher`, `InputStep`, `BSPRenderer`, `TestApp`, `GeneratedKeyName`, `IResponse`, `AccentIconStyles`, `OptionValue`, `ListClustersCommandInput`, `InputTextNode`, `ChainableHost`, `Replay`, `AnalysisCompleteCallback`, `UpdateOneInputType`, `FormInputs`, `SocketService`, `Margins`, `CreateAccountCommandInput`, `TThis`, `func`, `LocalTag`, `HTMLIonBackdropElement`, `DeleteNetworkProfileCommandInput`, `BrowserFetcher`, `ServerIO`, `InstallationQuery`, `MpegFrameHeader`, `EnabledFeatures`, `requests.ListMaintenanceRunsRequest`, `JSDocNonNullableType`, `PaneProperty`, `WithCSSVar`, `IBytes`, `ParsedOrderEventLog`, `IPriceDataSource`, `TaggedTemplateExpression`, `RenderFlag`, `IconBaseProps`, `CCAPI`, `_IIndex`, `CampaignTimelineChanelsModel`, `ToneAudioBuffer`, `MemberType`, `indexedStore.FetchResult`, `TextureManager`, `Lib`, `ApplicationOpts`, `CategoryTranslation`, `SendResponse`, `MemoryRenderer`, `NotificationAndroid`, `CannonBoxColliderShape`, `ContractBuilder`, `LockedDistricts`, `Segment`, `DiagnosticWithFix`, `Architecture`, `Objkt`, `HTTP_METHODS`, `Injection`, `DefaultEditorSize`, `Highcharts.Popup`, `LegacyRequest`, `HierarchyQuery`, `CollectionProp`, `AuthParams`, `AwsOrganizationReader`, `DaffCategoryFilterRangeNumericFactory`, `OrderByStep`, `_Code`, `LaunchEventData`, `ChangeSet`, `EditableNumberRangeFilter`, `MessageReceivedListener`, `IGameObject`, `TranslationItemBase`, `GroupParameterMethod`, `ColorAxis.Options`, `EmitType`, `EvaluatedChange`, `GasMode`, `SearchSequence`, `RouterCallback`, `ProposalActions`, `StraightCurved`, `org`, `ValidateFunction`, `LegendItemExtraValues`, `TRouter`, `ComponentCompilerListener`, `PromisedComputed`, `AudioStreamFormatImpl`, `Toolbar`, `JsonRpcProxy`, `TAttributes`, `IAzureNamingRules`, `AggConfig`, `SecurityGroupRule`, `ITrackInfo`, `RegistryInstance`, `PageElement`, `EqualContext`, `RepeatForRegion`, `AuthenticateFacebookRequest`, `t.VariableDeclaration`, `UserConfigExport`, `Euler`, `FILTERS.PHRASES`, `RigidBody`, `DialogSubProps`, `Model.LibraryStoreItemState`, `IPropertyWithName`, `LayoutNode`, `ElasticPool`, `ExecController`, `InferableAction`, `TileSet`, `ShContextMenuItemDirective`, `UserSchema`, `GoogleBooksService`, `EdgeImmutPlain`, `DummyNode`, `DateMarker`, `CompilerConfiguration`, `IRenderOptions`, `IAppProps`, `SettingsCallback`, `CreateAliasRequest`, `ErrorArgs`, `AnimationPlayer`, `BasicTemplateAstVisitor`, `AutoconnectState`, `SerializedObjectType`, `ConceptMap`, `PaginationNextKey`, `FolderNode`, `ObsConfiguration`, `ColorAxis`, `NodeLoadMetricInformation`, `CallbackManager`, `QueryBuilderFieldProps`, `TECall`, `Electron.Event`, `FinalInfo`, `Processes`, `ServiceDescriptorProto`, `MapMode`, `RPiComponentType`, `PoolFields`, `IHawkularRootScope`, `GetResponseBody`, `EventCallback`, `Transform2D`, `THREE.PerspectiveCamera`, `PartialResolvedVersion`, `Drone`, `api.ITree`, `LightInfo`, `FocusZoneDefinition`, `PortInfo`, `Bm.ComposeWindow`, `NavOptions`, `ShuftiproInitResult`, `IVectorLayer`, `Hill`, `ParsedDirectiveArgumentAndInputFieldMappings`, `ClipId`, `FallbackProvider`, `HoistState`, `ConnectedPosition`, `DialogflowApp`, `IAssignment`, `RouteEffect`, `TrackId`, `ScanCommandInput`, `requests.ListManagementAgentImagesRequest`, `ParameterSpec`, `DeleteAuthorizerCommandInput`, `IFileInfo`, `B10`, `PropertyChangedEventArgs`, `ReconfigResponseParam`, `ICellInfo`, `TempFile`, `MiddlewareArgs`, `InitConfiguration`, `ColorPresentation`, `CachedKey`, `HTMLIonTabElement`, `SvelteConfig`, `Thumb`, `ISerializedActionCall`, `WithStatement`, `EditorFile`, `ActorComponent`, `OpenChannelMessage`, `BrowserSimulation`, `IOdspResolvedUrl`, `DictionaryType`, `FieldTypes`, `ParseTreeListener`, `LocationObject`, `ast.SyntaxNode`, `RatingStyleProps`, `TestMethod`, `TexMap`, `Uni.Node`, `BaseParser`, `AppHelperService`, `TestController`, `PackageChangelogRenderInfo`, `DropdownItemProps`, `com.nativescript.material.bottomsheet.BottomSheetDialogFragment`, `TouchPulse`, `Survey.Survey`, `CachedPackage`, `CollidableCircle`, `ScrollToColumnFn`, `CornerSite`, `ReactMouseEvent`, `MetricId`, `chrome.runtime.MessageSender`, `IndexingRuleAttributes`, `ExtraInfoTemplateInput`, `Sharp`, `ThyDialogContainerComponent`, `MockRouteDefinition`, `IAnyStateTreeNode`, `ABLTableDefinition`, `RequestSession`, `MangoQuerySelector`, `SelectContext`, `ToLatexOptions`, `Screwdriver`, `TagResourceCommand`, `AnimationResult`, `DescribeStacksCommandInput`, `AuthAccessCallback`, `PluginDevice`, `ICourseDashboard`, `IImageryConfig`, `Adventure`, `MetricsService`, `ModuleOptions`, `IHelpCenter`, `GetUpgradeHistoryCommandInput`, `DevToolsExtension`, `RequestDto`, `HardhatConfig`, `GX.Command`, `SlateNode`, `DocfyService`, `AppInitialProps`, `CirclinePredicateSet`, `TransformListRow`, `GtRow`, `RawContract`, `SnapshotField`, `SignedAndChainedBlockType`, `GfxRenderDynamicUniformBuffer`, `ServeAndBuildChecker`, `RESTClient`, `RowGroup`, `ScopeSymbolInfo`, `MapAdapterUpdateEnv`, `SvelteSnapshotFragment`, `ZAR.ZAR`, `OperatorSpec`, `Road`, `WalkerStateParam`, `NodeMaterialConnectionPoint`, `FormErrorsService`, `ScaleCompression`, `NgModel`, `ValidationAcceptor`, `ContextTypes`, `BaseHeader`, `SyncEngine`, `FIRStorageReference`, `PresentationRpcResponse`, `CancelSignal`, `BinStructItem`, `LegacySocketMessage`, `ExpandedBema`, `S3MetricChange`, `TypeVarMapEntry`, `ISelectHandlerReturn`, `WebApiTeam`, `ISetItem`, `FrameItem`, `BrowsingPage`, `FileContext`, `AuthorizationErrorResponse`, `FormError`, `KeyValueStore`, `ColorStateList`, `TSTypeParameterDeclaration`, `IPair`, `TSBuffer`, `CollectionNode`, `MosaicDirection`, `GitLog`, `DaffCartShippingInformation`, `Rehearsal`, `requests.ListDynamicGroupsRequest`, `AzureParentTreeItem`, `ts.ArrowFunction`, `ServiceContainer`, `LinkType`, `UIComponent`, `PrimitiveSelection`, `Expiration`, `FirestoreSimple`, `ParenthesizedTypeNode`, `RateLimit`, `Icon`, `StackNode`, `MIRConstructableInternalEntityTypeDecl`, `ProductA`, `ServiceInstance`, `TestObservable`, `TemplateWithOptionsFactory`, `DvServiceFactory`, `MathExpression`, `OpenSearchDashboardsResponse`, `HistoriesService`, `NewsItem`, `OutputItem`, `IosBinding`, `ArrayPattern`, `ExportedConfig`, `SvelteIdentifier`, `CandidateResponderRule`, `SPHttpClientResponse`, `ImgType`, `Title`, `ConnectionListener`, `SeriesList`, `HookEnvironment`, `GameChannel`, `TriggerConfig`, `KoaMiddleware`, `core.ETHGetAccountPath`, `GrowableXYZArrayCache`, `Notify`, `AccountSetBase`, `IDataSourcePlugin`, `SortStateAPI`, `PlainObjectOf`, `GeneratorExecutor`, `AbstractField`, `UsePaginatedQuery`, `aws.autoscaling.Policy`, `VertexAttributeInput`, `ListDbSystemsRequest`, `SyncableElement`, `Chalk`, `AttributeListType`, `NonemptyReadonlyArray`, `KernelMessage.IIOPubMessage`, `ShellExecution`, `JSXOpeningElement`, `AbiStateObject`, `sdk.IntentRecognizer`, `IMiddlewareHandler`, `ISpriteAtlas`, `MongoIdDto`, `R2`, `CreatedObject`, `App.windows.window.IClassicMenu`, `IAudioSource`, `UpdateChannelError`, `HyperlinkMatch`, `IntegerList`, `BasketSettings`, `AnimationDefinition`, `ClearableMessageBuffer`, `NodeExtensionSpec`, `JsExport`, `ArrayPropertyValueRenderer`, `GaugeDialogType`, `UnderlyingSource`, `MergeResults`, `ASTCodeCompatibilityReport`, `InvalidSubnet`, `ConchVector3`, `PotentialEdge`, `ExternalCliOptions`, `KeywordTypeNode`, `ListIPSetsCommandInput`, `LineBasicMaterial`, `XAxisTheme`, `PluginConfigDescriptor`, `Dialect`, `IfExistsContext`, `PiConcept`, `PreferenceService`, `Difference`, `SO`, `props`, `TSSeq`, `IFunctionWizardContext`, `UserDevices`, `IDashboardConfig`, `JsonRpcResponsePayload`, `ResolveOutputOptions`, `CodeMirror.Doc`, `ExtendOptions`, `ComputedParameter`, `UseSavedQueriesProps`, `OffsetOptions`, `SelectSpace`, `Height`, `CoapPacket`, `DirectoryInfo`, `IExternalFormValues`, `IdentityContext`, `mitt.Handler`, `EXECUTING_RESULT`, `moneyMarket.market.BorrowerInfoResponse`, `AdagradOptimizer`, `IFilterItem`, `CommentAttrs`, `IChangesState`, `DashboardUrlGeneratorState`, `IUiState`, `NavigationService`, `IPropertyWithHooks`, `LinkOpts`, `ExtendedFeatureImportance`, `ReactExpressionRendererProps`, `CmsModelField`, `ExploreResult`, `TemplateFileInfo`, `Communicator`, `IStreamApiModel`, `MidwayFrameworkType`, `IDeployedContract`, `DfDvNode`, `BoostStyleProps`, `PaginationConfig`, `i18next.TFunction`, `PragmaNameContext`, `StopwatchResult`, `NodeImpl`, `FormatToken`, `ArkApiProvider`, `ParsingResult`, `CacheEntry`, `IWithHistory`, `monaco.languages.CompletionItem`, `INodeFilter`, `PageDescriptor`, `LookupByPath`, `SignInResult`, `RegionMetadataSchema`, `Refs`, `ModdleElement`, `ImportFromNode`, `QueryProviderAttributesRequest`, `SessionService`, `LIGHT_INFLUENCE`, `SnapshotDetails`, `Canceler`, `ChildNode`, `ArchiveHeader`, `ShadowsocksManagerServiceBuilder`, `MomentInput`, `IAPIService`, `WebsocketState`, `INotificationsService`, `SourceFileEntry`, `KeySuffixOptions`, `PropertySignature`, `vscode.Uri`, `ResponseCV`, `PlaywrightClientLike`, `ScaleByBreakpoints`, `BundleOrMessage`, `DotLayerArgs`, `ConnectorProperty`, `MetricData`, `TReducer`, `KanbanList`, `HttpHealthIndicator`, `ClientType`, `PropertyKnob`, `ts.ParsedCommandLine`, `CustomHelpers`, `ConnectionFetcher`, `NohmModel`, `RequestProgress`, `XEvent`, `CaBundle`, `ClientMessage`, `VaccinationEntry`, `DefaultAttributeDefinition`, `DamageEvent`, `TAccum`, `GitHubPRDSL`, `MyClassWithReturnArrow`, `LoginReq`, `StreamAction`, `SegmentedControlProps`, `XcodeCloud`, `EntryNested`, `SelectedScript`, `fixResult`, `KibanaSocket`, `IAugmentedJQuery`, `ClassLexicalEnvironment`, `StyleDeclaration`, `TileMap`, `ServiceTypeSummary`, `CompiledBot`, `DeletePolicyRequest`, `CoapRequestParams`, `RenderPassToDefinitionMap`, `JSParserOptions`, `ListTagsForStreamCommandInput`, `DehydratedState`, `ESTermSourceDescriptor`, `KWin.Client`, `IInputType`, `ConfigUpsertInput`, `IMessageResponse`, `SyncConfig`, `GearService`, `MIREphemeralListType`, `CppArgument`, `NameSpace.WithEnum`, `AsApiContract`, `XAnnotation`, `UnionRegion`, `GeometriesCounts`, `IJoin`, `DirectiveLocation`, `PaymentChannel`, `RoomSettings`, `GraphQLField`, `ITagNode`, `TheiaBrowserWindowOptions`, `ConfigDict`, `AudioProfile`, `CampaignTimelinesModel`, `graphql.GraphQLFieldConfigMap`, `Destroyable`, `TRPCErrorResponse`, `RootElement`, `Notice`, `anchor.web3.PublicKey`, `SessionData`, `PluginDeleteAction`, `CheckOptions`, `IStackStyles`, `ScriptCmd`, `Vehicle`, `ChangeCipherSpec`, `ITasks`, `InteractionReplyOptions`, `RecordStringAny`, `ActionCreatorWithoutPayload`, `DropdownComponent`, `DragInfo`, `CodeLocation`, `NewRegistrationDTO`, `DockerConfig`, `FileHandle`, `UpdateJobResponse`, `ImageIdentifier`, `NoteworthyApp`, `IndexedClassMapping`, `PartialVersionResolver`, `ArrayService`, `NSObject`, `InstallWithProgressResponse`, `MemberAccessInfo`, `V1ContainerStatus`, `ChatMessageReadReceipt`, `HassEntity`, `AssetPublishing`, `CodeItem`, `BaseFormValidation`, `BaseMarker`, `interfaces.MetadataReader`, `NSDatabase.ITable`, `requests.ListPrivateIpsRequest`, `ScaleHandle`, `NVM500NodeInfo`, `Products`, `Details`, `FieldRule`, `TString`, `SubProg`, `DecompiledTreeProvider`, `EntityAdapter`, `ScenarioCheckInput`, `RelationQueryBuilder`, `IconPack`, `ArweaveAddress`, `Popover`, `GitBlameLine`, `IconOptions`, `Http3Request`, `IVertex`, `MaskObject`, `web3.PublicKey`, `PathLike`, `BroadcastOperator`, `Glissando`, `OrderBalance`, `IInterceptors`, `LinkedPoint`, `SfdxError`, `TArg`, `CoreEventHandlers`, `Local`, `ISplitIndex`, `dia.Graph`, `StorageBackend`, `D3Link`, `ParametersHelper`, `OneInchExchangeMock`, `FlatCollection`, `WebcamIterator`, `NotificationState`, `NodeLocation`, `IMigrator`, `MetaDataOptions`, `StateMachine`, `Cpu`, `DataTypeFields`, `KeyOctave`, `p5`, `ActionLogger`, `LunarMonth`, `YogaNode`, `DeployState`, `NetInfoState`, `SVGTSpanElement`, `MVideoId`, `SliderInstance`, `CssClasses`, `GitHubInfo`, `MediaProvider`, `ProductOptionService`, `MockedObjectDeep`, `MessageComponentInteraction`, `RawRustLog`, `Slider`, `PickKeyContext`, `TechnologySectionProps`, `ListEntitiesCommandInput`, `vscode.NotebookData`, `UpdateArticleDto`, `ContainerArgs`, `BaseGraph`, `OffchainDataWrapper`, `IStatusResult`, `OutputTargetDistCustomElements`, `BlockNodeRecord`, `DisplayDataAmount`, `DateInterval`, `TranslateHttpLoader`, `XmlListsCommandInput`, `protos.common.IApplicationPolicy`, `RevalidatorOptions`, `ComponentSet`, `TextMap`, `MemoryDb`, `WholeJSONType`, `Awaitable`, `MapLocation`, `IAuthCredential`, `DeleteTagsCommandOutput`, `k8s.Provider`, `DiscoverTypings`, `FeedbackData`, `ReadOnlyFunctionResponse`, `ContextSet`, `Studio`, `ASRequest`, `CustomOracleNAVIssuanceSettings`, `GasTarget`, `SubmissionController`, `SwaggerSpec`, `CustomRequestOptions`, `iDraw`, `GaxCall`, `WorkspaceManager`, `NotificationError`, `IGraphData`, `ContractEntryDefinition`, `CallEffect`, `AppAuthentication`, `Auth`, `LabelModel`, `Walker.Store`, `Web3Provider`, `InMemoryStorage`, `PropertyData`, `ModelRef`, `Chai.Should`, `apid.VideoFile`, `ComponentChildren`, `EmployeeInfo`, `Organizations`, `CommandNode`, `AssignmentKind`, `Waypoint`, `CustomerModel`, `NamedField`, `IProp`, `PatternCache`, `Values`, `FormValidationResult`, `SimpleProgramState`, `BehaviorName`, `UndoPuginStore`, `d.WorkerMainController`, `KeypairBytes`, `InspectorViewProps`, `ZodIssue`, `SignatureReflection`, `HTMLBRElement`, `GLRenderPassContext`, `TeamsActions`, `IMoveFocusedSettings`, `DocViewsRegistry`, `Cube`, `Goal`, `White`, `HandPoseConfig`, `NotFoundException`, `IQueryParams`, `TableConfiguration`, `MethodOrPropertyDecoratorWithParams`, `Dsn`, `ArchTypes`, `ValidateOptions`, `SpringResult`, `AuditorFactory`, `CollectionBundleManifest`, `ICrudListQueryParams`, `WatchedFile`, `FluidObjectMap`, `StructType`, `ChangedDataRow`, `OidcClientService`, `DynamicEntries`, `PutBucketPolicyCommandInput`, `vsc.CancellationToken`, `JoyCon`, `TimeoutErrorMode`, `UserPrivilegeService`, `AdbBufferedStream`, `DataHandle`, `TestWorker`, `WebOutput`, `PageActions`, `ObservableArray`, `DataTable.ColumnCollection`, `Descendant`, `Node.DepositParams`, `BindingOptions`, `TransformedStringTypeKind`, `ScanMessage`, `NestedCSSProperties`, `EvaluateFn`, `HttpResponseBadRequest`, `CompositeParserException`, `SceneEmitterHolder`, `TD.ThingProperty`, `ApiPipelineVersion`, `IndividualTreeViewState`, `MarketHistory`, `InteractiveStateChange`, `FunctionTypeParam`, `IMaterialUniformOptions`, `IndicatorCCReport`, `TmGrammar`, `NzTreeNodeOptions`, `OAuthService`, `DateFormattingContext`, `DomManipulation`, `AppCompatActivity`, `DeleteMembersCommandInput`, `IParty`, `WrappingMode`, `GraphicsLayer`, `BoundBox`, `GLTFPrimitive`, `Entity.List`, `GameInfo`, `IMyTimeAwayItem`, `ShowProps`, `TriggerAction`, `FixHandlerResultByPlugin`, `SyntaxInterpreter`, `RemoveOutputRequest`, `CGOptions`, `VariableGroupDataVariable`, `V2`, `NotebookNamespace`, `effectOptionsI`, `EditPoint`, `SignalValues`, `ZWaveLogContainer`, `TooltipPortalSettings`, `ClientConfig`, `InlineFragmentNode`, `APIResponse`, `FullChat`, `PutAssetPropertyValueEntry`, `DataDocument`, `HslaColor`, `ThyTransferSelectEvent`, `PipelineStage`, `IEdge`, `GlobalScript`, `MousecaseResult`, `ContextType`, `TNerve`, `TransportParameterId`, `DeleteDocumentCommandInput`, `v`, `EnumIO`, `TypeEnv`, `ContainerBindingEvent`, `RouteHealthCheckResult`, `m.Comp`, `SignatureTypes`, `SignatureAlgorithm`, `T2`, `Node2D`, `CustomConfig`, `PrimaryContext`, `SourceFile`, `ExportingOptions`, `SpectrogramData`, `LegendValue`, `AwaitEventEmitter`, `TimeSlot`, `PoolConfig`, `HapiResponseObject`, `HomeProps`, `AsyncOpts`, `ResolvedStyle`, `DataDrivenQuery`, `SpyLocation`, `CompilerSystemRemoveDirectoryOptions`, `ObservableLike`, `UserNotification`, `cc.Event.EventMouse`, `EmployeeService`, `ViewItem`, `JVertex`, `FieldType`, `Address6`, `NonCancelableCustomEvent`, `FlowTypeTruthValue`, `StartMigrationCommandInput`, `Minion`, `RuledSweep`, `ListPackagesForDomainCommandInput`, `RedisCommandArgument`, `OperatorDescriptorMap`, `IVersion`, `AlertStatus`, `TypeGuard`, `OptimisticLockError`, `io.ModelArtifacts`, `HTMLImageElement`, `DeleteBranchCommandInput`, `TaroEvent`, `FieldFormatConfig`, `UpdateAccountCommandInput`, `ValidatorError`, `requests.ListManagedInstancesRequest`, `CreateApplicationCommandInput`, `ListingDefinitionType`, `LibraryComponent`, `AuthenticationFlowRepresentation`, `RowRendererProps`, `SerializedEvent`, `ast.PersistNode`, `OrganizationProject`, `DeferredImpl`, `StringNode`, `ModelItem`, `SchemaHelper`, `ModelCheckResult`, `AerialMappers`, `MultiFn2`, `IGroupData`, `EventFnError`, `SchemaGenerator`, `Executable`, `vscode.Extension`, `ObjectConstructor`, `FieldTypeSelectOption`, `ClassMethodDefinition`, `ScalarNode`, `WmsLayer`, `UnidirectionalTransferAppState`, `Success`, `DecodedLogEntryEvent`, `CheckItem`, `B14`, `TeamSpaceMembershipProps`, `PartyLeave`, `ContextPosition`, `QuotaSetting`, `Series.PlotBoxObject`, `ChangeAnnotationIdentifier`, `StartupInfo`, `CachedToken`, `PreviewPicture`, `StructCtor`, `IRunResult`, `CdsTreeItem`, `DescribeFileSystemsCommandInput`, `SymbolId`, `TokenDetailsService`, `Sein.IResourceState`, `CreateUserResponse`, `domain.Domain`, `CreateVpcPeeringConnectionCommandInput`, `BaseElement`, `ForgotPasswordVerifyAccountsValidationResult`, `PluginDiscoveryError`, `BlobBeginCopyFromURLResponse`, `BackgroundRepeatType`, `DiscordInteraction`, `BroadcastMode`, `SyntaxCursor`, `IIFeedsState`, `CSharpType`, `Op2`, `SessionClient`, `ProcessStorageService`, `VertoMethod`, `SimpleStateScope`, `PushOptions`, `CSSValues`, `ModelConstructor`, `MockedElement`, `RenderNodeAction`, `ElementArray`, `TooltipStateReturn`, `ITranslator`, `UNKNOWN_TYPE`, `HTTPHeader`, `CallHierarchyOutgoingCall`, `InstanceManager`, `ServiceWorkerVersion`, `FileUploadService.Context`, `GetCollapsedRowsFn`, `Float32List`, `ITodoItem`, `QRCodeScheme`, `AutoRenderOptionsPrivate`, `MachineEvent`, `IInstallManagerOptions`, `ViewPortHandler`, `MutationHandler`, `ecs.ContainerDefinitionOptions`, `WorkerMessageType`, `Clue`, `TypeAliasDeclaration`, `SGGroupItem`, `ICriteriaNode`, `TestFactory`, `PagerAdapter`, `AddressBookContact`, `AxisLabelFormatterContextObject`, `ServiceProxy`, `JSONRPCRequest`, `CliCommandProvider`, `EmbedToken`, `LedgerReadReplyResponse`, `DescriptorIndexNode`, `ConfigDeprecationProvider`, `KeyValueDiffers`, `ObjectData`, `AssertClause`, `FormatStringNode`, `ClientMatch`, `Workflow`, `AccountFacebookInstantGame`, `DiffInfo`, `BSPEntity`, `BitmapText`, `ISource`, `ProfilerConfig`, `DocumentProcessorServiceClient`, `RootLabel`, `OdmsPhaseActions`, `DynamicFormControlLayout`, `AnimationStateMetadata`, `AstNodeDescription`, `JoinClause`, `formatting.FormatContext`, `ChartAnimator`, `WalletKey`, `WordcloudUtils.PolygonObject`, `UIBeanStorage`, `Flavor`, `Twitter.Status`, `IPaneContent`, `DurableOrchestrationStatus`, `SavedObjectTypeRegistry`, `Fixed`, `AtomicAssetsHandler`, `LayerWeightsDict`, `JSONRPCProvider`, `blockchain_txn`, `TwoWayRecordObservable`, `WorkspacePath`, `RequestTask`, `AfterCaseCallback`, `DefaultGeneratorOptions`, `LOGGER_LEVEL`, `Asteroid`, `ErrorEvent`, `MongooseQueryParser`, `TableSuggestionColumn`, `BodyState`, `GameScene`, `FormatFactory`, `IContentFilter`, `DatabaseState`, `STColumnFilterMenu`, `QuantifierResult`, `IUserItemOptions`, `TransactionWithBlock`, `StateUpdatedEvent`, `StatusParams`, `TIO`, `ConsoleWidget`, `TwitchChat`, `MethodParam`, `OrganizationVendorService`, `CalculateInput`, `IOSInput`, `ExecutorMessages`, `CausalRepoBranch`, `SelectedPaths`, `ARPosition`, `CanvasSpaceValues`, `RestoreFn`, `sdk.ConversationTranscriber`, `GraphQLAbstractType`, `CellInterval`, `VcsAuthenticationInfo`, `SubmissionObjectState`, `ByteStream`, `MoveLandedType`, `CirclineArc`, `MessageRemoteImage`, `Queries`, `DaLayoutConfig`, `HttpStatus`, `Checkbox`, `IEmployeePresetInput`, `MarkdownParsedData`, `S2ExtensionType`, `Pred`, `ListViewProps`, `MultiDictionary`, `CreateStateContainerOptions`, `DateParts`, `LogObj`, `VisualizationOptionStore`, `PkSerializer`, `monaco.languages.ProviderResult`, `BaseCallbackConstructor`, `HDOMNode`, `SflTester`, `NewLineType`, `TreeModelChanges`, `EntitySchemaDatatype`, `JurisdictionDomainModel`, `IController`, `SavedObjectsExportTransformContext`, `RoughRenderer`, `CategoryState`, `ParameterDecorator`, `TemplateDiff`, `Html5QrcodeScannerState`, `Postfixes`, `MsgBlock`, `GX.CompareType`, `Interpreter`, `IArticleData`, 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`SelectableItem`, `MerchantGoodsService`, `GetModelTemplateCommandInput`, `DataflowAnalyzer`, `GetAllAccountsValidationResult`, `VdmParameter`, `ExtraGate`, `FaIconLibrary`, `ResourceConstant`, `ListOfPoints`, `ParamsFilter`, `QueryableFieldDescription`, `AlfrescoApiService`, `childProcess.ChildProcess`, `GetConnectionResponse`, `RowTransformCallback`, `SettingsNotify`, `OptsChartData`, `ExponentSpec`, `CinemaFrameType`, `DeleteMeetingCommandInput`, `ConnectionProfile`, `IZoweNodeType`, `FieldGroup`, `Vfs`, `OverrideContext`, `LineHeight`, `ITimeSlot`, `MotionInstanceBindings`, `BaseUIElement`, `BITBOX`, `PartialTransaction`, `Highcharts.AnnotationControllable`, `TextChange`, `C5`, `Requireable`, `ParseCxt`, `UserWhereInput`, `TermEnv`, `IntlType`, `ChangeAnnotation`, `ProviderOptions`, `SGArcItem`, `Verdaccio`, `ClientFactory`, `BaseEnvironment`, `AutoAcceptProof`, `ModalState`, `flags.Discriminated`, `LoaderConfOptions`, `IVue`, `EffectComposerComponent`, `coreClient.CompositeMapper`, `ProcessStatus`, `LibrarySearchQuery`, `InjectionService`, `CancellationToken`, `UIElement`, `NextResponse`, `ts.EntityName`, `HostRecord`, `DelayedRemovable`, `TextEditorEdit`, `TForwardOptions`, `PostTexMtx`, `ImportEqualsDeclaration`, `Versions`, `Brew`, `Algebra.PlanNode`, `GrafanaTheme`, `EndpointAuthorization`, `Support`, `ComponentCompilerMeta`, `CBService`, `TCacheResult`, `SVFunc`, `ICreateFormDialogState`, `ICollaborator`, `OpenSearchClientConfig`, `PhysicalModel`, `MDCTabIndicatorAdapter`, `HTTPAuthorizationHeader`, `azureBlobStorage.Container`, `ErrorBoundaryProps`, `HsdsId`, `TokenInterface`, `Json.Segment`, `ReadOnlyIterator`, `JSONAPIDocument`, `CrossTable`, `DirectivePosition`, `IpcCommandType`, `JsonPointer`, `Zoo`, `Point.PointLabelObject`, `ValueContainerProps`, `BTIData`, `IClient`, `SecretsService`, `AuthMode`, `GitFile`, `Neo4jService`, `IAzureQuickPickItem`, `RequestOption`, `ValueType`, `LineIndex`, `ecs.TaskDefinition`, 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`CreateFlowCommandInput`, `TripleIds`, `BaseIndexPatternColumn`, `HdRipplePayments`, `ReadModelEnvelope`, `BasicResumeNode`, `IUIDefine`, `ColorResult`, `SourceDescriptionChunk`, `EmployeeAppointmentService`, `model.InstanceOf`, `GX.TexMapID`, `requests.ListInstancePoolsRequest`, `GmailMsg`, `NSSet`, `FlowItemAssign`, `TwingLoaderInterface`, `DynamicCommandLineParser`, `QuizLetter`, `TextBufferObject`, `WarehouseService`, `unicode.UnicodeRangeTable`, `Terms`, `RecordedTag`, `Coordinates`, `BinderFindBindedPositionRet`, `ts.VariableDeclaration`, `UnitMusteringRule`, `BaseN`, `Modifier`, `CreateMasternode`, `BoxListEntity`, `ICustomViewStyle`, `IGroupTemplate`, `SavedObjectMigrationMap`, `RuleWithCnt`, `AccountServiceProxy`, `FieldApi`, `DebugCallback`, `ImageTransformation`, `SurveyPDF`, `UAVariable`, `ITccSettings`, `InternalData`, `RnM2Primitive`, `LineCaps`, `TimeConfig`, `ServerMethods`, `JSONRoot`, `TransferTransition`, `TimePicker`, `TestFileSystem`, `SaleorClient`, `StyleSet`, `ContentType1524199022084`, `MachineInfo`, `AsyncUnorderedQueryFlow`, `Matchers`, `TabApi`, `UpdateRoomMetadataRequest`, `ISharingResponse`, `AnyToken`, `IMyDateRange`, `InstructionType`, `StockSandbox`, `BaseAttribute`, `EventLog`, `PaginationPayload`, `ResolveTree`, `ProcessInstanceTableEntry`, `FileResponse`, `OpenTarget`, `Tweet`, `PlayerInput`, `StatusController`, `EthersProvider`, `providers.BlockTag`, `IModalService`, `CustomStore`, `AlertInputOptions`, `Drag`, `ScanDetails`, `DeleteScalingPolicyCommandInput`, `HashData`, `LogLevels`, `DeleteDBClusterEndpointCommandInput`, `IAnswers`, `MALEntry`, `DiffLayouterFactory`, `SuggestionItem`, `Highcharts.NetworkgraphPoint`, `OptionalVersionedTextDocumentIdentifier`, `Aggregate`, `CiaoService`, `MDCChipAction`, `Search`, `MainAccessRequest`, `NetworkTargetGroup`, `Dep`, `InputBlock`, `UnsubscribeMethod`, `Window`, `CalendarInput`, `CommandRelay`, `TGraphQLContext`, `TableSchemaSpec`, `TypeScriptDeclarationBlock`, `IntTerm`, `QueryBuilderProps`, `AccountGoogle_VarsEntry`, `ng.IQService`, `IOnValidateFormResult`, `MetricsResults`, `CallParams`, `CurveColumnSeries`, `PlaybackRate`, `CSSTemplate`, `AwaitExpression`, `PageRequest`, `DefaultReconnectionHandler`, `DefaultChildrenWNodeFactory`, `ISchemaCollector`, `CssNodeType`, `ProgressList`, `ViewContext`, `Investor`, `WinState`, `TooManyTagsException`, `ConvertedDocumentUrl`, `BrowseCloudDocumentWithJobs`, `BlockOutputFormat`, `RecordObject`, `TimelineGridWrapper`, `GfxReadbackP_GL`, `HtmlContextTypeConvert`, `IAuthContextData`, `CompressedId64Set`, `AnyEvent`, `Aliases`, `ParametricRegExp`, `TrustIdHf`, `IServerSideGetRowsRequest`, `ScrollPosition`, `ApplicationDefinition`, `ShortUrl`, `CallingBaseSelectorProps`, `EncryptionLevel`, `DebugCurve`, `PayableOverrides`, `Triple`, `CreateSavedObjectsResult`, `ProposeMessage`, `Grouping`, `RibbonEmitterWrapper`, `ProblemViewPanel`, `ViewColumn`, `d.SerializeImportData`, `IBlobINode`, `EmittedMessage`, `Polyline`, `d.FunctionalComponent`, `GroupMetadata`, `DefaultRes`, `FleetMetricSummaryDefinition`, `ChangeAccumulator`, `DigitalObjectSet`, `ProductMap`, `MinimalNodeEntity`, `SMTDestructorGenCode`, `ttm.MockTestRunner`, `ChangesetGenerationHarness`, `Addon`, `LayoutPartialState`, `VisHelpTextProps`, `CasesClientInternal`, `AuxChannel`, `THREE.Line3`, `Package.Target`, `ts.ClassElement`, `NormalizedPath`, `CancelablePromise`, `RequestValues`, `RegistrationPage`, `BaseInteractionManager`, `msRest.OperationSpec`, `GeomEdge`, `AuthenticationProgramStateBCH`, `LogMeta`, `_1.EventTargetLike.HasEventTargetAddRemove.Options`, `grpc.Code`, `ValidationController`, `WeightsManifestEntry`, `NetworkInfoStore`, `LocalMigration`, `IBlock`, `RenderCallback`, `ListWorkspacesCommandInput`, `Main`, `InputContext`, `StringNote`, `ListArtifactsCommandInput`, `MockedOptions`, `Describe`, `SIGN_TYPE`, `NumOrElement`, `ExecutionConfig`, `MigrateFunction`, `Git.IStatusFile`, `ResponsivePartialState`, `FetchEvent`, `SDPCandidateType`, `jest.CustomMatcherResult`, `IValidator`, `CodeMaker`, `AppConfiguration`, `$mol_atom2`, `LoginDTO`, `WithGeneric`, `ISerializedRequest`, `AnyError`, `IFragment`, `DatasourceRefType`, `PageImportExportTask`, `Symbols`, `TodoAction`, `LegacyReputationToken`, `AnimalType`, `SolveType`, `JPAFieldBlock`, `CircleObject`, `Char`, `ActionStatusResolverService`, `ISignerProvider`, `AccountFixture`, `ModelDefinition`, `CandidateInterviewService`, `Vuetify`, `LambdaOutput`, `Knex.CreateTableBuilder`, `ScanDb`, `ActiveTaskExtended`, `AngularExternalStyles`, `LineConfig`, `Story`, `FooterComponent`, `OscType`, `ModulusPoly`, `NewSpecPageOptions`, `RepoData`, `ActionListItem`, `ReactiveObject`, `Coord`, `RTCPeerConnectionIceEvent`, `RequestApprovalTeam`, `PlatformAccessory`, `_BinaryWriter`, `RoomObject`, `StackItemType`, `CucumberQuery`, `DeleteConnectionRequest`, `ImportIrecDeviceDTO`, `SeriesTypeOptions`, `RoomPayload`, `GitHubApi`, `MatchExpression`, `SpectatorServiceFactory`, `PerQuadrant`, `ExpShape`, `SecurityCCCommandsSupportedReport`, `MapToType`, `IFolder`, `TBookAuthorMapping`, `TestFixtureComponent`, `CompositionItem`, `ExportJob`, `CanvasSide`, `Nodes.Node`, `SimpleCondition`, `MediaWiki`, `_1.Operator.fλ.Stateless`, `MutationObserver`, `JSXElement`, `MdcSelect`, `ManifestCacheChangedEvent`, `TikTokConstructor`, `FlattenSimpleInterpolation`, `Rule.RuleModule`, `BasicTarget`, `HeftSession`, `FlameGraphNode`, `RemoveArrayControlAction`, `QueryAllProvidersAttributesRequest`, `ImportService`, `Methods`, `uint16`, `DescribeEventSubscriptionsCommandInput`, `p5.Color`, `requests.ListManagedInstanceErrataRequest`, `EngineType`, `IlmPolicyMigrationStatus`, `MultiFileRenderResult`, `VertexBuffer3D`, `ActionEffectPayload`, `LavalinkNode`, `UseFormReset`, `LyricFont`, `IConfigOptions`, `PlaceholderComponent`, `YaksokRoot`, `CollisionPartsFilterFunc`, `NetworkPolicy`, `MessageInterface`, `IOHandler`, `PortSet`, `IConfigurationModify`, `NavigationEdgeStatus`, `ExperimentPhase`, `StateInvocationParams`, `ComponentModel`, `Common.ILog`, `DOMElement`, `Octokit`, `BaseChannel`, `CodePoint`, `ReturnTypeFuncValue`, `TransactionFormSharedState`, `CancelParameters`, `IClock`, `IDocumentWidget`, `RootObject`, `Selectable`, `GetActionParams`, `SelectionDirection`, `ClusterRoleBinding`, `IButtonProps`, `BarcodeScannerOperationParams`, `IBundleWithoutAssetsContent`, `RsRefForwardingComponent`, `DateSkeleton`, `SessionManager`, `CT`, `ProofItem`, `YoganOptions`, `ContentTypeReader`, `SendMessage`, `ModelBuilder`, `Disposer`, `TRawComponent`, `IScript`, `IndoorMap`, `UpdateResult`, `ApolloReactHoc.OperationOption`, `AnimationGroup`, `ConvectorControllerClient`, `MatchModel`, `A8k`, `Optional`, `ElasticsearchResponseHit`, `PostConditionMode`, `CellData`, `ParsedTranslation`, `WithSubGenericInverted`, `ScreenDetailDto`, `ScreenshotConnectorOptions`, `PackageJsonFile`, `OverlayStart`, `DiskOptions`, `MockLink`, `postcss.LazyResult`, `data`, `Testing`, `UserPresence`, `JsonStringifierContext`, `TokenizerConfig`, `HostSettings`, `ValidTimeoutID`, `Exceptions`, `FIRVisionImage`, `CrudRepositoryCtor`, `JsonConfig`, `GrowableFloat64Array`, `IStorageProvider`, `StrategyOrStrategies`, `EditorSchema`, `WorldService`, `MutateResult`, `ChipDirective`, `ts.TypeAliasDeclaration`, `WorkspaceStructure`, `CompactInt`, `PropIndex`, `StringAtom`, `Tsa.SourceFile`, `CliOptions`, `QueryConditionOptions`, `ResultMapper`, `PedAppearance`, `ScrollView`, `Swiper`, `IExtentStore`, `AError`, `AnimatorControllerLayer`, `IInterceptor`, `SearchInWorkspaceRootFolderNode`, `EncodedDeviceType`, `CfnPolicy`, `NormalizedExtension`, `requests.ListLimitDefinitionsRequest`, `AntiVirusSoftware`, `UpdateUserSettingsCommandInput`, `SystemVerilogExportInfo`, `UseLazyQueryState`, `JMapIdInfo`, `R1`, `IRawStyle`, `Pathfinder`, `ProjectConfig`, `TestcaseType`, `GetMyOrganizationCommand`, `AppService`, `vscode.TreeItemCollapsibleState`, `Toolkit.IPluginExports`, `KeyPhrase`, `SkipListNode`, `SnsMetricChange`, `Actions`, `AddToCaseActionProps`, `Prose2Mdast_NodeMap_Presets`, `IChatMessage`, `TextCanvas`, `IDirective`, `CharacterMetadata`, `IRoot`, `SubcodeLine`, `ExceptionBlock`, `NDArray`, `TaskExecutor`, `Visualization`, `UrlTemplate`, `StateStorageService`, `DestructuringAssignment`, `SkipListSet`, `TypeDBOptions`, `DocumentLinkParams`, `STPPaymentHandlerActionStatus`, `XmlAttributes`, `RolandV60HDConfiguration`, `Export.DefaultInterface`, `QueryParams`, `ActorId`, `FilterFor`, `ShowModalOptions`, `DescribeSourceServersCommandInput`, `TConvData`, `InterceptorFn`, `RelationsInputType`, `RectLike`, `KeyStore`, `vscode.ViewColumn`, `MethodHandler`, `UnpackNode`, `LogAnalyticsParser`, `TelegramBot.Chat`, `MenuCardProps`, `CityBuilderStore`, `vile.YMLConfig`, `DevToolsNode`, `ISnapshotTreeEx`, `OrdersService`, `React.LegacyRef`, `Run`, `VnetGateway`, `TokenStorage`, `CategorySegment`, `d.CompilerFileWatcherEvent`, `BaseToken`, `RetryConfigurationDetails`, `StatusResponse`, `CardContextOptions`, `MarkEncoding`, `AbortController`, `FileQuickPickItem`, `AngleFromTo`, `Stitches.PropertyValue`, `AllState`, `NormalizedMessage`, `SymbolInfo`, `Releaser`, `OutputLocation`, `MessageTimer`, `Marker`, `MouseState`, `aws.S3`, `ArcTransactionResult`, `StringLiteralLike`, `IRegistryInfo`, `TSESTree.Identifier`, `BitcoinCashAddressFormat`, `VanessaTabs`, `ODataServiceFactory`, `UseMutationResponse`, `MyEditor`, `RequestInput`, `GroupChannel`, `AttrRewriteMap`, `CounterAction`, `ContractWrapperFactory`, `PathFilter`, `Skeleton_t`, `PatternLiteralNode`, `ExpressionsServiceSetup`, `RepoFrontend`, `AutoTranslateServiceAPI`, `PartType`, `MockContractFactory`, `PostConditionPrincipal`, `GraphEdges`, `NotificationService`, `PedigreeConstraint`, `ICategoricalStatistics`, `RuntimeCacheInterface`, `GlobalAction`, `IProcess`, `DisassociateFromMasterAccountCommandInput`, `apid.RuleId`, `DocsBinding`, `AnalysisOptions`, `BasePeerType`, `InjectableDependency`, `VcsFileChange`, `IMaterialAttributeOptions`, `DocumentInfo`, `RAFirebaseOptions`, `FilterCriteria`, `Facet`, `PromoteGroupUsersRequest`, `ConvLSTM2DArgs`, `CausalObjectStore`, `Z64LibSupportedGames`, `TextDiff`, `CinemaHallSeat`, `DateTimeFormatOptions`, `RestSession`, `ConvWithBatchNorm`, `MerkleTreeNode`, `RouteInfoWithAttributes`, `ENDProgram`, `UpperMainBelow`, `NodeFileSystem`, `IToaster`, `ts.BinaryExpression`, `QueueServiceClient`, `FieldData`, `TelemetryOptions`, `FromToWithPayport`, `PluginLoaderService`, `ParameterDesc`, `ValidResponses`, `DecodedData`, `TypeReferenceNode`, `PropertySignatureStructure`, `IHostedZone`, `SupportedLocale`, `WorkflowStep`, `Application`, `Arpeggiate`, `KernelFunc`, `UserCredentials`, `ShaderInstance`, `VectorSourceRequestMeta`, `JitMethodInfo`, `MESSAGE_ACTIONS`, `ArtifactDownloadTicket`, `LoginFieldContainer`, `TabbedAggRow`, `BezierSeg`, `SymString`, `Fog`, `NucleusChannel`, `DiffSelection`, `DocController`, `DocumentFilter`, `EditorController`, `StatusBarItem`, `DimensionRecord`, `ThemeOptions`, `BindingOrAssignmentElement`, `WalletAccount`, `DeployHelpers`, `TimelineState`, `Module`, `Vp9RtpPayload`, `StyleType`, `UIInterfaceOrientation`, `CustomRenderElementProps`, `MutableMatrix22`, `NotificationProps`, `JQueryDeferred`, `CreateChannelMessage`, `NotebookDocument`, `Modifiers`, `NodeJS.Platform`, `MockStorage`, `Audio`, `TaskRunnerFactoryInitializerParamsType`, `IDirectory`, `ColorInformation`, `UserPreferencesService`, `cc.Vec3`, `PoisonPayload`, `PrimitiveShape`, `IParseInstruction`, `SubcodeWidget`, `ResolveType`, `TabId`, `QueryFlag`, `CSSState`, `MActorLight`, `IGarbageCollectionData`, `HapticOptions`, `RouterStore`, `ParamData`, `AnimatorClassSettings`, `requests.ListCustomProtectionRulesRequest`, `AccountFacebookInstantGame_VarsEntry`, `Dockerode`, `SlotId`, `IYamlApiFile`, `MatCheckboxChange`, `VisibilityType`, `SendCommandOptions`, `BaseDirective`, `ButtonToolConfig`, `React.BaseSyntheticEvent`, `MessageOrCCLogEntry`, `StyleStore`, `IStageManifest`, `XY`, `ThingMetaRecord`, `AllowedNetworks`, `BaseVerifiableClaim`, `ITimeToSampleToken`, `OutdatedDocumentsSearchRead`, `PackageManagerCommands`, `SingleConfig`, `UseAsyncReturn`, `BaselineOptions`, `CreateApp`, `CertificateAuthorityRule`, `SonarQubeConfig`, `TabStorageOptions`, `TypeAttributeMap`, `CustomResponse`, `IPanel`, `GestureStateEventData`, `PackedTrie`, `PolyPoint`, `Compressor`, `DaffQueuedApollo`, `VideoObject`, `TerminalNode`, `ListenForCb`, `Writable`, `WorkTree`, `ChatPlugService`, `LiveObject`, `CardManifest`, `i32`, `IGetMembersStatistics`, `FileHashCache`, `Sorter`, `MapControlsUI`, `MsgUpdateDeployment`, `HubInfo`, `CategoryRecordsDict`, `CreateComponent`, `FormatProvider`, `ResultProps`, `ActivityStatus`, `CreateFileSystemCommandInput`, `WebpackType`, `WishListRoll`, `CliProxyAgent`, `FastFormContainerComponent`, `TypeChange`, `MatSnackBar`, `IClassicListenerDescription`, `FcEdge`, `AnnotationData`, `AFSReference`, `LocationData`, `IndTexMtx`, `ConditionalArg`, `Domains`, `FloorCode`, `DictionarySchema`, `CacheSnapshot`, `BottomNavigationViewType`, `ApolloServerPlugin`, `DeleteIPSetCommandInput`, `PresenceSync`, `CoreCompiler`, `Tnumber`, `SalesOrderState`, `RESTResponseDataType`, `TransliterationFlashcardFields`, `Stem`, `AccountKey`, `SlotAst`, `TaggedProsemirrorNode`, `wdpromise.Promise`, `Manifest`, `GroupHoldr`, `Electron.MenuItem`, `ODataStructuredType`, `DeserializeOptions`, `CardId`, `Ingress`, `QuadrantRow`, `DynamicMatcher`, `GridSize`, `VariableRegistry`, `CertificateSummary`, `OptionValues`, `ClientDetails`, `DtlsPlaintext`, `DeserializeWireOptions`, `GetCellValueFn`, `RootData`, `AFSQuery`, `ScopeManager`, `WalletInit`, `IHttpProvider`, `GfxTextureP_GL`, `Mass`, `YjsEditor`, `JPA.JPABaseEmitter`, `SearchResultsArtist`, `Pointer`, `ComponentConstructor`, `ILogger`, `_IType`, `VDocumentFragment`, `PyJsonValue`, `WalletAdapter`, `ResultError`, `Mars.TransactionOverrides`, `CommonLanguageClient`, `TestSettings`, `SVGCircleElement`, `ClassGenerics`, `TabsModel`, `OperatingSystem`, `LoggedInUser`, `Charset`, `ContractAbiDefinition`, `CircleDatum`, `SpecFiles`, `PlantProps`, `WidgetObject`, `SignedTx`, `SqlFragment`, `MiBrushAttrs`, `d.ComponentCompilerPropertyType`, `CodeNameDTO`, `ResolvedGlobalId`, `InternalPlugin`, `ISnapshotProcessor`, `AlertInstanceState`, `WebApi.JsonPatchDocument`, `GbBackendHttpService`, `PermissionResponse`, `ArchDescr`, `GeneratorSourceConfig`, `SRoutingHandle`, `InvalidNextTokenException`, `CreateCertificateDetails`, `ICommandResponse`, `UserInfoData`, `TokenSmartContract`, `TProduct`, `protocol.FileLocationRequestArgs`, `AlignItems`, `JSBI`, `StreamParam`, `EffectRef`, `RtkRequest`, `SchemaOptions`, `PBRStandardMaterial`, `RenderObject`, `ConstructorAst`, `PutDedicatedIpInPoolCommandInput`, `PlayerSubscription`, `ExpressionValue`, `DeleteWebhookCommandInput`, `React.ChangeEvent`, `BindingKey`, `TriangleFilterFunc`, `CryptoContext`, `basic.Token`, `RemoteDataBuildService`, `MessageAttributes`, `PossibleSelections`, `WalletOrAddress`, `VisibilityNotifier2D`, `OverridedSlateBuilders`, `ScopedPlannerConfiguration`, `NotificationRequestInput`, `ContextMessageUpdate`, `CreateAppInstanceAdminCommandInput`, `ConvertedRemoteConfig`, `MetricsServiceSetup`, `MemoizedSelector`, `IOptionalIType`, `ReferenceUsedBy`, `BoundsData`, `SavingsService`, `TargetProperty`, `Feed`, `ConstraintService`, `ANIME_DICT`, `Readonly`, `FinalConfig`, `ErrorProps`, `SVGPathFn`, `OrganizationPoint`, `StyledComponent`, `RGBColor`, `JSDocsType`, `ListFileStatResult`, `UploadFileOptions`, `DisplacementRange`, `WalletModule`, `KeyframeInfo`, `StructureSpawn`, `CharStream`, `IVocabulary`, `AnnotationType`, `TRight`, `MFAPurpose`, `NoteSize`, `CollectionReference`, `DeclarationReflection`, `BigInteger`, `ISetCombination`, `IndicesService`, `QueryRunner`, `WorkflowState`, `CallHierarchyPrepareParams`, `ANodeStmList`, `RollupConfigurationBuilder`, `ExecaError`, `LanguageServer`, `CursorContent`, `MetricOptions`, `GUIDriverOptions`, `ConvertionResult`, `EditMode`, `XYChart`, `LocationId`, `DaffOrder`, `ViewState`, `WithKeyGeneric`, `vscode.TextEditorEdit`, `LayerProps`, `ApprovalRuleTemplate`, `GPUPipelineLayout`, `ExchangeParams`, `ConnectedOverlayPositionChange`, `IServiceLocator`, `OrgMember`, `WebsocketMessage`, `DaffAccountRegistration`, `DefaultReconnectDisplay`, `VideoDialog`, `RemoteObject`, `IReceiveParams`, `MXMirrorObjMethodCall`, `RouteResult`, `Amounts`, `PageMaker`, `LoadmoreFlatNode`, `HtmlParser`, `ts.Scanner`, `HashMap.Instance`, `Escape`, `H`, `SemanticType`, `Unionized`, `Numbers`, `ScaffoldType.Local`, `DatePickerValue`, `DocumentChange`, `ServerEventEmitter`, `d3Request.Request`, `JSX.IntrinsicAttributes`, `IntrospectFn`, `UnitBase`, `BTCSignedTx`, `Codebase`, `AppManifest`, `BasicKeyframedTrack`, `SignalMutation`, `Control3D`, `CreateTableNode`, `ConcatenateLayerArgs`, `GX_Material.GXMaterial`, `Redis`, `IBufferService`, `fromSettingsActions.UpdateSettingModel`, `BaseClusterConfig`, `NormalizedConfigurationCCAPISetOptions`, `IPluginAPI`, `Reddit`, `AudioInterface`, `ConsoleContext`, `RenderFunction`, `VcsInfo`, `GuildMember`, `InferredFormState`, `ConfigData`, `Estimate`, `Wildcard`, `HistoryViewContext`, `TaskChecker`, `VRDisplay`, `MDCMenuAdapter`, `Cutline`, `FormDataEntryValue`, `PackageRegistryEntry`, `SchemaProperty`, `Layers`, `Events.predraw`, `AdjacentList`, `TsTabCollectionComponent`, `PaginatedSearchOptions`, `LocalVueType`, `BuildPipelineVisFunction`, `PageHeaderProps`, `Pact`, `CircleEditOptions`, `AppenderConfigType`, `WKWebView`, `ThrottleOptions`, `That`, `Models`, `PreloadedState`, `io.SaveConfig`, `EntityStatus`, `FunctionFactory`, `DefaultApp`, `FindManyOptions`, `TurnClient`, `IModalContent`, `Events.initialize`, `MappingFn`, `FieldHierarchyRecord`, `JSXMemberExpression`, `IPropertyIdentValueDescriptor`, `MsgCloseLease`, `Permute`, `SymbolCategory`, `cwrapSignature`, `ImGui.U32`, `MockRequestParams`, `TSType`, `HashValue`, `nodes.Stylesheet`, `SparseMerkleTree`, `DeleteDatasetGroupCommandInput`, `SlotDefaultValue`, `TypedEventFilter`, `SocketOptions`, `MockPort`, `AsyncActionType`, `IEndExpectation`, `ObjectSet`, `WithGetterString`, `ts.Identifier`, `LogCallbackType`, `VersionMismatchFinderEntity`, `OutlineSymbolInformationNode`, `IDinoProperties`, `GridsterItemComponentInterface`, `IDatabaseDataActionClass`, `TagInformation`, `Opt`, `Poly`, `GraphRecord`, `GameModule`, `ImageryMapExtentPolygon`, `RuleId`, `DownwriteUIState`, `Components`, `ICheckAnalysisResult`, `PrincipalCV`, `WorkflowStateType`, `GridChildComponentProps`, `ConfigAccumulator`, `GraphQLRequest`, `EntityToFix`, `StorageMigrationToWebExtension`, `Responses.IViewContentItemResponse`, `primitive`, `TaroElement`, `ITsconfig`, `OpenDateRange`, `protocol.Location`, `Optimization`, `RtfDestination`, `Register64`, `GX.LogicOp`, `IntrospectionType`, `AuthorizationError`, `IOpenSearchSearchResponse`, `ResultNode`, `AttendanceStatusType`, `AccentColor`, `NumericNode`, `DynamoDB.DeleteItemInput`, `IFilters`, `SSAState`, `SessionStorage`, `S3.Types.PutObjectRequest`, `SettingOption`, `GroupSpec`, `OpenObject`, `Plan`, `TransportContext`, `CustomDialogOptions`, `WorkerContext`, `LocalState`, `EventSpy`, `ValueFormField`, `SymShape`, `BabelTarget`, `SectionsService`, `ExternalStyleCompiler`, `StringShape`, `TEvent`, `AntVSpec`, `requests.ListDbCredentialsRequest`, `RedAgateElement`, `NgSelectConfig`, `P2SVpnConnectionRequest`, `TemplateProps`, `ListTagsForResourceCommandInput`, `ControlBase`, `PluginMetrics`, `BindingWrapper`, `ITargetInfoProps`, `IORedis.Redis`, `ITaskLibrary`, `PuzzleState`, `CarService`, `PlanetPortalApplication`, `GitHubRepoData`, `vscode.WorkspaceConfiguration`, `VaultEntry`, `LiveEventSession`, `YieldNode`, `Defer`, `VisDefaultEditor`, `GUILocationProperties`, `ArrayFunc`, `Type_Interface`, `StepAdjustment`, `Nerve`, `AxisMilestone`, `FieldsSelection`, `ICompetitionDefault`, `ViewController`, `PaperProps`, `CstNode`, `SubsetConstraints`, `ApiTableData`, `TooltipContextValue`, `UseQueryResult`, `AggregateRowModel`, `StateT1`, `DFAState`, `NavigationItem`, `JsonDocs`, `CustomFilterArgs`, `Skin`, `PositionStrategy`, `IRenderData`, `CommentRequest`, `PluginExtended`, `StackLayout`, `ClientDTO`, `IAssetProvider`, `GraphQLServiceContext`, `py.Expr`, `DescribeRegistryCommandInput`, `StyledTextProps`, `IProjectsRepository`, `DescribeJobCommandInput`, `Pie`, `ISnapshot`, `Tuple`, `ApiV2Client`, `OriginGroup`, `RoomParticipantIdentity`, `ServiceDiscoveryPlugin`, `Webhooks`, `Tensor5D`, `BIP85`, `NgxUploadLogger`, `PartialResults`, `DAL.DEVICE_ID_SYSTEM_MICROPHONE`, `SVGLineElement`, `NgrxJsonApiStoreData`, `ConflictMap`, `AssetProps`, `IActivitiesGetByContactState`, `RegisterInput`, `Workunit`, `StaticArray`, `ActionObservations`, `InterventionTip`, `StaticSiteCustomDomainRequestPropertiesARMResource`, `StdlibRegistry`, `TinaFieldEnriched`, `ListRenderItem`, `AZSymbolInformation`, `IOriginConfiguration`, `SearchQuery`, `OpenSearchError`, `CreateTagsCommandInput`, `InternalMetric`, `MenuStateReturn`, `Dock`, `GunMsg`, `StateKey`, `PublishParams`, `RangeDelta`, `IamRoleName`, `ViewGroup`, `ResolverRelation`, `MarkdownNode`, `ViewModel`, `CreateDataAssetDetails`, `AwsShapes`, `FundedAward`, `ImageType`, `V1Pod`, `PackageDefinition`, `ModuleType`, `MonthViewProps`, `TreeItemCollapsibleState`, `CliCommandOptions`, `OperationHandlerPayload`, `BuildSourceGraph`, `SequentDescriptor`, `IUserDTO`, `DropdownMenuItemLinkProps`, `ScannedPolymerElement`, `GsTeam`, `ScreenMatrixPixel`, `Analyzer`, `HttpClientRequest`, `MediaFile`, `RowLayoutProps`, `requests.ListAutonomousDatabaseBackupsRequest`, `ComponentHost`, `ContentInfo`, `OnReferenceInvalidated`, `Errors`, `ChromeExtensionManifest`, `PubKeyType`, `GraphQLInputObjectType`, `ClassElement`, `T19`, `EventHint`, `MfaOption`, `ClusterCreateSettings`, `FieldsetContextProps`, `LayoutState`, `HistoryInteractionEvent`, `Themer`, `PresetType`, `requests.ListCachingRulesRequest`, `ManyApiResponse`, `Notebook`, `ConstructorOptions`, `$ResponseExtend`, `SelectFileModel`, `TsOptionComponent`, `ProcessService`, `DocService`, `IMovable`, `UserDoc`, `ClickHandler`, `Ball`, `Crosshair`, `CandleGranularity`, `LocalizedSteps`, `FlashbotsBundleProvider`, `OasOperation`, `RejectInvitationCommandInput`, `MethodHandle`, `AbiFunction`, `ProxyInfo`, `MaxAttrs`, `RuleDescriptor`, `OmitsNullSerializesEmptyStringCommandInput`, `PropOfRaw`, `MaterialOptions`, `K.BlockStatementKind`, `LinkResolverResponse`, `NodeJS.ErrnoException`, `QuicStream`, `CreateMembersCommandInput`, `FunctionAppEditMode`, `ClassDetails`, `AddressBookService`, `QueryParser.QueryNode`, `RSPSharedOutput`, `KintoClient`, `CanvasBreakpoints`, `MapMeshStandardMaterial`, `DatabaseContainer`, `TestRenderNode`, `ParamValues`, `ChainTokenList`, `Changes`, `Spell`, `AbiParameter`, `SavedKeymapData`, `FunctionSetting`, `FileExtension`, `BuildPackage`, `MutationSubState`, `ConditionExpressionDefinitionChain`, `firebase.app.App`, `CatalogLayoutState`, `IOidcIdentity`, `WalletConfig`, `Got`, `IFormContext`, `d.ComponentCompilerStaticMethod`, `AABBOverlapResult`, `Light`, `OptionProps`, `HandleError`, `PhotoDataStructure`, `UpdateAppInstanceCommandInput`, `CommitOrDiscard`, `IPaintEvent`, `GRULayerArgs`, `Hero`, `ZoweDatasetNode`, `SankeyGraph`, `EditWidgetDto`, `ServiceStatus`, `WithdrawAppState`, `Denque`, `Knex.ColumnBuilder`, `EditorAction`, `CloudPoint`, `IQueryInfo`, `AuthenticateGoogleRequest`, `HsLaymanService`, `TextTrackCue`, `V1StepModel`, `PaginatedRequestOptions`, `WatchOptions`, `AzureFirewall`, `DiscogsTrack`, `IndexerManagementClient`, `IOnSketchPreviews`, `RenameInfo`, `ApiToken`, `XMLAttribute`, `LoopBounds`, `RawDoc`, `MultiTrie`, `Relayer`, `LemonTableColumns`, `ColorStyle`, `ParsedAccount`, `ICollectItem`, `SyntaxError`, `InputParamMapper`, `ICfnFunctionContext`, `DropTarget`, `ForwardingParams`, `PluginStorageKind`, `CreateIndexBuilder`, `HubUtility`, `IFrontendDomChangeEvent`, `TestDirectEscrow`, `ICoreMouseEvent`, `ListAvailabilityDomainsResponse`, `StylesMap`, `SimControlLog`, `HdmiInput`, `Staking`, `HumanData`, `DocumentSymbolProvider`, `Events.preupdate`, `AggsCommonStartDependencies`, `LedgerTransport`, `t.SourceLocation`, `OpenDialogReturnValue`, `NodeAttributes`, `IComponentWithRoute`, `Attachment`, `GetDedicatedIpsCommandInput`, `StatementNode`, `SysUser`, `InputActionMeta`, `AdamaxOptimizer`, `GfxInputState`, `Path2`, `ILineGeometry`, `TT.Level`, `BasicSourceMapConsumer`, `TableNS.RowProps`, `requests.ListAutoScalingConfigurationsRequest`, `QuickPick`, `DietForm`, `F3DEX_Program`, `StoreGetter`, `IStepAdjustmentView`, `BaseShrinkwrapFile`, `IApplicationShell`, `TLang`, `UnionMemberMatchTransformer`, `PluginTransformResults`, `picgo`, `IdentityDictionary`, `numVector`, `Constant`, `Query`, `ServerStatus`, `pxt.Map`, `DropData`, `TallySettingsIni`, `Journey`, `CharacterCreationPage`, `GetDomainNamesCommandInput`, `SpatialCategory`, `GetAdministratorAccountCommandInput`, `FirestoreUserField`, `IBaseComponent`, `SQLParserVisitor`, `MIREntityTypeDecl`, `Structure`, `SaveFileArgs`, `ABN`, `StringLocation`, `ValidationParams`, `UsersService`, `LinkService`, `HTMLTableHeaderCellElement`, `Archiver`, `IStorageSchema`, `MouseService`, `Order2Bezier`, `Packages`, `ContentLinesArrayLike`, `EpicTestMocks`, `JSDefinitionNode`, `InsertQueryBuilder`, `RadSideDrawer`, `LatLon`, `TAccesorData`, `ReadonlyDeep`, `StoreItem`, `ServerRoute`, `AppxEngineActionContext`, `TransactionQueryPayload`, `ImageTexture`, `SubmissionObject`, `IAuthorizer`, `Widgets`, `BudgetGroup`, `MultilevelNode`, `DesignerVariable`, `requests.ListPublicationsRequest`, `KeyFrame`, `ControlDirective`, `Accessor`, `ZWaveController`, `MigrationService`, `Loading`, `RequestPolicyOptionsLike`, `SwapEncoder`, `Papa`, `NoteStateWithRoot`, `DIContainer`, `TestGroup`, `CardDatabase`, `EmittedObject`, `TMetricAggConfig`, `VideoConverter`, `PointerButton`, `IUserProfile`, `AsyncModuleConfig`, `IDebugProvider`, `ElTreeModelData`, `ActivityTimeSeriesMetrics`, `StartPoint`, `DetectedFeatures`, `GameTreeNode`, `AuthOptions`, `Budget`, `ISummaryHandle`, `Guide`, `BackendTimingInfo`, `PostResult`, `DaffCartItemInput`, `IMrepoConfigFile`, `CourseDuration`, `MavenTarget`, `IWhitelistUser`, `KeyboardEventToPrevent`, `RateLimitOptions`, `AreaPointItem`, `AccountResource`, `UntagResourceCommandInput`, `pulumi.ResourceOptions`, `ShoutySession`, `ListBackupsRequest`, `Big`, `d.HostElement`, `CdsInternalPopup`, `MccScrollspyGroup`, `EnrichedPostageBatch`, `BasicLayoutProps`, `UseQueryStringProps`, `GridGraph`, `TopNavigationEntry`, `Vnode`, `InsertContentDOM`, `CompletionOptions`, `DeleteGroupRequest`, `PushToServiceResponse`, `requests.ListIncidentResourceTypesRequest`, `PieceSet`, `ConverterFunction`, `ImageDefinition`, `CompositeContentBuilder`, `Migrate`, `ValidationSchema`, `RatingProps`, `NestedDict`, `LinksList`, `UserId`, `ComboBoxGroupedOptions`, `CommandRegistry`, `PrimaryKeyOptions`, `ElkNode`, `JSONTree`, `StreamResetResponseParam`, `UseMutationReducerAction`, `SchemaTypes`, `DrawingNode`, `SpeedDialItem`, `ELULayerArgs`, `QueryOrderMap`, `CoordinateConverter`, `MissingFilter`, `Reducer`, `RippleRef`, `CreateTaskCommandInput`, `IFunctionParameter`, `CurveVector`, `IDisposable`, `TileMatrixType`, `MyPromise`, `DeleteResourcePolicyCommandInput`, `TTarget`, `EdgePlaceholder`, `express.Response`, `DbTokenMetadataQueueEntry`, `Jsonp`, `MVideoThumbnail`, `JSDOM`, `ApplicationConfigService`, `Restangular`, `ListTagsForResourceResponse`, `FleetRequestHandler`, `ExtendedMesh`, `ChangeEvent`, `ReportParameter`, `UseCaseBinder`, `DeadLetterConfig`, `Vector3_`, `Cross`, `PolylinePoint`, `ActionExecutionContext`, `ProjectsService`, `ClarityAbiType`, `FieldDoc`, `PsbtTxOutput`, `OwnerItemT`, `RangeError`, `DataPromise`, `GhcModCmdOpts`, `ts.ReturnStatement`, `ProtoPos`, `CsvInputOptionsNode`, `ITokensState`, `Seed`, `InputStyleProps`, `ChartDataset`, `VerifiableClaim`, `TSetting`, `UpdateApplicationResponse`, `OneToManyOptions`, `FabricGatewayRegistryEntry`, `MessageOption`, `SessionProposal`, `HookConfig`, `SubmissionQueueItem`, `LS.CancellationToken`, `WebGLVertexArrayObject`, `ReAtom`, `SharePlugin`, `PendingUpdateDetails`, `ApplicationConfigState`, `d.OutputTargetDocsJson`, `Panel`, `Visitors`, `JieQi`, `MonzoAccountResponse`, `DirectoryEntry`, `SyntaxType`, `CreateEntrypoint`, `IndexFileInfo`, `ServicesState`, `FnReturnType`, `StynTree`, `AnalyicsReporterConfig`, `QWidget`, `MlCommonUI`, `PlaneByOriginAndVectors4d`, `ExpressLikeStore`, `Flicking`, `UserManagerInstance`, `GitHubIssueOrPullRequest`, `GethInstanceConfig`, `DashboardContainerOptions`, `StreamID`, `TimelineRecord`, `TextDocumentRegistrationOptions`, `GeoService`, `Book`, `WalletManager`, `CoreTracer`, `alt.RGBA`, `UIImage`, `AnyRouter`, `WatcherFactory`, `ProcessResult`, `PluginModule`, `common.ConfigFileAuthenticationDetailsProvider`, `UploadOptions`, `LocalizationProviderProps`, `address`, `HTMLTableCellElement`, `MenuProps`, `ITwin`, `GtConfigSetting`, `FormikActions`, `code.Uri`, `PluginManager`, `UserReport`, `OptimizationPass`, `MActorId`, `ITimelionFunction`, `requests.GetJobLogsRequest`, `AutoImportResultMap`, `CardContentProps`, `IFirmwareCodePlace`, `CreateGrantCommandInput`, `Lyric`, `DaffCategoryFilterEqual`, `IconButtonProps`, `apid.BroadcastingScheduleOption`, `TelemetryData`, `XYZStringValues`, `AcornNode`, `IFormItem`, `MediaRec`, `ReactClient`, `AnimationConfig`, `TestConfigOperator`, `CellType`, `ProtocolParams.Propose`, `ParsedJob`, `int32`, `SoFetch`, `MigrationStatus`, `NavController`, `SubscriptionCategoryNotFoundFault`, `WithAttributes`, `ClaimStrategy`, `Recorder`, `OctreeNode`, `SchemaUnion`, `MapsManagerService`, `WorkDoneProgressServerReporter`, `MimeType_`, `IUserRegistrationInput`, `MouseOrTouch`, `InstalledDetails`, `requests.ListTaskRunLogsRequest`, `CreateImageCommandInput`, `SqrlCompiledOutput`, `ts.ForStatement`, `UseMutationState`, `BitBucketServerAPI`, `AstWalker`, `UpdateNoteRequest`, `ImageBox`, `FlowLog`, `SubscriptionOptions`, `GetResourcePoliciesCommandInput`, `ThyAutocompleteContainerComponent`, `ActionImportRequestBuilder`, `SankeySeries.ColumnArray`, `BoolQuery`, `LoggerTimeSpan`, `CreateArgs`, `MdlPopoverComponent`, `TokenDetailsWithBalance`, `Function2`, `USSEntry`, `AWS.DynamoDB`, `ConfigLoader`, `Weight`, `MatchmakerRemove`, `TestSetup`, `UpdateFilterCommandInput`, `JoinNode`, `TeamsState`, `PolicySummary`, `ResourceKey`, `TaroNode`, `MDCMenuFoundation`, `BatchValidator`, `serialization.SerializableConstructor`, `MutationRecord`, `When`, `OpenBladeInfo`, `PromiseRequest`, `MetricDataPoint`, `SpaceType`, `PaletteRegistry`, `IAccountProperties`, `IntCV`, `LibraryNotificationAction`, `UI5XMLViewCompletion`, `OpenApiDocumentRefs`, `PageAPIs`, `Guard`, `ObjectStore`, `ResolveCallback`, `PropertyCategoryRendererManager`, `core.IThrottler`, `UITextView`, `IEmail`, `IFilterItemProps`, `BoxCollisionShape`, `ts.ImportDeclaration`, `HDNode`, `ImageVideo`, `PathEdge`, `UpdateOrganizationConfigurationCommandInput`, `ListCardContent`, `NZBAddOptions`, `LeafNode`, `ClarityType`, `PutResourcePolicyCommandInput`, `GroupedFields`, `Conditional`, `IStorageScheme.IStorage`, `ProjectGraph`, `AppEventsState`, `IGeometryAccessor`, `IMdcChipElement`, `AssociationGroupInfoCCInfoGet`, `ISets`, `GraphQLFormattedError`, `DocSourceFile`, `IZipEntry`, `ESLScreenBreakpoint`, `GraphicUpdateResult`, `FirebaseUser`, `ICharacteristic`, `DocumentError`, `HTMLFormElement`, `Block`, `AstEditorProps`, `MeterCCReset`, `ComponentStory`, `GroupItem`, `TaggingInfo`, `CoreSetup`, `UAProxyManager`, `server.Diagnostic`, `LiveEventMessagingService`, `KeyboardEventHandler`, `ParquetData`, `THREE.Object3D`, `TableColumnWidthInfo`, `IMusicDifficultyInfo`, `Applicative2C`, `IImageConstructor`, `CaptionSelector`, `AxisTick`, `Event`, `ClusterMetadata`, `CardBrand`, `FileTrackerItem`, `IGraphDef`, `GraphNode`, `ISessionContext`, `findUp.Options`, `ComponentResult`, `Discord.GuildMember`, `SnackbarState`, `DeclarationMapper`, `ChangesetFileProps`, `ComponentTag`, `PersonFacade`, `ListObjectsRequest`, `Tsoa.Method`, `TTypescript.ParsedCommandLine`, `PutPermissionPolicyCommandInput`, `FieldConfiguration`, `WolfState`, `TestResponse`, `PlayerPageSimulation3D`, `UAMethod`, `JsonSchemaDataType`, `Mock`, `ScmDomain`, `SignatureProviderRequestEnvelope`, `DrawContext`, `DecodeData`, `Electron.OpenDialogReturnValue`, `AssetChangedEvent`, `PostFilter`, `WebResourceLike`, `Electron.IpcMainEvent`, `tensorflow.ISignatureDef`, `VNodeTypes`, `FilterMetadata`, `React.MouseEventHandler`, `AmountOptions`, `MessengerTypes.Attachment`, `ContentData`, `NumericLiteral`, `PubSubEngine`, `Membership`, `UpdateCheckResult`, `CategoryData`, `TokenResponse`, `TableOperationColumn`, `social.ClientState`, `ReadableSpan`, `LibraryContextSeries`, `SupportedFormat`, `GlobalConfig`, `TagWithRelations`, `d.CssImportData`, `UseReceiveSet`, `DividerProps`, `TaskWithMeta`, `ColumnDefs`, `GameObj`, `FormatterFn`, `BlockMapType`, `EntityCollections`, `DaffAuthTokenFactory`, `MDCSliderAdapter`, `lsp.Location`, `PackagesConfig`, `TestFunctionImportEntityReturnTypeCollectionParameters`, `FirebaseSubmission`, `ValidationResult`, `ServerProvider`, `DescribeReservationCommandInput`, `SingleWritableState`, `TabStrip`, `LOG_LEVEL`, `Events.pointerdown`, `ResolvedAliasInfo`, `Tap`, `ZobjPiece`, `VariableDefinitionNode`, `StageInfo`, `requests.ListWindowsUpdatesInstalledOnManagedInstanceRequest`, `GetExtensions`, `BungieService`, `Ethereum.Network`, `TextStyle`, `cachedStore.Container`, `HighlighterProps`, `BinaryInfo`, `Miner`, `sodium.KeyPair`, `BufferedChangeset`, `poolpair.PoolSwapMetadata`, `MigrationBuilder`, `NotificationTime`, `WritableComputedRef`, `NonNullTypeNode`, `RegLogger`, `LocalStorageSources`, `BitcoinBalanceMonitorConfig`, `UpdateDatabaseCommandInput`, `PuppetBridge`, `ImportEditor`, `DragDropService`, `EditorActionsManager`, `TCity`, `Terrain`, `DataStartDependencies`, `ModuleBody`, `IInstance`, `ListExperimentTemplatesCommandInput`, `ITestWizardContext`, `AsyncValidatorFn`, `ChainGunLink`, `ComplexNestedErrorData`, `Drive`, `UNIST.Node`, `interfaces.ServiceIdentifier`, `books.Table`, `ValidationEngine`, `Ban`, `ts.ParameterDeclaration`, `AST.Module`, `CreateDomainRequest`, `NodeVisitor`, `ThemeColorState`, `ErrorData`, `ExadataInfrastructureContact`, `vscode.MessageItem`, `GetRotation`, `VendorType`, `Globals`, `CustomSpriteProps`, `IMatrixCell`, `IdentifierObject`, `FunctionFallback`, `ActivationLayer`, `PlayingState`, `DebugProtocol.StepOutArguments`, `AliasMap`, `ObservableLanguage`, `CSSRule`, `FieldErrors`, `ParsedRoute`, `PutResourcePolicyCommand`, `ContainerForTest`, `RequestResult`, `SelectDropdownOption`, `JsonResponse`, `V1Namespace`, `MethodMap`, `DynamoDB.DocumentClient`, `MlContextValue`, `GraphConfiguration`, `IUserSubscription`, `EthTxType`, `DaffCartPaymentFactory`, `IgnoreQueryParamsInResponseCommandInput`, `Shuriken`, `ScopedClusterClientMock`, `Highcharts.PolarSeries`, `IRNG`, `Atomico`, `Kafka`, `PlansState`, `LoginResult`, `ViewCell`, `VerticalAlignments`, `IRuleCheck`, `TextDocumentChangeEvent`, `DefaultInputState`, `LedgerWalletProvider`, `ARCamera`, `PDFField`, `ActionSheetProps`, `MangleOptions`, `WebdriverIO.Browser`, `PureIdentifierContext`, `IGroupItem`, `OrganizationInterface`, `VoiceServerUpdate`, `SettingsService`, `QueryHints`, `DefaultState`, `MemFS`, `ResolvedEntitySchema`, `IOObjectSet`, `Research`, `Semigroup`, `MacroInfo`, `UnderscoreEscapedMap`, `MeshVertex`, `okhttp3.WebSocket`, `LoadEvents`, `SignedToken`, `MockWebSocket`, `IAnimationState`, `UpdateSecurityProfileCommandInput`, `ConfigurationOptions`, `ListSecretVersionsRequest`, `Ppu`, `UpdateContactCommandInput`, `VarAD`, `AppABIEncodings`, `CloseChannelParams`, `TranslatePipe`, `CdkDropList`, `q.Tree`, `GraphQLSubscriptionConfig`, `IOContext`, `UseSubscription`, `SNode`, `Observation`, `ParamConfig`, `types.IAzureQuickPickOptions`, `MyNFT`, `CompletedGatewayOptions`, `ContactsProvider`, `functions.storage.ObjectMetadata`, `DateOrString`, `AbstractMethod`, `Response`, `ComponentCommentIterator`, `DocumentRegistry.IContext`, `StartPlugin`, `River`, `FoamTags`, `TextType`, `EElementSignature`, `IAnimationOptions`, `Heading`, `JobNumbered`, `IMQRPCRequest`, `ChangeTheme`, `UIFill`, `MagentoOrder`, `EditableContent`, `MetaValue`, `clientSocket`, `MatchedStory`, `FileSystemEntryKind`, `Scroll`, `IKeyboardInput`, `PreprocessorGroup`, `NewableFunction`, `IGherkinLine`, `UpSetQueries`, `IElementColors`, `MdcChipSet`, `Unsub`, `JobRunLifecycleState`, `CBCharacteristic`, `IQueryProps`, `DefaultTextStyle`, `CancelTokenStatic`, `ExpShapeConcat`, `ErrorObject`, `ng.IHttpService`, `VariableDefinition`, `SelectDownshiftRenderProps`, `RelationshipProps`, `ContentState`, `ScannedProperty`, `ListTableRowsCommandInput`, `MessageCollector`, `FilterEntity`, `RendererNode`, `CrudRequest`, `ResolverData`, `ViewContainerTitleOptions`, `CommentItem`, `ContainerSample`, `StreamMetricReport`, `TransactionModel`, `ISiteScriptActionUIWrapper`, `OpaqueToken`, `CertificateSummaryBuilder`, `Files`, `PlanInfo`, `TabularDataset`, `nanoid`, `CallbackObject`, `TraitLocation`, `Element`, `Apps`, `CalculatedTreeNode`, `AccountService`, `PluginStrategy`, `SavedObjectConfig`, `JsonPointerTokens`, `MailTo`, `MarkerInfo`, `BaseReasonConfig`, `FMOscillator`, `GDQOmnibarBidwarOptionElement`, `OffsetIndexItem`, `DragDropConfig`, `NumericRange`, `Sanitizer`, `EventStream`, `NzTreeBaseService`, `API.services.IXulService`, `AcceptTokenRequest`, `Currency`, `requests.ListVolumeBackupPoliciesRequest`, `GradientBlock`, `Splice`, `HTMLIonRouterElement`, `SetStateFunc`, `ContentFolder`, `BinaryDownloadConfiguration`, `IStatRow`, `Critter`, `ApplicationVersion`, `CLM.CLChannelData`, `FilenameFilter`, `ChangeBundle`, `FlagshipTypes.AndroidConfig`, `TextColor`, `StringExpression`, `AxiosResponseGraphQL`, `ExcludedConditions`, `ListMatchesRequest`, `iField`, `ODataSegment`, `PSIReal`, `BoardView`, `ThreadItem`, `ArDrive`, `EventFnBefore`, `firestore.DocumentReference`, `CTR`, `XmlParser`, `FabAction`, `ToneMapping`, `MkFuncHook`, `Memo`, `tf.io.ModelJSON`, `StringKeyValuePair`, `UpSetQuery`, `ActionName`, `GeneralConfig`, `RecurringDepositsService`, `requests.ListServicesRequest`, `GradientBlockColorStep`, `IExecutorHandlersCollection`, `ChildAppRequestConfig`, `ITreeDataNode`, `CreatePolicyCommandInput`, `NormalizedFile`, `TabsConfig`, `NativeComputationManager`, `B9`, `CompanionData`, `$IntentionalAny`, `BlockTransactionString`, `files.FullLink`, `TagData`, `FieldFormatInstanceType`, `ISdkStreamDescriptor`, `OnSuccessCallback`, `ZWaveNode`, `AxeResults`, `StructureController`, `IServiceConfiguration`, `LinearGradientPoint`, `FileContent`, `RecordsRefs`, `uElement`, `IteratorResult`, `DocumentsExtImpl`, `BigQueryRetrieval`, `Weighter`, `RenderButtonsArgs`, `SettingService`, `Expense`, `TreeEnvironmentContextProps`, `VirtualNetwork`, `decimal.Decimal`, `PartyRemove`, `ReleaseType`, `RecordSource`, `OnCacheChangeEventFn`, `DisplayLabelsRequestOptions`, `OmvFeatureFilterDescriptionBuilder.MultiFeatureOption`, `IModifierRange`, `Fallback`, `ServerState`, `requests.ListApmDomainWorkRequestsRequest`, `CommandExecutorInterface`, `Relative`, `CharRenderInfo`, `IMergeTreeDeltaCallbackArgs`, `EventSearchRequest`, `JsonParserGlobalContext`, `Mocha.SuiteFunction`, `DescribeStreamCommandInput`, `PageIndex`, `Hit`, `CellItem`, `VariantCfg`, `F1`, `CellEventArgs`, `DeleteIntegrationResponseCommandInput`, `CompilerEventBuildFinish`, `a.Module`, `ThyGuiderConfig`, `IAuthenticationManager`, `StatusIcon`, `OutputChunk`, `LoggerWithTarget`, `BehaviorSubject`, `T9groups`, `ModalDialogOptions`, `TreeMapNode`, `ImageModel`, `MovieState`, `RTCRtpEncodingParameters`, `L2`, `RegClass`, `JSXElementConstructor`, `FuncType`, `CustomSettings`, `HttpResponseCodeCommandInput`, `PerpMarket`, `CreateConfigurationSetCommandInput`, `ListModel`, `CacheState`, `NavItem`, `LedgerService`, `Animated.Value`, `LegendStateProps`, `ResponseType`, `ParsedGeneratorOptions`, `PresentationPropertyDataProvider`, `GCM`, `DescribeDBParameterGroupsCommandInput`, `FileDataMap`, `UserPreKeyBundleMap`, `ElementHarness`, `Flashcard`, `IPodcast`, `UpdateUser`, `ReferenceExpression`, `Computer`, `Signer`, `ExecOptions`, `GroupWithChildren`, `UpdateJobRequest`, `DecodedInformation`, `VMLRenderer`, `SettingNames`, `ESLMedia`, `BaseRange`, `IForm`, `ValueNode`, `ts.UnionTypeNode`, `PriceRangeImpl`, `ObjectSetting`, `Warehouse`, `OutputTargetAngular`, `RequestArugments`, `CF.Get`, `TestableApiController`, `OAuthRedirectConfiguration`, `SafetyDepositDraft`, `ContactResponse`, `IAudioMetadata`, `LoadResult`, `TreeData`, `ResizeObserverEntry`, `InvokeDecl`, `ng.ITimeoutService`, `ParameterizedValue`, `ValidationQueue`, `DatetimeParts`, `LinkReduxLRSType`, `RemoteConfig`, `EdgeRouting`, `IndentNode`, `IToastProps`, `OutputTargetHydrate`, `HttpBackend`, `Mixer`, `RenderBatch`, `ts.CompilerOptions`, `CdtSite`, `CoreTypes.LengthType`, `EnhancedTransaction`, `HighRollerAppState`, `Todo_viewer`, `RoleModel`, `Simulator`, `BuildEvents`, `SpecialBreakTypes`, `TextTrack`, `Face3`, `DMMF.InputType`, `MIRPCode`, `GifFrame`, `CalendarDate`, `App.services.IWindowService`, `TagItem`, `Positioner`, `UserFields`, `CLIEngine`, `RetryStrategyOptions`, `EveesConfig`, `TodoModel`, `Gesture`, `ResOrMessage`, `ResourceCount`, `TextureInfo`, `MediaType`, `PropertyFactory`, `ClippedVertex`, `LiteralCompiler`, `requests.ListBudgetsRequest`, `RadixAtom`, `Tuplet`, `DeserializeEvent`, `AnimatedInterpolation`, `ContentObject`, `ListsPluginRouter`, `CommonStyle`, `CSSShadow`, `forge.pki.Certificate`, `IPropertyTemplate`, `IW`, `IStarterDependency`, `FilterInput`, `K`, `Initial`, `SkeletonProps`, `Rule.RuleMetaData`, `B64EncryptionResult`, `DeclaredElement`, `SensorElement`, `PartialParam`, `Pulse`, `UseRefetchState`, `Ops`, `ThyTreeNodeData`, `MatchData`, `TodoItemFlatNode`, `IProjectItem`, `WalletRecord`, `HTMLIonOverlayElement`, `JSONTopLevel`, `MigrationTypes`, `ISortCriteria`, `ChanLayer`, `TreeNodeValue`, `GraphTxnOutput`, `TaskManagerSetupContract`, `NodePosition`, `INamedDefinition`, `ServiceProvider`, `LobbyController`, `ReadonlyTuple`, `PaginationServiceStub`, `IGridColumnFilter`, `CopySnapshotCommandInput`, `AnimeNode`, `APIGateway`, `MergeTreeChunkV1`, `LroImpl`, `d.OutputTargetDocsReadme`, `SubmittableExtrinsic`, `DismissedError`, `GraphNodeID`, `MultisigItem`, `ClientSessionEntryIded`, `ObservableConverter`, `DeleteChannelModeratorCommandInput`, `RebaseResult`, `RootScreenDelegate`, `peerconnection.PeerConnection`, `MySQL`, `ImmutableAssignment`, `Connector`, `AppEpic`, `ObjectIdentifier`, `CustomConfigurationProvider`, `OutgoingStateType`, `MetricsModel`, `AuditedAttributes`, `PaperAuthor`, `TournamentList`, `ValidationRules`, `LiveSelector`, `SmallMultiplesGroupBy`, `BlobCreateSnapshotResponse`, `TestFunctionImportEntityReturnTypeParameters`, `NodeObject`, `ConsumeMessage`, `AuthRouteHandlerOptions`, `RadioOption`, `IPluginsContext`, `PrimitiveBundle`, `FoundationElementDefinition`, `IEventData`, `VisEditorOptionsProps`, `StructureRampart`, `ServerIdentity`, `IconifyElement`, `SequencePatternInfo`, `GitContributor`, `UsePreparedQueryOptions`, `settings.Settings`, `RatingPair`, `FieldTemplateProps`, `FieldArrayRenderProps`, `mod.LoadBalancerTarget`, `PopupInfo`, `LogType`, `DocumentSymbolParams`, `Metadata_Item`, `STColumnFilter`, `KVNamespace`, `DataRecognizer`, `FullConfig`, `TypedDataDomain`, `EntryList`, `ITokenService`, `EthereumCommon`, `LineSegments`, `BaseConverter`, `ToastItem`, `NameObjExecuteInfo`, `ESTree.MemberExpression`, `DomainSummary`, `DeleteGlobalClusterCommandInput`, `ProgressBarProps`, `CacheNotifyResult`, `GridLineStyle`, `InternalInstanceState`, `L2Item`, `ReadModelReducerState`, `IContent`, `AccountRepository`, `d.EmulateConfig`, `ExecutionScopeNode`, `IQueryParameter`, `IFieldOption`, `MenuController`, `Wine`, `Bindable`, `PhysicalObject`, `RawOptions`, `ColorPresentationParams`, `IEnvironmentRead`, `Identity`, `PolicyStatement`, `scriptfiles.ASScope`, `TimePeriod`, `SortConfig`, `MemoryStorage`, `AutocompleteProps`, `BuildTarget`, `Heightfield`, `UserMetadataStore`, `Bals`, `ParserInput`, `DaffCategoryFilterToggleRequestEqualFactory`, `YamlMap`, `SchemaEnv`, `RefactorContext`, `DetectionResult`, `IClusterClient`, `TypeAttributes`, `BaseDbFieldParams`, `Angle`, `TypeParameterReflection`, `MooaApp`, `fabric.IObjectOptions`, `ComponentFactory`, `ReplayTabState`, `RE`, `CustomLink`, `FieldArgs`, `PermissionContext`, `ColumnComponent`, `WindowRef`, `UnitsMap`, `StepOption`, `Renderer3`, `TypeApp`, `LogAnalyticsMetric`, `ICollectParms`, `OnboardingOpType`, `IntervalScheduler`, `AdvancedDynamicTexture`, `DataLoader`, `MonitorCollection`, `SafeElementForMouse`, `ResizeInfo`, `BiKleisli`, `Plugins`, `IAsset`, `firestore.QueryDocumentSnapshot`, `AudioVideoController`, `NavNode`, `ModalOptions`, `RuleContext`, `InsightType`, `DescribeEventsRequest`, `CommandExecutor`, `AccountID`, `CreateCertificateResponse`, `CreateClusterRequest`, `CellInput`, `ObservableHash`, `AsyncProcessingQueue`, `WStatement`, `GSMemoryMap`, `RSS3Index`, `SplitCalculator`, `ExchangePriceRepository`, `IPublicKey`, `Fn2`, `ManifestLoader`, `ILinkWithPos`, `ParsedFile`, `SiteStatus`, `PopoverStateReturn`, `listOptions`, `TraverseFunction`, `PageBlockRule`, `ContractDeployer`, `ToasterService`, `ethers.ethers.EventFilter`, `TypeContext`, `InMemoryFileSystemHost`, `FragLoaderContext`, `IEntry`, `DropletInfo`, `FactEnvelope`, `DotenvConfigOutput`, `SparseMerkleTreeImpl`, `Table2`, `ThreadData`, `IExecuteCommandCallback`, `AxisCoordinateObject`, `GetWorkRequestResponse`, `LayoutFacade`, `InterceptorManager`, `response`, `TokenFactory`, `ERC20Value`, `TrackGroup`, `TypeTemplates`, `TaskPool`, `CliCommandExecution`, `FunctionExpression`, `CkElement`, `IAtomHeader`, `SerializedConsoleImpl`, `FunctionDocumentation`, `EventType`, `capnp.List`, `ErrorBoundaryState`, `DummyTokenContract`, `MemoString`, `IPlan`, `TDataProvider`, `LocalProxiedEntry`, `ModuleMap`, `IStorages`, `AlertId`, `Types.RequestParameters`, `PerSignalDetails`, `TestRun`, `PassImpl`, `HubConnection`, `IBucket`, `DummyResolver`, `ISceneConfiguration`, `MVideoAccountLight`, `DashboardContainerInput`, `RematchStore`, `Align`, `P2PResponsePacketBufferData`, `ObservableFromObject`, `AddSchema`, `CRC16CCCommandEncapsulation`, `TransientGraphUtility`, `Experiment`, `RenderProps`, `QueryPrecedenceCommandInput`, `DebugProtocol.Response`, `GlobalsService`, `ShoppingCartService`, `MapboxGL.Map`, `ICandidateInterviewersCreateInput`, `StatusType`, `Preimage`, `CommunicationIdentifier`, `Fixtures`, `HTMLIonAccordionElement`, `CoreType`, `RequestHandlerParams`, `Span_Event`, `ButtonSize`, `UriLocation`, `SegmentHandler`, `AbbreviationMap`, `IDataPoint`, `RawProcess`, `ObjectPredicate`, `SankeyNode`, `SkipOptions`, `IocContext`, `requests.ListAccessRulesRequest`, `requests.ListAddressListsRequest`, `TooltipPosition`, `ExchangePriceRecord`, `TasksPluginReminderModel`, `FundedAwardModel`, `ResponsiveState`, `LmdbDbi`, `ConfigurationCCSet`, `ts.WhileStatement`, `GetRoomCommandInput`, `Orders`, `ArticleService`, `NodesRef`, `Pokemon`, `SpatialImageEnt`, `CustomersState`, `ZipIterator`, `ParameterInjectInfoType`, `OutlineManualServerEntry`, `React.ErrorInfo`, `ValueSuggestionsGetFnArgs`, `InstallerMachineContext`, `NotNeededPackage`, `RedBlackTree`, `OgmaPrintOptions`, `MemberInfo`, `SetupParams`, `ValueOrPromise`, `IPointPosition`, `PuppetRoomJoinEvent`, `VNodeWithAttachData`, `TooltipOperatorOptions`, `MarkdownView`, `WebStandardsDashboard`, `Collection`, `UserDataStore`, `EnvironmentVariables`, `PropertyFilter`, `CmbData`, `ConsoleSidebarLink`, `StatsCompilation`, `TransactionData`, `ManagedHsm`, `IGceDisk`, `WorkspaceDefinition`, `VisibilityFilter`, `TransactionEndedPayload`, `TAccessor`, `Material_t`, `QueryableFieldSummary`, `Enzyme.ShallowWrapper`, `CameraControllerClass`, `ZoneAndLayer`, `IAuthentication`, `R`, `WithGenerics`, `DynamoDbWrapper`, `MUST_CALL_AND_RETURN_SUPER_METHOD`, `UserVariableContext`, `ISharedDirectory`, `ServerDataImportStore`, `AsyncIterableIterator`, `TransientStore`, `RefreshTokenEntity`, `ContributorService`, `IChoice`, `SinonSandbox`, `ButtonColors`, `$RequestExtend`, `ClientInfo`, `AwsState`, `FunctionCallValue`, `GoToLabelProps`, `DeleteWriteOpResultObject`, `AssignmentNode`, `D2`, `Attribute.JSON`, `DxModelContstructor`, `RawDraftContentBlock`, `ContextMenuAccess`, `Paginate`, `PathMatcher`, `_ITable`, `p5ex.ShapeColor`, `ValueEdge`, `ApiTypes.UploadLinkRequest`, `language`, `IGetOptions`, `Plugin.Shared.Definition`, `LogicalExpression`, `ParserSourceFileContext`, `MyContext`, `QueryArg`, `StreamPipeOptions`, `JestEnvironmentGlobal`, `SyncSubject`, `NameSpaceInterfaceImport.Interface`, `ODataOptions`, `MathToSVGConfig`, `IHubContent`, `express.Application`, `NgxSmartLoaderService`, `TableRow`, `LoadingEvents`, `AutocompleteSelectCellEditor`, `Accessibility.SeriesComposition`, `UserRegister`, `ComponentStatus`, `IAstBuilder`, `TwilioServerlessApiClient`, `BitcoinjsKeyPair`, `ItemController`, `DaffCategoryFilterEqualOption`, `VerifyErrors`, `OutputDataSource`, `ModbusTransaction`, `NodeAndType`, `KanjiNode`, `TypedObject`, `Concept`, `CarSpec`, `DidChangeTextDocumentParams`, `SensorObject`, `IExecutionQueue`, `IOrganizationCreateInput`, `LogProperties`, `DirectoryResult`, `Pouchy`, `ContainerModel`, `requests.ListQuotasRequest`, `UseLazyQuery`, `CanvasTexture`, `PointerEventInit`, `UserAdministrative`, `ClarityAbiFunction`, `ICreateSessionOptions`, `QueryStart`, `FormService`, `ValidationFn`, `MetaTransaction`, `Parameterizer`, `Oracle`, `ColorDirection`, `ISelectedEmployee`, `BudgetItem`, `Physics2DServer`, `MatSlideToggleChange`, `SendTransactionOptions`, `IDialogConfiguration`, `UserAuth`, `ConcreteTaskInstance`, `FlatNode`, `ScrollEventData`, `SimpleToast`, `HeaderMapTypeValues`, `Throttler`, `SetInstallPrompt`, `ActivityItem`, `XI18nProperty`, `VertexLabels`, `CanaryExecutionResult`, `SelectionScopeRequestOptions`, `Required`, `VirtualNetworkGateway`, `WaterfallStepContext`, `T.Component`, `NumberRange`, `Deno.Addr`, `AnnotationService`, `EqlCreateSchema`, `StyledElementLike`, `BitcoinStoredTransaction`, `monaco.languages.IState`, `dia.Element`, `RoutesService`, `TKind`, `BigIntInstance`, `InfluxDB`, `CustomWorld`, `ErrorTypes`, `HistoryItemImpl`, `MlJobWithTimeRange`, `workspaces.WorkspaceDefinition`, `CollectDeclarations`, `ArXivStorage`, `k8s.types.input.core.v1.PodTemplateSpec`, `SettingsRepository`, `SessionStateControllerTransitionResult`, `BlockStatement`, `GetSampledRequestsCommandInput`, `Auto`, `InitializeSwapInstruction`, `HalfEdge`, `TwingTest`, `MockEvent`, `ConfigState`, `CheckSavedObjectsPrivileges`, `Guid`, `Spinner`, `RootSpan`, `TableAliasContext`, `requests.ListAvailableWindowsUpdatesForManagedInstanceRequest`, `PersistedStateKey`, `StructureNode`, `ListNotificationsRequest`, `EvaluateCloudFormationTemplate`, `UpdateProjectCommandInput`, `DemographicsGroup`, `ComboBox`, `requests.ListScheduledJobsRequest`, `CommandInterface`, `UpdateWriteOpResult`, `By`, `FilePickTriggerProps`, `WalkResult`, `Orderbook`, `AbstractCamera`, `CheckRun`, `t.Expression`, `FocusEvent`, `ThemeState`, `IBoxProps`, `RenderView`, `DeployUtil.ExecutableDeployItem`, `DataViewComponentState`, `StoreCreator`, `MergeTree.TextSegment`, `IAlert`, `SettingEntity`, `MyClass`, `BIterator`, `ITimerToggleInput`, `Newsroom`, `EncryptedShipCredentials`, `XTransferSource`, `DataId`, `CalendarDateInfo`, `DaffCartItem`, `LocalPackageInfo`, `MVideoFullLight`, `SparseVec`, `WebGLRenderingContext`, `UserAnnotationSet`, `InternalCoreUsageDataSetup`, `MappingsEditorTestBed`, `CmsGroup`, `Launcher`, `MyEThree`, `listenTypes`, `ICoverageCollection`, `ListJobsByPipelineCommandInput`, `AndroidActivityBackPressedEventData`, `ThemeService`, `ActivityFeedEvent`, `ControllableEllipse`, `BMapGL.Point`, `DescribeConnectionsCommandInput`, `TitleProps`, `AfterCombatHouseCardAbilitiesGameState`, `ContractData`, `ChangeMap`, `IBlockchainProperties`, `AuthorizeOptions`, `FunctionContext`, `EnvelopeListener`, `Events.kill`, `ora.Ora`, `RepositoryStateCache`, `Justify`, `ShapeInstanceState`, `QuickInputButton`, `DeleteRepositoryResponse`, `WFWorkflow`, `CallOptions`, `MaybeType`, `OptionsWithMeta`, `QueryDefinition`, `DatabaseTransactionConnection`, `CollectionTransaction`, `FirstConsumedChar`, `IndexingConfig`, `FieldFilter`, `WyvernSchemaName`, `DinoContainer`, `FakeCard`, `UpdateAccountRequest`, `AstVisitor`, `UpdateDeploymentCommandInput`, `ClassSymbol`, `files.FullFilePath`, `StylableResolver`, `JsonDocsMethod`, `Draft`, `ColorString`, `CoreSavedObjectsRouteHandlerContext`, `LexDocument`, `PartyLeader`, `TabularLoaderOptions`, `LegendItem`, `DataTable.CellType`, `ir.Stmt`, `IParameterTypeDefinition`, `GfxTexture`, `TextEditChange`, `ICloudFoundryCreateServerGroupCommand`, `IntersectParams`, `Views.View`, `INgWidgetPosition`, `IUpworkDateRange`, `IDeviceInterface`, `GetFieldsOptions`, `ChatModule.chatRoom.ChatPubSubMessage`, `ConventionalCommits`, `GameStateModel`, `BuildFailure`, `CreateIndexNode`, `IDescriptor`, `FieldParser`, `CompilerIR`, `EventDispatcherEntry`, `RemoveSourceIdentifierFromSubscriptionCommandInput`, `IChange`, `IUpdateOrganizationCommandArgs`, `VirtualElement`, `LoaderService`, `ast.AbstractElement`, `SpriteSheet`, `RequestApprovalEmployee`, `GraphQLQueryBuilder`, `DialogContextValue`, `CachedProviders`, `EventFilter`, `ESLAnimateConfigInner`, `TokenizerOutput`, `AccessToken`, `MyUnion`, `RtcpHeader`, `EvaluationFunction`, `Comparer`, `dom.Node`, `React.Context`, `FlowsenseCategorizedToken`, `IndyLedgerService`, `MediatorMapping`, `DSpaceObjectDataService`, `DatabaseFacade`, `ExternalAuthenticateResultModel`, `ListApplicationsRequest`, `Monoid`, `TikTokScraper`, `RouteLocationNormalized`, `SpriteEffect`, `InstalledPlugin`, `ThySlideService`, `StorageTransformPlugin`, `SwitchIdInfo`, `IHash`, `ColumnExtension`, `OriginConnectionPosition`, `StatefulSearchBarDeps`, `Cancellation`, `CommandDescriptor`, `GameVersion`, `AddAsTypeOnly`, `XMLBuilderState`, `IOrganizationVendor`, `XPath`, `JitsiLocalTrack`, `TestFunctionImportComplexReturnTypeCollectionParameters`, `CohortCreationState`, `RelativeTimeFormatOptions`, `TokenBurnV1`, `ServiceStatusLevel`, `ChapterStatus`, `QueryCacheEntry`, `J3DLoadFlags`, `CreateTRPCClientOptions`, `GridCellValue`, `IMyChangeRequestItem`, `IServerResponse`, `OrSchema`, `DecltypeContext`, `IObjectDefinition`, `ViewPortService`, `MAL`, `TSPass`, `NzDestroyService`, `DeploymentTargetConfig`, `coord`, `HostCreatedInstance`, `ITestState`, `ResourceRequirement`, `TReference`, `ParserPlugin`, `ResEntry`, `IssuesListCommentsResponseItem`, `FixedTermLoan`, `LiftedStore`, `RuleExpr`, `AnimationKeyframe`, `WgConfigFile`, `WalletKeys`, `nodenCLContext`, `FilterProps`, `ts.ScriptTarget`, `Subscribable`, `IAuthContext`, `NodeWithPos`, `SanitizedProtonApiError`, `IVSCodeWebviewAPI`, `OrderImpl`, `INumberFilter`, `BeancountFileService`, `ScaleString`, `DayHeaderWrapper`, `ListPortalsCommandInput`, `YAMLMap`, `TransactionConfig`, `IDetachable`, `TsConfigSourceFile`, `IRedisOptions`, `UI5SemanticModel`, `PlanGraph.Entities.GraphData`, `CustomTag`, `MaxVersions`, `BeButtonEvent`, `PrivateKey`, `ShowNewVisModalParams`, `SelectorFn`, `NodeEvaluateResult`, `RequesterMap`, `FsUri`, `NameIdentifier`, `Spatial`, `tf.io.TrainingConfig`, `IConnectionInfo`, `Font`, `XYZSizeModeValues`, `MessagingPayload`, `AvailabilityZone`, `XMessageService`, `AsyncSettings`, `CreateConfigurationSetEventDestinationCommandInput`, `HTMLProgressElement`, `ImmutableMap`, `DAL.DEVICE_NULL_DEREFERENCE`, `ConnectionPositionPair`, `Associativity`, `ParameterDetails`, `PaymentOpts`, `Any`, `requests.ListBootVolumeAttachmentsRequest`, `PathMatch`, `SearchInWorkspaceWidget`, `Idea`, `WrappingCode`, `message`, `ClassMemberLookup`, `FsReaddirItem`, `GuildChannel`, `AngularFirestoreCollection`, `ITelemetryLoggerPropertyBags`, `SubtleCrypto`, `ExpressionContainer`, `CreateStateHelperFn`, `HookHandler`, `DefinitionYAMLExistence`, `IEntityGenerator`, `Incoming`, `parser.Node`, `Xform`, `CircularQueue`, `OpenCommand`, `Dree`, `PostgresInfo`, `LabelProvider`, `MssEncryption`, `ProgramOptions`, `TransformNode`, `NavigationGraphicsItem`, `SinglePointerEvent`, `IFabricEnvironmentConnection`, `IRoomData`, `requests.ListComputeGlobalImageCapabilitySchemasRequest`, `TensorContainer`, `TargetDetectorRecipeDetectorRuleSummary`, `d.RobotsTxtResults`, `ContextFlags`, `IModelContentChangedEvent`, `LocalizeFunc`, `NewDeviceDTO`, `ITelemetryBaseEvent`, `PseudoClassSelector`, `AtomGetter`, `SerializedAnalysis`, `FovCalculation`, `QuestaoModel`, `FractionalOffset`, `Uint64`, `RepoSideEffectPendingExpectation`, `EnumNodeAndEdgeStatus`, `Type_AnyPointer_ImplicitMethodParameter`, `NamedProblemMatcher`, `ExtendedFloatingActionButton`, `RadixAID`, `IFormItemProps`, `IJetApp`, `CreateAudioArgs`, `IUploadedFile`, `requests.ListTaggingWorkRequestsRequest`, `active`, `MockDeploy`, `ArgMap`, `BlockNumber`, `BottomNavigationBar`, `DevServerService`, `ColumnPropertyInternal`, `WebviewPanelImpl`, `ScopeTransform`, `ProductsService`, `CatchClause`, `TracingBase`, `Dimension`, `RTCSctpTransport`, `SSHExecCommandResponse`, `ChatMessageReceivedEvent`, `IMonthAggregatedEmployeeStatisticsFindInput`, `Phaser.Types.Core.GameConfig`, `Mathfield`, `DataQueryRequest`, `TextEditor`, `ConvLayerArgs`, `ProductReview`, `SpringChain`, `StandardAuthorization`, `CascaderOption`, `MethodDeclarationStructure`, `VisualizationListItem`, `SVGVNode`, `DrilldownState`, `ReplacePanelActionContext`, `HubConfigInterface`, `BindingType`, `OrderBook`, `DoorLockLoggingCCRecordReport`, `DetectedCronJob`, `ContractOperationCallback`, `PrimitiveTypeDescription`, `ChainablePromiseElement`, `NamedStyles`, `Property`, `SchemaFunctionProperty`, `MSGraphClient`, `EventPartialState`, `LoginSession`, `IGatewayMember`, `UnitSystemKey`, `MonadIO`, `TSubscribeHandler`, `SendProp`, `IChangeEvent`, `TypeDBTransaction.Extended`, `RepositoryKind`, `InternalBulkResolveParams`, `SFCBuildProps`, `UICollectionDelegateImpl`, `X12Element`, `Outcome`, `OverviewTestBed`, `TopologyData`, `AwsTaskWorkerPool`, `StorageObjects`, `FindEslintConfigParams`, `RefactorBuffer`, `ImportsMetadata`, `TransformationMatrix`, `ProcessStageEnum`, `RemoveTagsFromResourceCommandInput`, `AliasOrConnection`, `StorageService`, `BlogService`, `Rights`, `Timespan`, `ResolverOptions`, `SavedObjectOptionalMigrationFn`, `ITagSet`, `ITypeMatcher`, `EqState`, `MessageBuffer`, `UpdateManager`, `Fn1`, `Part`, `SpecHelperConnection`, `IWarrior`, `LaunchRequestArguments`, `Html2OrgOptions`, `EdiDocumentConfigurationResult`, `CLLocationCoordinate2D`, `FootnotesItem`, `AddressDetails`, `requests.ListAutonomousDatabaseClonesRequest`, `LogFunctions`, `GqlExecutionContext`, `DashboardComponent`, `OutboundPackage`, `VFSRef`, `t.File`, `LocKind`, `DrawerNavigationState`, `SharedMatrix`, `UpdateResponseData`, `ContactList`, `ModifyLoadBalancerAttributesCommandInput`, `BezierCurve3dH`, `WaterPoint`, `ICategoricalColorMappingFunction`, `SavedObjectType`, `TSESTreeToTSNode`, `CieloTransactionInterface`, `RtcpPacket`, `ModuleJob`, `IApprovalPolicyCreateInput`, `SinonFakeTimers`, `BotState`, `IQuizFull`, `Yendor.Tick`, `CollectorFetchContext`, `fromSingleRepositoryStatisticsActions.GetRepositoryStatistics`, `TickSource`, `androidx.transition.Transition`, `OuterExpressionKinds`, `TsProject`, `HeatmapConfig`, `Curried`, `GitHubIssue`, `QUICError`, `TypeResult`, `SolutionDetails`, `MeetingState`, `ISignal`, `ControlsProps`, `CustomRegion`, `TextWidthCache`, `SelectRangeActionContext`, `CachedMapEntry`, `PreparedFn`, `ApplicationTemplateAPIAction`, `BarDataSet`, `UtilProvider`, `HighlightInfo`, `SocketIoChannel`, `INodeType`, `EndpointInfo`, `PopulatedTransaction`, `RecentData`, `IPartitionLambdaFactory`, `SpanAttributes`, `GroupOrientation`, `JobResultDTO`, `Facade`, `IntNode`, `Range`, `ComputedScales`, `InputLayer`, `GeolocationService`, `FeedbackState`, `AjaxAppender`, `Events.start`, `CreateTypeStubFileAction`, `ConsoleLogger`, `UserAccountID`, `ConfigurationProperty`, `DataAccess`, `GetterHandler`, `RenderDeps`, `IBuildApi`, `AuthToolkit`, `WorkspaceConfig`, `ItemIndex`, `FeatureValue`, `KbnFieldType`, `AtomizeNecessary`, `MatchersUtil`, `CredentialPreview`, `ExpShapeConst`, `MlCapabilities`, `HTMLHtmlElement`, `ApplyHandler`, `Replica`, `Espree`, `IpcMainEvent`, `IResponseMessageHandler`, `MessageItem`, `EthereumClient`, `ParameterGroup`, `MatTabChangeEvent`, `GeoCoordinatesLike`, `PickerProps`, `PDFAcroCheckBox`, `ArianeeWallet`, `ElectronRoleCommand`, `SuggestionsComponentProps`, `ChatAdapterState`, `Monitoring`, `InstancePool`, `DeleteScheduledActionCommandInput`, `Overloads`, `ComponentWithMeta`, `SignInOutput`, `RawAlertInstance`, `ConsoleMessage`, `PSIChar`, `RulesTestEnvironment`, `VisualizeFieldContext`, `ts.SetAccessorDeclaration`, `NucleusVersion`, `InheritedCssProperty`, `StreamState`, `TableViewModel`, `HTMLCanvas`, `IStepAdjustment`, `TimeoutError`, `ISampleDescription`, `ts.SourceFile`, `OrbitDefinition`, `PostgresAdapter`, `ScrollOptions`, `FieldHierarchy`, `chromeWindow`, `Dynamic`, `DbPatch`, `StatelessOscillator`, `EmitHelper`, `DaffAuthToken`, `ts.PropertyAccessExpression`, `q.Message`, `FailureDetails`, `SavedSearch`, `CollapsedFormatField`, `ResolvedSchema`, `CampaignTimelineChanelPlayersModel`, `DragObjectWithType`, `InternalSymbol`, `JSDocUnionType`, `PlainValue`, `SUUID`, `InterfaceWithCallSignature`, `ObservablePoint3D`, `ExperimentStateType`, `OpenYoloProxyLoginResponse`, `RawError`, `SwaggerConfig`, `BanList`, `NzCascaderOption`, `IStoreState`, `FormConfig`, `ICkbMint`, `ExchangeAccount`, `IMDBVertex`, `AceConfigInterface`, `XmlFile`, `MergeTree.PropertySet`, `GunGetOpts`, `Value`, `MakeErrorMessage`, `RadixAddress`, `InlineComposition`, `MediaDeviceInfo`, `IUploadAttributes`, `I80F48`, `vscode.ConfigurationTarget`, `VerifyEmailAccountsRequestMessage`, `GPattern`, `LeafonlyBinaryTree`, `HarperDBRecord`, `ViewBase`, `RemovableAtom`, `InsertUpdate`, `GitHubRepository`, `IAckedSummary`, `CacheStore`, `DynamicArgument`, `LocalActorSystemRef`, `PreviousSpeakersActions`, `PhysicsBody`, `InjectedQuery`, `TodoTxtTask`, `IReserveUpdateValues`, `Cache`, `MutableVector3`, `OceanSpherePoint`, `DefaultViewer`, `ConnectionAction`, `SpeechConnectionMessage`, `ISurveyCreatorOptions`, `UnitConversion`, `MiddlewareContext`, `CodeGenDirective`, `Meter`, `PluginViewWidget`, `ethereum.UnsignedTransaction`, `ResourceHolder`, `fieldType`, `VariableDefinitions`, `GetOrganizationParams`, `ChangedData`, `TOperand`, `DbDrop`, `ModulesContainer`, `StartServicesGetter`, `interfaces.CommitType`, `IImageryMapPosition`, `BuiltRule`, `LPStat`, `CommentInfo`, `LookupExpr`, `StylableMeta`, `Connection`, `DMMF.OutputType`, `CompilationError`, `Cards`, `Package`, `MockERC20Instance`, `TokenTypes`, `ReducerState`, `HandshakePacket`, `IEffectExclusions`, `DeclarationCache`, `ASN`, `HeroCollection`, `SearchInWorkspaceFileNode`, `ErrorValue`, `ActionMeta`, `SubscriptionLike`, `SemanticContext`, `IModelTemplate`, `requests.ListApplianceExportJobsRequest`, `XHRBackend`, `APIQuery`, `NxData`, `IterationService`, `UIntTypedArray`, `WorkItem`, `TAtrule`, `InitUI`, `GenerateSWOptions`, `DbSchema`, `StatusPresenceEvent`, `tBootstrapArgs`, `Types.EventName`, `AuthVuexState`, `ItemRepository`, `IDBKeyRange`, `IShape`, `CommandManager`, `IGitRemoteURL`, `AdtHTTP`, `httpm.HttpClient`, `J`, `FunctionPlotOptions`, `RequestSigner`, `StructsLib1.InfoStruct`, `AgeOrForm`, `OperationDefinitionNode`, `CardFinder`, `Product`, `FieldFormatParams`, `JSONValue`, `FirebaseMock`, `DebugInfo`, `ModelJSON`, `RotType`, `DeleteApplicationCloudWatchLoggingOptionCommandInput`, `EveesMutationCreate`, `UserItem`, `UIScrollView`, `FuncInfo`, `Customer`, `BarPrice`, `ListDevicesCommandOutput`, `DatabaseUsageMetrics`, `AuthorisationService`, `FeatureType`, `VectorStylePropertiesDescriptor`, `AssetReferenceArray`, `DocumentColorParams`, `TextureMapping`, `Renderer`, `AnnounceNumberNumberCurvePrimitive`, `BuildHandlerOptions`, `IStatusProvider`, `IReactComponentProps`, `PIXI.Texture`, `ICkbBurn`, `MatDrawer`, `VerificationClientInterface`, `CreateKeyPairCommandInput`, `ElevationRange`, `MonitoringParametersOptions`, `ISupportCodeExecutor`, `NodeVM`, `PositionOptions`, `ERC20FakeInstance`, `OnPreRoutingResult`, `LoaderInstance`, `SpaceBonus.DRAW_CARD`, `onChunkCallback`, `AssessmentItemController`, `LogoImageProps`, `ParserErrorListener`, `requests.ListLogsRequest`, `ArcGISAuthError`, `TransactionReducerResult`, `SupCore.Data.ProjectManifestPub`, `ShownModallyData`, `DeleteManyResponse`, `IWorkspaceDir`, `HKDF`, `Explorer`, `ReadonlyMap`, `TaskEvent`, `ExecutionContext`, `Season`, `TPluginsSetup`, `ReflectCreatorContext`, `ReportTaskParams`, `IKeyObject`, `ConditionalStringValue`, `track`, `OverridedMdastBuilders`, `VsCodeApi`, `IJsonRpcRequest`, `DeleteBackupResponse`, `$p_Expression`, `FailedAttemptError`, `ts.LiteralTypeNode`, `IHttpPromise`, `DirectoryItem`, `ILibraryResultState`, `TreeNodeGroupViewModel`, `TrackOptions`, `Stack`, `FieldDetails`, `LocationSet`, `CodeSpellCheckerExtension`, `TableStorageContext`, `RendererResult`, `WechatyPlugin`, `SpatialImagesContract`, `StepExecution`, `VueSnipState`, `TabsProps`, `CorsRule`, `CardRequirement`, `DistanceMap`, `CommandStatus`, `requests.ListCrossConnectLocationsRequest`, `FieldPath`, `FunctionBuilderArguments`, `XSLTokenLevelState`, `lsp.Diagnostic`, `StripeService`, `ListOption`, `CommandFunction`, `IT`, `DeltaAssertions`, `SpawnerOrObservable`, `AnimationPosition`, `FormFieldsType`, `ReferenceEntry`, `NetworkListenerArgs`, `ColumnOptions`, `FilteringPropertyDataProvider`, `requests.ListEdgeSubnetsRequest`, `CategorizedMethodMemberDoc`, `WeakMap`, `UIntCV`, `Register8`, `EllipseProps`, `angular.IHttpPromise`, `WorkflowEntity`, `AreaFormType`, `AnnotatedFunctionABI`, `APIEndpoint`, `Indexed`, `TypeResolution`, `IConstrutor`, `SwitchApplicationCommand`, `ClientSession`, `PendingResult`, `AlertAccentProps`, `SnapshotGenerator`, `KeyValType`, `CreateConfig`, `OverlayInitialState`, `MyResource`, `SelectTokenDialogEvent`, `IceTransport`, `SFPage`, `CredentialCache`, `TranslationChangeEvent`, `StateMethodsImpl`, `RequiredOrOptional`, `Descriptor`, `BaseGraphRewriteBuilder`, `CertificateAuthorityConfigType`, `Logout`, `GenerateOptions`, `NonEmptyString`, `OmvFeatureFilter`, `FileSchemaKey`, `DataBuckets`, `FluentUITypes.IDropdownOption`, `RestFinishedResponse`, `ScenarioData`, `JSONInMemoryCache`, `ConfigurationFile`, `ErrorDetailOptions`, `BScrollFamily`, `DLLData`, `MetricSet`, `NodeCheckFlags`, `DefaultTheme`, `PianoService`, `VdmEntity`, `QuickPickOptions`, `FilterNode`, `DepositAppState`, `PreviewProps`, `SourceString`, `Mars.NumberLike`, `ScheduledEventRetryConfig`, `messages.IdGenerator.NewId`, `PageCollection`, `Editor`, `LambdaEvent`, `SpeechCommandRecognizerResult`, `HsSaveMapService`, `TLineChartPoint`, `AgentIdentity`, `TabChangeInfo`, `TCalendarData`, `Advisor`, `ApiSettings`, `QueryStateChange`, `MockRequest`, `TransferedRegisterCommand`, `DistinctPoints`, `ListChannelsModeratedByAppInstanceUserCommandInput`, `OpenChannel`, `CalendarsImpl`, `WorkerMsgHandler`, `ObservableOption`, `ENV`, `OpenSearchDashboardsDatatableColumn`, `ImageSpecs`, `Cost`, `ElementComponent`, `PhysicalElementProps`, `UnsignedMessage`, `KeyframeIcon`, `Annotations`, `StyleAttribute`, `IEventLogService`, `MatrixType`, `Prisma.JsonValue`, `Apify.RequestQueue`, `Visual`, `KernelMessage.IOptions`, `AttributeDecoratorOptions`, `tmp.DirectoryResult`, `D.State`, `FacemeshOperatipnParams`, `TypeParameterDeclaration`, `ReadonlyObject`, `CSReturn`, `IRecurringExpenseEditInput`, `ReadableByteStreamOptions`, `HapiResponseToolkit`, `Register32`, `VisualDescriptor`, `IMouseEvent`, `ObjectDeclaration`, `UpdateParameterGroupCommandInput`, `DaffCategoryFilterRangePair`, `RequestManager`, `ajv.ErrorObject`, `TimelineLite`, `Precision`, `jasmine.CustomReporterResult`, `Types.PluginOutput`, `TransmartPackerHttpService`, `MockContainerRuntimeFactory`, `TagResourceOutput`, `VideoFileModel`, `IndexPatternFieldMap`, `PropertyResolver`, `GShare`, `scribe.Config`, `api.ISnapshotTree`, `DatabaseV2`, `InstallProfile`, `Timeslice`, `ManagedDatabase`, `WatchDirectoryFlags`, `AngularExternalResource`, `NodeProtocolInfo`, `SymbolMetadata`, `events.Args`, `ExpanderQuery`, `IOrganizationProject`, `AbstractView`, `LogResult`, `FixableProblem`, `SceneState`, `RxCacheService`, `DescribeEventsCommand`, `IiOSSimulator`, `IImage`, `ValidationExceptionField`, `LogViewer`, `ForwardInfo`, `SteemConnectProvider`, `IValidBranch`, `BarColorerStyle`, `ContainerPassedProps`, `TopNavConfigParams`, `IpcRendererListener`, `TreeItemIndex`, `INodeExecutionData`, `$Promisable`, `GenericAction`, `Quickey`, `ListWebhooksCommandInput`, `CompilerSystemRemoveFileResults`, `IContact`, `AvailabilityTestConfig`, `InstrumentationConfig`, `FullPath`, `TaskParameters`, `MathOptions`, `DecodedMessage`, `MoveAction`, `TimelineBucketItem`, `IExternalPrice`, `OutputTargetDist`, `IProvider`, `ColorTokens`, `IDataRow`, `ApplicationCommandOptionData`, `Inversion`, `DeeplyMockedKeys`, `ExtendedCluster`, `EdgeSnapshot`, `ListStudiosCommandInput`, `IParserConfig`, `JoinStrategy`, `ExceptionConverter`, `StaticSiteARMResource`, `CreateInstanceCommandInput`, `CacheKey`, `HSD_TExp`, `AnimationsService`, `InsertOptions`, `TypeModel`, `OneOrMore`, `MagicSDKError`, `RepositoryModel`, `RecordDataIded`, `SecurityAlertPolicyName`, `HLTVConfig`, `ExerciseService`, `ElementNames`, `SinglesigAddressType`, `ParseString`, `Mount`, `BlockParameter`, `ModeType`, `DiskAccess`, `AttributeSelector`, `RawData`, `SkeletonShapeProps`, `DataProviderProxy`, `SearchParamsMock`, `RuleDeclaration`, `CancelQueryCommandInput`, `vscode.DocumentSelector`, `ITccProfile`, `IFBXRelationShip`, `PluginInterface`, `SourceDocument`, `HammerManager`, `BaseVisType`, `ICharacter`, `GameStartType`, `DayFitnessTrendModel`, `ResolvedRecordAtomType`, `ServerResponse`, `ValueAndUnit`, `BlockchainPropertiesService`, `ADTClient`, `ArrayValue`, `JupyterLab`, `Immutable.Map`, `ParsedUrlQuery`, `NeverType`, `NVNode`, `ParsedDevModuleUrl`, `SFSchemaEnum`, `Audit`, `IssuePayload`, `ShoppingCartContextValue`, `PrimitivePolygonDrawerService`, `StyleObject`, `PagedResult`, `MultiSigSpendingCondition`, `XMessageBoxService`, `ToolAssistanceInstruction`, `MemoryUsage`, `backend_util.BackendValues`, `SchemaVisitorFactory`, `AssetBindings`, `VdmMappedEdmType`, `BibtexAst`, `RouteGroup`, `DaffError`, `GalleryItem`, `MousePressOptions`, `Aurelia`, `UseMutation`, `io.LoadOptions`, `PoiTableEntry`, `DaffProductServiceInterface`, `ModalHelperOptions`, `JoinRow`, `ProblemMatcher`, `CreateJobResponse`, `GuideData`, `BedrockFileInfo`, `ExtraData`, `ContractABI`, `TagListQueryDto`, `FactoryContext`, `ExtractorInput`, `ServerViewPageObject`, `ChatNode`, `MenusState`, `ApisService`, `EdgeDescriptor`, `ItemState`, `Deserializer`, `IBLEAbstraction`, `AbstractFetcher`, `TransactionRequest`, `requests.ListWaasPolicyCustomProtectionRulesRequest`, `AutorestContext`, `AwarenessUpdate`, `SchemaName`, `SigError`, `RequestArgs`, `TrackEntry`, `ReactFCNoChildren`, `MatchLeave`, `ts.TupleTypeNode`, `Probot`, `TileCoordinator`, `Student`, `TextRewriterState`, `IThemeWeb`, `IDatabase`, `FilePath`, `IClusters`, `InternalException`, `TxPayload`, `MockClass`, `angular.ui.bootstrap.IModalService`, `TypeOfContent`, `IndexTemplateMapping`, `Burst`, `TestMessages`, `ContainerType`, `Benchmark`, `AttributeValueType`, `vscode.Diagnostic`, `Key1`, `QBoxLayout`, `PersistenceManager`, `SymbolOriginInfo`, `Issue`, `ObjectSelector`, `RequestWithdrawalDTO`, `Align1`, `SearchCriteria`, `Operations`, `AsyncStateRetry`, `LanguageMatcher`, `ContractAbi`, `ICommit`, `StateHelper`, `IKeyEntry`, `Web3SideChainClient`, `CrochetTypeConstraint`, `DefaultBrowserBehavior`, `UserDocument`, `VariableArgs`, `RenderTreeEdit`, `TransactionList`, `StripeConfig`, `SetGetPath`, `RouteInitialization`, `NavItemProps`, `Redis.Redis`, `TypedLanguage`, `IExpectedSiop`, `d.Module`, `ConsoleInterceptor`, `IDataContextProvider`, `GfxrResolveTextureID`, `RetrieveResult`, `TDeclarations`, `TokenDetails`, `OverlayOptions`, `VueApolloSmartOpsRawPluginConfig`, `PiElement`, `PublicKeyData`, `IconifyAPIIconsQueryParams`, `ErrorThrower`, `DatasetManagerImpl`, `Filesystem.PackageJson`, `SFCBlockRaw`, `WrappedComponentRoot`, `LiteralSource`, `EditorModel`, `CallHierarchyIncomingCallsParams`, `React.ForwardRefExoticComponent`, `ISubmitEvent`, `Cdt`, `Simulation`, `ApolloSubscriptionElement`, `requests.ListStandardTagNamespacesRequest`, `GDQOmnibarListElement`, `ConcurrentModificationException`, `UserButton`, `MockStyleElement`, `IUnit`, `LinkModel`, `PublicPlayerModel`, `PeerTypeValues`, `ICallback`, `StateTimeline`, `MaterialButton`, `CommonInfo`, `LabwarePositionCheckStep`, `DiagnosticAction`, `SutTypes`, `ICategoryCollectionState`, `ColorSchemeId`, `SpyAsyncIterable`, `BuilderProgramState`, `TrainingConfig`, `PDFOptions`, `ManagedItem`, `MDCDialogCloseEvent`, `StatBlock`, `quat`, `MockAthena`, `AggregateBuilder`, `ExpressionFunctionVisualization`, `MaterialEditorOptions`, `AbstractSqlDriver`, `LatexAtom`, `MangoAccount`, `LibraryOptions`, `CurveFactory`, `ServerActionHandler`, `IDragEvent`, `JSHandle`, `AssertionContext`, `PlayerClass`, `SynthDefResultType`, `vscode.CompletionContext`, `WriteStorageObject`, `RawMatcherFn`, `ServiceHelper`, `HSLA`, `TestDisposable`, `Category2`, `XsltPackage`, `JPAResourceRaw`, `InstanceOf`, `CommandEnvelope`, `RadioComponent`, `XConfigService`, `IPricedItem`, `OutputTargetDocsVscode`, `JSheet`, `NineZoneStagePanelsManagerProps`, `StructurePreviewProps`, `BuildOnEventRemove`, `SelectionSource`, `IGetTimeSlotStatistics`, `ts.TextChangeRange`, `ISearchParams`, `IVocabularyItemWithId`, `TemplateBlock`, `PAT0_MatData`, `LineGeometry`, `ActOptions`, `PvsTheory`, `HelperOptions`, `DOMWindow`, `FileUploadState`, `ShortId`, `IDebtsGetByContactState`, `ProxySettings`, `ModuleWithComponentFactories`, `PluginConfigSchema`, `OptionTypeBase`, `XNotificationOption`, `EnteFile`, `d.ComponentRuntimeMeta`, `FieldMeta`, `EndpointName`, `TooltipState`, `TAccessQueryParameter`, `WorldgenRegistryHolder`, `SharingResult`, `RenderTexture2D`, `CAST_STRATEGY`, `DidOpenTextDocumentParams`, `TestItem`, `IFetchOptions`, `IUiSettingsClient`, `ColorInfo`, `LSAndTSDocResolver`, `PurchaseList`, `Parent`, `appleTransactions.Table`, `IniData`, `DescribeLoadBalancerAttributesCommandInput`, `DSONameService`, `LambdaCloseType`, `AdjustNode`, `OptimizeModuleOptions`, `Overlay`, `ChatService`, `RowSet`, `UserClients`, `ResultItem`, `SExp`, `GraphImpl`, `RestoreDBClusterToPointInTimeCommandInput`, `AsyncSnapshot`, `Firmware`, `DataViewFieldBase`, `UiPlugins`, `Url`, `ActionTypeRegistry`, `ReactorConfig`, `MessageDescriptor`, `HTMLButtonElement`, `XYZValuesArray`, `OpenYoloError`, `ResizableTest`, `ExecaChildProcess`, `IApiSnapshot`, `ReductionFn`, `SentimentValue`, `ComponentRuntimeMembers`, `IVirtualDeviceConfiguration`, `IEditorTracker`, `DynamicFlatNode`, `ToastProps`, `ScreepsReturnCode`, `MirroringHost`, `IToken`, `RenderedSpan`, `RuntimeFn`, `PeriodInfo`, `TagComponent`, `PluginVersionsClient`, `Axial`, `PathParamOptions`, `IReportingRule`, `PointTuple`, `CUUID`, `YACCDocument`, `TupletType`, `IAnimal`, `ResolvedConfigFilePath`, `BackgroundAnalysisBase`, `PreflightCheckNamespacesResult`, `FiddleSourceControl`, `ITerminalChunk`, `IBaseNode`, `UserApp`, `TableRefContext`, `MigrationFeedback`, `chrome.tabs.TabActiveInfo`, `AngularEditor`, `CSVDataset`, `CoinbasePayload`, `StoreGroup`, `VideoSettings`, `FlowType`, `BuildResult`, `MethodDecorator`, `Unpacked`, `HostConfig`, `ReduxRootState`, `AppInsightsQueryResultTable`, `ApplicativeHKT`, `IUnitProfile`, `TableAccessByRowIdStep`, `KeyID`, `TransportMessage`, `RSS3List`, `sdk.Conversation`, `WebsiteScanResult`, `Arity2`, `CubicBezier`, `GestureType`, `LineSeriesStyle`, `SourceFileNode`, `AutorestConfiguration`, `ChapterData`, `AimEvent`, `ClientTag`, `CameraGameState`, `EnumDictionary`, `ExampleMetadata`, `puppeteer.Page`, `LambdaAction`, `GaugeAction`, `Fermata`, `ClientBuilder`, `GrammaticalGender`, `PickerColumnOption`, `TodoList`, `InlineField`, `TransactionEventArgs`, `ICXGenericResult`, `BareFetcher`, `ScopedSlotReturnValue`, `ApplicationListener`, `MockXMLHttpRequest`, `ServerHelloDone`, `EqualsGreaterThanToken`, `StatePages`, `QueryInput`, `ActionFunctionAny`, `OrganizationsClient`, `NodeClient`, `ActionHandlerContext`, `SVGVNodeAttrs`, `HubIModel`, `builder.Session`, `WebGLUniformLocation`, `BlobTestServerFactory`, `SequenceNode`, `ERC20`, `FrameNote`, `CreateEventSubscriptionResult`, `UICollectionViewDataSourceImpl`, `WebGLEngine`, `MyService`, `VerifiedToken`, `MixerCommunicator`, `NSRange`, `backend_util.Conv2DInfo`, `Web3ProviderEngine`, `TableRecord`, `p5ex.SpriteArray`, `CarouselProperties`, `FunctionTypeNode`, `ImageCacheItem`, `TelemetryService`, `EventDef`, `LegacyWalletRecord`, `IfStatement`, `Color3`, `NgrxJsonApiStoreQueries`, `choices`, `RestConfigurationMethod`, `KeyInput`, `DAOcreatorState`, `Thought`, `CohortPatient`, `CarImage`, `PouchDB.Database`, `IJsonRPCError`, `NetworkEdge`, `ProdutoDTO`, `GestureDetail`, `Observations`, `ChipService`, `YT.SuggestedVideoQuality`, `ITestResult`, `ListTournamentsRequest`, `MultipleInterfaceDeclaration`, `IScopeData`, `FIRUser`, `KeyboardManager`, `HStackProps`, `IRgb`, `ListApmDomainsRequest`, `ElementDataset`, `VirtualEditor`, `a.Type`, `jest.Mock`, `SlmPolicy`, `DocHandler`, `RankedTester`, `VectorEntry`, `BaseProvider`, `AbstractCommandDescriptor`, `WNodeFactory`, `FullFilePath`, `WholeStoreState`, `THREE.BufferAttribute`, `ListFriendsRequest`, `LexerResult`, `FirebaseServiceNamespace`, `WrapConfig`, `ITargetFilter`, `ICallsGetByContactState`, `ContractInterfaces.Market`, `ICalDateTimeValue`, `SystemData`, `SampleDataType`, `CharacterStore`, `ITimelineGroup`, `Obj`, `QuestionType`, `IpcSender`, `EnhancedTestStore`, `GetAttendeeCommandInput`, `esbuild.BuildResult`, `NonThreadGuildBasedChannel`, `Owner`, `CannedMarket`, `DescribeBackupsCommandInput`, `SimpleLogger`, `LangiumServices`, `EllipticCurves`, `MockContainerRuntimeForReconnection`, `SmartBuffer`, `IAnimation`, `IValidatorOptions`, `TestApi`, `ComponentTemplateDeserialized`, `DialogContextOptions`, `StreamService`, `xlsx.CellObject`, `RcModuleV2`, `ConeSide`, `FlashSession`, `EDerivativeQuality`, `SerializedSlot`, `FilterConstructor`, `BLAKE2s`, `MessageEvent`, `ODataStructuredTypeFieldParser`, `Nature`, `ClaimantInfo`, `ImporterRegistry`, `EntityInterface`, `ArtworkData`, `Engine`, `Definitions`, `LogSplitLayout`, `TypeESMapping`, `PlayerService`, `LockStepVersionPolicy`, `Free`, `EVMParamValues`, `SideMenuState`, `MDCSemanticColorScheme`, `UpdateConfigurationSetEventDestinationCommandInput`, `Accumulator`, `AppFilters`, `ListCtor`, `RaceCancellation`, `ProjectImage`, `SyncedRef`, `AccountsServer`, `GitDiff`, `Implementation`, `ObjectLiteral`, `ElementRef`, `TargetedMouseEvent`, `SigningKey`, `Kubeconfig`, `StatsTable`, `SFTPWrapper`, `CommandClassOptions`, `MapAnchors`, `RouterData`, `MockWrapper`, `GX_VtxAttrFmt`, `EvalParam`, `TreeProps`, `MarkdownSection`, `PolySynth`, `ITabInternal`, `IFS`, `ListUsersCommandOutput`, `Leaf`, `ErrorFn`, `SqrlExecutable`, `CohortService`, `FileTransportInstance`, `ToastState`, `EscapedPath`, `ExcerptToken`, `Middleware`, `PlacementStrategy`, `ControlPointView`, `GridApi`, `CircuitGroup`, `Parse.User`, `Softmax`, `PopupUtilsService`, `DurationUnit`, `AccountModel`, `Area`, `NameAndContent`, `AddTagsToResourceCommandOutput`, `BufferTypeValues`, `d.DevClientConfig`, `StoredReference`, `WebSiteManagementModels.FunctionEnvelope`, `com.github.triniwiz.canvas.ImageAsset.Callback`, `LoggerTask`, `NumberFilter`, `TableEntry`, `LeaderboardEntry`, `IAddAccountState`, `NodeMaterialBlock`, `InitiatingTranslation`, `ContractDeployOptions`, `ThresholdCreateSchema`, `TimeGranularity`, `IRawDiff`, `ResponseEnvelope`, `NgrxFormControlId`, `NumberFormat.UInt32LE`, `ThyDragStartEvent`, `CoinPrimitive`, `OnPreResponseInfo`, `PolkadotConnection`, `GLTF2.GLTF`, `NumberRenderer`, `Environment_t`, `requests.ListPingMonitorsRequest`, `APIGatewayProxyResult`, `InternalVariation`, `BurnerPluginContext`, `Main.LogScope`, `PostfixUnaryOperator`, `Dev`, `KillRing`, `IUniform`, `Express.Response`, `ConfigConfig`, `CharacterInfo`, `VisualProperties`, `ThyGuider`, `CommandBus`, `IType`, `MinMax`, `OF.IDropdownOption`, `GeocodeQueryInterface`, `ResolveImportResult`, `DSVRowString`, `TronTransactionInfo`, `RetryLink`, `ProviderEventType`, `TransformParams`, `DOption`, `Toggle.Props`, `AutorestSyncLogger`, `ITxRecord`, `resourceI`, `SuggestMatch`, `CommonDivProps`, `HttpPayloadTraitsWithMediaTypeCommandInput`, `PresetOptions`, `OptionalCV`, `ConfigInterface`, `models.ArtifactItem`, `Windup`, `APIResource`, `CLM.AppDefinition`, `RRdomTreeNode`, `SmdDataRowModel`, `Vec2Term`, `UserEvent`, `PreviewSize`, `requests.ListObjectsRequest`, `NotifyFn`, `RestRequestOptions`, `FilterType`, `PoolInfo`, `RecognizerResult`, `NAVObjectAction`, `Release`, `ESMessage`, `CipherData`, `SourceDetails`, `CellKey`, `IListViewCommandSetListViewUpdatedParameters`, `TDeleteManyInput`, `PackageAccess`, `JSChildNode`, `ChainInfoInner`, `MarketCurrency`, `RouterExtensions`, `ILocationResolver`, `UrlGeneratorId`, `PostMessageStorage`, `District`, `LineSeries`, `DeleteSettingCommand`, `observable.EventData`, `TableBuilderComponent`, `SharedFunctionsParser`, `CompletionEntry`, `MaterialInstanceConfig`, `MIRStatmentGuard`, `tf.io.ModelArtifacts`, `Endian`, `UnsupportedTypeLog`, `PreActor`, `UnionShape`, `ComposedChartTickProps`, `StyledProps`, `Legend.Item`, `ng.IModule`, `StorableUrl`, `SeriesOptions`, `LoginResultModel`, `MDCContainerScheme`, `DebugNode`, `ListQueuesRequest`, `MapNode`, `IDropboxEntry`, `ComparisonNode`, `Browser`, `AudioInputDevice`, `UserApollo`, `AudioStreamFormat`, `BufferSource`, `CommonService`, `PartsModel`, `SemanticTokens`, `AccessorComponentType`, `StackCardInterpolationProps`, `theia.DocumentSelector`, `WorkRequestError`, `IDatasource`, `Status`, `MongoCallback`, `CLM.LogDialog`, `Repeater`, `IDiffStatus`, `DevError`, `ArrayPromise`, `IOperandPair`, `Arbitrary`, `UserDetailsQuery`, `ModuleSymbolMap`, `ArmFunctionDescriptor`, `AccessorNames`, `GitStore`, `memory`, `SocketHandler`, `GetIPSetCommandInput`, `d3.Selection`, `SeparatorAxisTest2D`, `RangeDataType`, `GlobalStore`, `DAL.KEY_COMMA`, `BrowseProductsFacade`, `MaterialRenderContext`, `OrderJSON`, `IMiddlewareEvent`, `ILoginResult`, `PostItem`, `IDocString`, `WishlistsDetailsPage`, `ActionSheetButton`, `ForceLightningLwcStartExecutor`, `HardhatUserConfig`, `LocalVideoStream`, `ValueTransformer`, `InspectorLogEntry`, `PatchObjectMetadata`, `CacheHandler`, `ChatPlugin`, `SimpleExpressionNode`, `StringFilterFunction`, `AnySchema`, `FlightType`, `XYBrushEvent`, `ElementProfile`, `DeployOrganizationStep`, `TokenInfo`, `DeflateWorker`, `TaskManager`, `ModuleSpec`, `FrameInfo`, `ITokenClaims`, `StaticBuildOptions`, `DashboardCollectorData`, `OptionsConfig`, `Tolerance`, `MatchExplanationTreeNode`, `MicrophoneIterator`, `TextBlock`, `SessionStorageSinks`, `FrameNavigation`, `TelemetryReporter`, `InvalidParameterException`, `egret.Point`, `MlRoute`, `MatrixMessageProcessor`, `ModuleContext`, `PutMessagesResultEntry`, `Lunar`, `AxeCoreResults`, `CompletedPayload`, `DisabledRequest`, `StreamData`, `HomePage`, `FeaturePrivilegeAlertingBuilder`, `Readable`, `IAlertProps`, `SupCore.Data.Entries`, `GQLResolver`, `TIntermediate1`, `SortedSetItem`, `DatasourceRef`, `DirectionDOMRenderer`, `DisplacementFeature`, `MarkdownContentService`, `QueryChannelRangeMessage`, `IPeacockSettings`, `ParamMap`, `FilterValueExpressionOrList`, `DotIdentifierContext`, `ViewportCoords`, `ChangesetIndex`, `MapConstructor`, `UiSyncEventArgs`, `ProviderRegistry`, `ISODateTime`, `OasRef`, `AppData`, `Wizard`, `DeleteOptions`, `PutObjectOptions`, `ParingTable`, `Monad3`, `Point2d`, `Shard`, `Groupby`, `KdfType`, `ActiveProps`, `DamageType`, `CommonMiddlewareUnion`, `InviteService`, `Scalar`, `IViewProps`, `FeedbackRecord`, `AnyValidateFunction`, `SdkDataMessageFrame`, `RarePack`, `IAttentionSeekerAnimationOptions`, `SessionTypes.Settled`, `IDocumentServiceFactory`, `RedPepperService`, `ServerDevice`, `SNSEvent`, `TelegramClient`, `ClaimingSolution`, `AllActions`, `QueryPointer`, `AnalysisContext`, `CalculateHistogramIntervalParams`, `PluginWriteAction`, `TestingLogger`, `LogAnalyticsSourcePattern`, `OffsetConnectionType`, `ng.IAngularEvent`, `GX.CompType`, `Record.Update`, `vsc.Uri`, `MatOption`, `MenuStateBuilder`, `SnippetVisibility`, `MapSavedObjectAttributes`, `RecordPatternItem`, `GraphSnapshot`, `RandomNormalArgs`, `FontSize`, `ZoneWindowResizeSettings`, `SingleRepositoryStatisticsState`, `api.IZoweTree`, `PlaceEntity`, `NotificationActions`, `Hmi`, `RSSFeed`, `AbstractTransUnit`, `AnyStandaloneContext`, `IHandlerAdapter`, `DocumentClassList`, `FogBlock`, `StateForStyles`, `ILoginOptions`, `actionTypes`, `ITerm`, `AlertExecutionStatus`, `CodeFixAction`, `TValPointer`, `FnN4`, `Voyager`, `VIdentifier`, `AssociationConfig`, `TestContractAPI`, `Intervaler`, `SuperTest.SuperTest`, `InputBoxOptions`, `APITweet`, `JsxOpeningElement`, `BundleManifest`, `RouterContext`, `TestUseCase`, `Fixed8`, `ConnectResponseAction`, `PlayerData`, `GADBannerView`, `DescribeCommunicationsCommandInput`, `TVLAnalysis`, `DbRefBuilder`, `UrlResolver`, `ConstructDataType`, `AzureFunction`, `RowViewRef`, `TopicChangedListener`, `TEBopType`, `FormConnectionString`, `TDynamicObj`, `InternalCorePreboot`, `OperatorOption`, `ReadReceiptReceivedEvent`, `BatchGetItemInput`, `FakeInput`, `RediagramGlobalConfig`, `TObject`, `SlateEditor`, `BindingTemplate`, `GitHubUser`, `DescribeLoggingOptionsCommandInput`, `ObjMap`, `OutputAdapter`, `Outside`, `StableToken`, `OutputBinaryStream`, `CombinedState`, `ContractOptions`, `IBlockchainEvent`, `TrialVisitConstraint`, `FileStatus`, `IOrder`, `NotificationChannelServiceClient`, `IWindow`, `TransformingNetworkClient`, `StringSchema`, `CheckableElement`, `HomeAssistantMock`, `UniversalAliasTable`, `SurveyForDesigner`, `optionsType`, `MySpacesComponent`, `MemberId`, `IList`, `CanvasTypeProperties`, `UntagResourceResponse`, `RnPromise`, `PathCandidate`, `Change`, `CollectionOptions`, `pw.Page`, `ChatNodeVM`, `IncomingDefault`, `FieldUpdate`, `TeamProps`, `PRNG`, `RouteChildrenProps`, `ListDomainsRequest`, `SempreResult`, `MainDate`, `SqrlTest`, `RedirectUri`, `pageOptions`, `UInt128`, `QueryBuilder`, `DataStoreService`, `InteractivityChecker`, `ExtProfile`, `APEv2Parser`, `MetricSourceIntegration`, `OpenAPIV2.Document`, `CampaignItemType`, `AttributeContainer`, `ChannelSigner`, `DefaultEditorAggSelectProps`, `EditorFromTextArea`, `IRouterSlot`, `ProtocolVersionFile`, `SlaverListener`, `TPagedParams`, `ConfigProps`, `Events.postkill`, `MapStateToProps`, `ApplyPendingMaintenanceActionCommandInput`, `CursorEvents`, `Constraints`, `FavoritesState`, `UpdateInfoJSON`, `MockValidatorsInstance`, `PublicPolynomial`, `ActionsConfigurationUtilities`, `SurveyResultMongoRepository`, `ThemeValue`, `UnitWithSymbols`, `ILeague`, `ICardInfo`, `ContributionProvider`, `AssertionResult`, `TimerType`, `TabularCallback`, `TPLTextureHolder`, `GetTagsCommandInput`, `SvgIconConfig`, `MediaDef`, `YAxis`, `PromptResult`, `JSONSchemaSourceData`, `ts.HeritageClause`, `MessageWithReplies`, `vec3`, `ListFunctionsRequest`, `DAL.DEVICE_ID_SERIAL`, `JobResult`, `android.animation.Animator`, `IUpworkClientSecretPair`, `TaskDetails`, `UserFunction`, `WidgetTracker`, `TextDecoration`, `ParsedUrlQueryInput`, `DocusaurusContext`, `SerumMarket`, `Portion`, `SchemaConfig`, `ServiceNameFormatter`, `GetServersCommandInput`, `ListClient`, `RouteShorthandOptions`, `Miscellaneous`, `DragLayerMonitor`, `IndexedXYZCollection`, `Out`, `QueryIdempotencyTokenAutoFillCommandInput`, `StandardTableColumnProps`, `ExceptionIndex`, `Reward`, `ISubWorkflow`, `TSESLint.Scope.Reference`, `ThingProto`, `SignedOperation`, `ILoggerModel`, `CreateElement`, `MagickColor`, `UserSummary`, `FormGroupControls`, `SourceFileContext`, `LngLat`, `IssueAnnotationData`, `Arrayish`, `ITest`, `CallAgentProviderProps`, `GenericBreakpoint`, `SfdxTestGroupNode`, `FooValueObject`, `PagerDutyActionTypeExecutorOptions`, `messages.Attachment`, `GraphQLTypeInformer`, `AggParamEditorProps`, `IStateTypes`, `StatefulLogEvent`, `TextTexture`, `CheckupConfig`, `CheckboxFilter`, `Mesh_t`, `d.OutputTargetAngular`, `PostsContextData`, `google.maps.GeocoderResult`, `RootPackageInfo`, `DateFormatter`, `Encoding.Encoding`, `IReserveApiModel`, `AuthDataService`, `TextEditorConfiguration`, `AttrState`, `OpeningHours`, `BroadcastTxResponse`, `ClientSocketPacket`, `PartialOptions`, `ConformancePatternRule`, `ListConnectionsResponse`, `AccessKeyId`, `ReactionId`, `PgdbDataSource`, `EditMediaDto`, `ActionTypeModel`, `TextBuffer.Point`, `FungibleTokenDetailed`, `ISearchSetup`, `ValidatorConfig`, `ApiCredentials`, `SchemaComposer`, `STRowSource`, `PerformanceEntryList`, `BencheeSuite`, `TransitionConditionalProperties`, `IPropertyPaneConfiguration`, `DataImportRootStore`, `ObjectContent`, `Mars.AddressLike`, `DescribeInstancesCommandInput`, `IMinemeldStatusService`, `ISampler3DTerm`, `DropoutLayerArgs`, `ApplicateOptions`, `DataLayer`, `ExpressionsStart`, `ProgressBarEvent`, `EventMutation`, `Cancelable`, `OpenCLBuffer`, `ExtensionSettings`, `IViewport`, `UInt64`, `ApplicationLoadBalancer`, `MerkleIntervalInclusionProof`, `EntityDTO`, `ContractTransaction`, `CommandConstructorContract`, `Cypress.Actions`, `PlanetData`, `firebase.Promise`, `ParquetCompression`, `CanvasSpaceNumbers`, `LegendOrientation`, `EyeGazeEvent`, `NNode`, `DebugSystem`, `ScaleValue`, `DefaultRenderingPipeline`, `Oas3`, `IScripts`, `RecentDatum`, `_ts.Node`, `ICassClusterModuleState`, `IVar`, `tensorflow.IGraphDef`, `TargetConfiguration`, `YearToDateProgressConfigModel`, `DynamicFormLayoutService`, `ComponentArgTypes`, `ListColumn`, `ColumnDefinitionBuilder`, `WakuMessage`, `Config.GlobalConfig`, `PageHelpers`, `IPSet`, `Triangle`, `AssessmentType`, `DomApi`, `Hasher`, `SpectrumElement`, `BuildAnnotation`, `MatrixUser`, `VideoInfo`, `ASTConverter`, `SentimentAspect`, `FileSystemCommandContext`, `ParserContext`, `StorageObjectAcks`, `HealthPolledAction`, `BaseHub`, `Accord`, `JobStatus`, `UserPreferences`, `MediationState`, `CommonOptions`, `MapImage`, `SharedConfig`, `KibanaExecutionContext`, `CmsContext`, `ScaledSize`, `PropEnhancers`, `NetworkBuilder`, `ChemicalState`, `EngineArgs.ListMigrationDirectoriesInput`, `IMonitorPanelAction`, `EvActivityCallUI`, `NumberLike`, `requests.ListWorkRequestLogsRequest`, `StackHeaderProps`, `PropertyAnimation`, `NetworkConfig`, `GeometryKind`, `IVertoCallOptions`, `StarPieceHostInfo`, `FaunaPaginateOptions`, `Vars`, `React.DragEvent`, `Eth`, `WebhookProps`, `SearchEmbeddableConfig`, `TwingTemplate`, `PolymorphicPropsWithoutRef`, `EntityObject`, `Answers`, `GetResult`, `DriverException`, `CreateUser`, `ToolbarButton`, `SubscriptionField`, `reflect.TypeReference`, `InsightShortId`, `MapDispatchToProps`, `IResultSetRowKey`, `HalfEdgeGraph`, `InstanceClient`, `TestabilityRegistry`, `ObjectNode`, `SwapInfo`, `DeviceConnection`, `TEBinOp`, `ServiceManager`, `ViewMetaData`, `OscillatorNode`, `LayerObjInfoCallback`, `JHistory`, `OperationBatcher`, `FrameGraphicsItem`, `DateIntervalDescriptor`, `ContentChangedCallbackOption`, `BufferLine`, `IColorModeContextProps`, `OverrideOptions`, `ActionToRequestMapper`, `ModelObj`, `RowLevel`, `MiniMap`, `ReadableStreamController`, `MsgAndExtras`, `EngineResults.DevDiagnosticOutput`, `ChainedIterator`, `DAL.DEVICE_ID_GESTURE`, `DryPackage`, `RedisConnectionManager`, `GaussianDropout`, `TheiaDockPanel`, `EthereumEvent`, `StripePaymentMethod`, `TreeChanges`, `IGhcModProvider`, `AMock`, `RouteProp`, `AppStatusChangeFaker`, `CalendarRange`, `MoveData`, `InsertOneResult`, `AlbumListItemType`, `GrowableXYZArray`, `MemoryDump`, `AC`, `TagKey`, `NewSyntax`, `MonitoredHealth`, `NFT1155V3`, `LineChartLineMesh`, `Libraries`, `QueueData`, `EntityKey`, `CommentRange`, `requests.ListDhcpOptionsRequest`, `Pully`, `DataConfig`, `WsViewstateService`, `ElementDefinition`, `Of`, `AutocompleteProvider`, `VaultAdapterMock`, `SavedObjectsServiceStart`, `DataDown`, `PrefFilterRule`, `Knex.Transaction`, `NaviRequest`, `AutoRest`, `binding_grammarVisitor`, `EventPublisher`, `VirtualFilesystem`, `SetupModeProps`, `ArtifactItem`, `StynPlugin`, `MarkConfig`, `ExtendedAppMainProcess`, `Reader`, `MalRequest`, `ApolloServerExpressConfig`, `VSnipContext`, `GetResponse`, `TreemapSeries.ListOfParentsObject`, `MultiPolygon`, `IcalEventsConfig`, `FileEditorSpec`, `ImageSourcePropType`, `OsmObject`, `DeployStageExecutionStep`, `IUiStateSlice`, `ComponentFixture`, `FilterFunction`, `ShortcutEventOutput`, `ZoomOptions`, `VisTypeTimeseriesVisDataRequest`, `TransitionDefinition`, `VisualizationConfig`, `ChannelState`, `S3Control`, `Computed`, `SwitchOptions`, `ImageInspectInfo`, `PhrasesFilter`, `CronService`, `WeaponMaterial`, `git.ICreateBlobParams`, `ArweavePathManifest`, `androidx.appcompat.app.AppCompatActivity`, `DoorLockCCOperationReport`, `SupervisionResult`, `VisualizationsSetupDeps`, `SavedObjectsPublicPlugin`, `SeriesOption`, `Scope`, `TouchGestureEventData`, `HintMetadata`, `TestBed`, `JointConfig`, `TableOffsetMap`, `THREE.Euler`, `GenerateClientOptions`, `HomePageProps`, `TypeName`, `TypeCacheEntry`, `SingleEmitter`, `ReindexState`, `FunctionImportRequestBuilder`, `SavedObjectsImportOptions`, `SwitchAst`, `LoginOptions`, `Resources`, `IDBTransactionMode`, `TensorLike2D`, `RTCRtpParameters`, `ChartParams`, `Types.TooltipCfg`, `UserStakingData`, `TransferType`, `ConstrainDOMString`, `HomeReduerState`, `AlainI18NService`, `EditorCompletionState`, `PlanPreviewPanel`, `IdentityNameValidityError`, `AddMessage`, `RecommendationLevel`, `Partition`, `SubscriberType`, `ItemTable`, `DecoratorDefArg`, `MOscMod`, `AddonEnvironment`, `DispatchWithoutAction`, `DebtKernelContract`, `IController.IParameter`, `DriverModel`, `Matrix22`, `SheetRef`, `URLParse`, `GiphyService`, `SVGLabel`, `StreamModel`, `ExceptionsBuilderExceptionItem`, `WindiPluginUtils`, `TerraNetwork`, `GraphQLFieldMap`, `GetItemOutput`, `ImageViewerProps`, `ProjectInfo`, `ConfigSet`, `FunctionProp`, `WeaponData`, `ForgotPasswordVerifyAccountsRequestMessage`, `UserID`, `Snap`, `Web3ReactContextInterface`, `IFilterListGroup`, `ActionWithError`, `IBalance`, `ListInstancesCommandInput`, `AggConfigOptions`, `BillId`, `GameSettings`, `MediaFileId`, `ICredentialsDb`, `CallArguments`, `StatusFollow`, `sdk.TranslationRecognitionEventArgs`, `FrameType`, `EngineEventType`, `FormWindow`, `loader.Loader`, `CreateConfigurationCommandInput`, `GeoBoundingBoxFilter`, `DataSharingService`, `GameInput`, `Pile`, `FadeSession`, `RawNodeData`, `PresentationRpcRequestOptions`, `InternalHttpServiceSetup`, `PropParam`, `LinkedAccount`, `AxisDimension`, `ILiquorTreeNode`, `IGradGraphs`, `CSSProperties`, `LuaDebugVarInfo`, `ChampList`, `StorageRecord`, `Aser`, `BufferConstructor`, `ProjectMeta`, `DescribeTagsCommand`, `SelectorT`, `EvaluateOperator`, `env`, `HTMLPreElement`, `RegisteredTopNavMenuData`, `OperationQueryParameter`, `MatchDoc`, `ConflictResolution`, `ConverterDiagnostic`, `SoundConfig`, `CompanyType`, `MetadataSelector`, `Dump`, `vscode.TextDocument`, `DatabaseOptions`, `CreateDBClusterParameterGroupCommandInput`, `RequestorBuilder`, `ShoppingCartStore`, `IDependenciesSection`, `PbSecurityPermission`, `IServerSideDatasource`, `WFunction`, `FeedbackId`, `QueryMiddleware`, `DocumentMetadata`, `MaxNormArgs`, `GlobalInstructionData`, `AppletIconStyles`, `SandDance.specs.Insight`, `AuthorModel`, `GetEmailTemplateCommandInput`, `UpdateFlowCommandInput`, `CreateSubnetGroupCommandInput`, `CircuitInfo`, `ENGINE`, `Events.enterviewport`, `CachedImportResults`, `Git`, `PluginDependencies`, `FileSpec`, `TimingSegmentName`, `ISavedObjectsPointInTimeFinder`, `LoaderBundleOutput`, `ScreenTestViewport`, `AdvancedFilter`, `DeleteChannelMessageCommandInput`, `IBox`, `requests.ListComputeGlobalImageCapabilitySchemaVersionsRequest`, `TDiscord.GuildMember`, `ForgeModAnnotationData`, `ChildAttributesItem`, `DBUser`, `RefreshAccessTokenAccountsValidationResult`, `BreadCrumb`, `URL`, `ISequencedDocumentMessage`, `Eventual`, `GraphQLHandler`, `DeleteDatasetRequest`, `Curve`, `IPackage`, `InterfaceTemplate`, `OptionKind`, `NeverShape`, `KeyResultUpdateService`, `IMineMeldAPIService`, `MockProject`, `FileHandlerAPIs`, `HsUtilsService`, `TestRouter`, `MediaTrackSupportedConstraints`, `MLKitRecognizeTextResult`, `AxisBuilder`, `TState`, `GreetingStruct`, `EdmTypeShared`, `TreeFile`, `Theme`, `Variants`, `SpriteFont`, `IndigoOptions`, `IWriteOptions`, `AppStateSelectedCells`, `TRPGAction`, `ContainerContext`, `ColorValue`, `NinjaPriceInfo`, `AgentConnection`, `WordCharacterClassifier`, `Decider`, `VoidFunctionComponent`, `enet.IDecodePackage`, `BlockReference`, `S.Stream`, `RouteRule`, `IButtonStyles`, `SessionUserAgent`, `InheritedChildInput`, `mmLooseObject`, `ModelEvaluateDatasetArgs`, `CtrBroad`, `SignedMessage`, `MessageServiceInterface`, `INodeContainerInfo`, `MockFluidDataStoreRuntime`, `ComboFilterSettings`, `NumericOperand`, `Sql`, `MigrationSubject`, `CompositeTreeNode`, `FlexElementProps`, `PDFRadioGroup`, `MetricName`, `DraggableEvent`, `TypographyDefinition`, `InspectReport`, `RetryAction`, `HashSet`, `WebpackRule`, `ChakraComponent`, `LiteralMap`, `RequestPolicyFactory`, `ReadAddrFn`, `SendDataMessage`, `IMarkdownDocument`, `Batcher`, `IObject3d`, `AttendanceDay`, `IExpression`, `NockDefinition`, `MenuItem`, `ts.ModuleResolutionHost`, `ContactInterface`, `SiteSourceControl`, `ITestPlan`, `app.FileService`, `ICellStructure`, `IHasher`, `GraphQLParams`, `Buildkite`, `IsNumber`, `ISampleSizeBox`, `lspCommon.WorkspaceType`, `FsTreeNode`, `Generic`, `globalThis.MouseEvent`, `DepositKeyInterface`, `DescribeExecutionCommandInput`, `sinon.SinonStubbedInstance`, `DescribeSubnetGroupsCommandInput`, `ApiJob`, `SubscribeEvents`, `IDockerComposeResult`, `PostMessageStub`, `MultilevelSwitchCCReport`, `LogLevel`, `IHydrator`, `MEPChromosome`, `RegisteredClient`, `ContentRepository`, `MacroBuffer`, `ResourcePage`, `apid.ProgramId`, `PrimitiveArg`, `CIMap`, `ViewRect`, `UInt128Array`, `AuthenticationService`, `OpenSearchQueryConfig`, `$FixMe`, `ProcessAccountsFunc`, `HDKeychain`, `EventsTableRowItem`, `Referral`, `VisorSubscription`, `MapPool`, `ITableProps`, `SeriesSpecs`, `ShadowGenerator`, `MapperService`, `SessionCsrfService`, `DateObject`, `EmailConfig`, `ExtraDataTypeManager`, `PartyMatchmakerAdd_StringPropertiesEntry`, `AccountBase`, `NodeParserOption`, `CC`, `ImageResolvedAssetSource`, `LiveAnnouncerDefaultOptions`, `MathfieldPrivate`, `DQLSyntaxErrorExpected`, `StacksNetwork`, `ObjectFetcher`, `Panner`, `Pkg`, `ErrorBarSelector`, `ExecutionResult`, `MockBaseService`, `BMD`, `d.OptimizeJsInput`, `OrderType`, `CustomAnimateProps`, `ScopeContext`, `Compatible`, `DevServerEditor`, `ScopeQuickPickItem`, `ViewFunctionConfig`, `StopExperimentCommandInput`, `GradientObject`, `RegisterDr`, `Distance`, `DisplayableState`, `TodoController`, `TaskChecklistItem`, `InternalKeyComparator`, `JumpFloodOutput`, `VarianceScalingArgs`, `ISizeCalculationResult`, `StringLiteral`, `CopyDirection`, `ImageInfo`, `tmp.DirResult`, `UnionC`, `APropInterface`, `OrganizationContext`, `FieldContextValue`, `StackHeaderInterpolatedStyle`, `UserDataContextAPI`, `ListTagsCommand`, `ComplexArray`, `BucketHandler`, `ScrollState`, `IQueryParamsConfig`, `GitHubActionWorkflowRequestContent`, `t.Node`, `DataStreamInfo`, `Switch`, `IDerivation`, `DateRangeMatch`, `ChildSchoolRelation`, `P5`, `IndexStats`, `FileStats`, `SymbolDefinition`, `CellValueChangedEvent`, `UpdateUserInput`, `RenderSchedule.ScriptProps`, `MochaOptions`, `IApolloContext`, `StyleRecord`, `SelectableListService`, `supertest.SuperTest`, `BinaryHeap`, `InterfaceWithConstructSignatureReturn`, `VideoLayer`, `IEcsDockerImage`, `BarEntry`, `Cloud`, `ReduxState`, `IValueChanged`, `NormalizedDiagnostic`, `TBook`, `SceneTreeTimer`, `ResponseMeta`, `ElUploadRequest`, `builders`, `DateTimeFormat`, `PartitionedFilters`, `ListUsersCommand`, `ErrorService`, `Disposable`, `DescribeDatasetImportJobCommandInput`, `CustomMapCache`, `SubstrateEvent`, `StreamFrame`, `TransitionPreset`, `ReadOnlyFunctionOptions`, `DirectThreadEntity`, `Mocha.Context`, `SFProps`, `ViewPropertyConfig`, `prettier.Options`, `TPath`, `UIEventSource`, `vscode.TextLine`, `SettingsProvider`, `DeviceTypeJson`, `ContactSubscriptions`, `DataObject`, `ListAlarmsRequest`, `CodepointType`, `ContextWithMedia`, `GraphQLEntityFields`, `TTag`, `FlexLine`, `GraphQLResolverContext`, `SitesFixesParserOptions`, `DecoratorNode`, `ts.UserPreferences`, `WrapExportedClass`, `CompleteResult`, `execa.ExecaChildProcess`, `ISuggestValue`, `PersistedSnapshot`, `WebDNNWebGLContext`, `TypeDef`, `CollisionObject2DSW`, `TransactionPayload`, `vscode.EndOfLine`, `SourceCodeInfo_Location`, `CliInfo`, `requests.ListWafLogsRequest`, `ICoverageFragment`, `ApiInterfaceRx`, `PersistAppState`, `AstNode`, `PLI`, `requests.ListCloudVmClusterUpdateHistoryEntriesRequest`, `InstancePrincipalsAuthenticationDetailsProvider`, `WorkRequestStatus`, `TreeEdge`, `VariableUiElement`, `BlockElement`, `ColumnProps`, `AppleTV`, `WXML.TapEvent`, `ListDomainNamesCommandInput`, `ITagProps`, `RTCIceTransport`, `Ad`, `ArticleStateTree`, `ClusterEvent`, `WorldgenRegistry`, `SyntaxDefinition`, `AnchorBank`, `GradleVersionInfo`, `TsSelectComponent`, `Victor`, `EmailTempState`, `IExtentChunk`, `ITrackEntry`, `ShaderVariable`, `WorkerProxy`, `PriceState`, `TranslatedValueID`, `IFileDescription`, `ImGui.Vec2`, `PythonPreviewConfiguration`, `d.CompilerBuildResults`, `EventDelegator`, `InstanceLocator`, `DatasourcePublicAPI`, `InferableComponentEnhancerWithProps`, `CreateDatabaseCommandInput`, `VoiceConnection`, `WrapOptions`, `IVoicemail`, `IRNGNormal`, `s.Field`, `PersonAssignmentData`, `AP`, `LazyMedia`, `LintResult`, `Bus`, `ConsolidateArgs`, `PlasmicConfig`, `CausalRepoIndex`, `NavigationIndicator`, `ClassMetadata`, `IAppStrings`, `DeleteDestinationCommandInput`, `SchemeRegistrarWrapper`, `PathItemObject`, `RecipientOrGroup`, `poller.IPollConfig`, `GherkinQuery`, `Multer`, `AddonClass`, `MaterialAccentColor`, `UrbitVisorConsumerExtension`, `Account`, `ComponentDecorator`, `BabelOptions`, `AuxUser`, `TabStyle`, `DeleteInstanceProfileCommandInput`, `BudgetResult`, `EmailConfirmationsStore`, `ScriptData`, `AccessTokenProvider`, `TinyQueue`, `VgApiService`, `DictionaryEntryNode`, `BlockNode`, `RTCIceGatherer`, `TldrawApp`, `Banner`, `MapBounds`, `CheckpointNode`, `Integer`, `Interfaces.IBroker`, `ConfigurationCCBulkSet`, `StyledOtherComponent`, `Others`, `RoomItem`, `MethodAst`, `DefaultTreeDocument`, `ContextMenuExampleProps`, `ChannelInflator`, `ComponentStrings`, `EndpointDefinition`, `UITabBarController`, `FullIndex`, `Preset`, `IAttr`, `CommonMiddleware`, `ApiMethod`, `NearSwapTransaction`, `InitParams`, `OpenSearchDashboardsDatatable`, `ZonedDateTime`, `IndexPatternRef`, `IDocumentFragment`, `GlobalEventName`, `PromptProps`, `CreateChannelBanCommandInput`, `ActorArgs`, `IResultSetElementKey`, `PredictionContext`, `GridBase`, `EffectFunction`, `GroupMembershipEntity`, `UtilObject`, `https.AgentOptions`, `SDK`, `ObjectDetails`, `_ISelection`, `Config.IConfigProvider`, `IConfigurationExtend`, `Widget.ChildMessage`, `IToastOptions`, `UserResult`, `TestingSystem`, `IBaseTabState`, `LoginForm`, `DebugStateAxes`, `EdmxEntityTypeV4`, `UInt256`, `SemanticRole`, `MessageDataFilled`, `ethOptionWithStat`, `Event1EventFilter`, `vscode.CompletionList`, `CommentState`, `ItemEntity`, `ResponseWrapper`, `MenuSurfaceBase`, `PIXI.Graphics`, `InMemoryLiveQueryStore`, `TLockfileObject`, `DeviceChangeObserver`, `JsSignatureProvider`, `ExcludedEdges`, `ListKeyVersionsRequest`, `StringLiteralExpr`, `Link`, `Events.pointercancel`, `MDCBottomSheetController`, `identity.IdentityClient`, `MemberDoc`, `FaktoryControl`, `HeadClient`, `IConversation`, `DiffedURIs`, `PublishOptions`, `theia.SemanticTokensLegend`, `AppServiceBot`, `ConnectedPeer`, `ChangeLanguage`, `LocalActions`, `V3SubgraphPool`, `IConnectionExecutionContextInfo`, `YAMLSchemaService`, `IInvoiceUpdateInput`, `CreateCard`, `PackagePolicyVars`, `IEpochOverview`, `AuxVM`, `IndexedPolyface`, `OutlineSharedMetricsPublisher`, `FurMulti`, `PrivateEndpoint`, `CollateralRequirement`, `IAppServiceWizardContext`, `SqliteValue`, `UnaryContext`, `TSExpr`, `Tags`, `MessagingDevicesResponse`, `Intermediate`, `ExtensionData`, `CodeGenerator`, `ImGui.DrawList`, `MyObject`, `RouterOutlet`, `requests.ListRouteTablesRequest`, `GenesisBlock`, `Accountability`, `FocusPath`, `BalanceActivityCallback`, `ChatMessageType`, `ErrorReporter`, `BigFloat32`, `SerializeCssOptions`, `RenderElement`, `VirtualContestProblem`, `SoftVis3dMesh`, `NumericType`, `MapState`, `GetGroupResponse`, `KernelConfig`, `InternalServerException`, `PackageService`, `Semaphore`, `VersionId`, `ListReleaseLabelsCommandInput`, `RowSchema`, `MapView`, `LanguageServiceHost`, `FakeHttpProvider`, `IDBCursorWithValue`, `TRWorld`, `ko.Subscription`, `CommitStatus`, `PageBlobClient`, `ArgType`, `ErrorReport`, `ThemeConfiguration`, `Issuer`, `IAngularScope`, `SceneDesc`, `StreamingStatus`, `ControlPoint`, `LLink`, `App.IPolicy`, `AlbumService`, `MXCurve`, `HttpMethod`, `RowProps`, `TradeExchangeMessage`, `HorizontalAlignment`, `JsonRpcId`, `GetRepository`, `KeyIndex`, `ElkLabel`, `GlyphCacheEntry`, `AlertOptions`, `FavoriteGroup`, `MonzoService`, `ConfigurationService`, `SQLeetEngine`, `QueryNodePath`, `VatLayout`, `ListTagsForResourceInput`, `InMemoryConfig`, `ValidateRuleOptions`, `BaseFactory`, `IRootReducer`, `EmployeeViewModel`, `WorkspaceProject`, `SFCScriptBlock`, `ReducerMap`, `IUIMethodParam`, `WrappedProperties`, `Chlorinator`, `IBuilder`, `DecoderFunction`, `CovidData`, `MaterialMap`, `Mocha.Test`, `AnyField`, `HookBase`, `DemoSettings`, `android.support.v7.widget.RecyclerView`, `NgbModal`, `SharedElementSceneData`, `NavigatorState`, `SnackbarContextInterface`, `Directus`, `IDifferences2`, `Op`, `TestTemplate`, `IContainer`, `WindowRect`, `AudioNode`, `JPABaseEmitter`, `Proof`, `UserManager`, `IWrappedEntity`, `UserMusicDifficultyStatus`, `MagickFormat`, `ZIlPayCore`, `VarUsages`, `ConnectedComponentClass`, `PanelsState`, `TheMovieDb`, `HttpErrorHandler`, `ComboFilter`, `TransactionsState`, `SlatePlugin`, `SerializableConstructor`, `StateProps`, `AxisProperties`, `__HttpResponse`, `IServiceConstructor`, `d.ComponentCompilerEvent`, `LocalStorageArea`, `DeploymentOptions`, `AppiumDriver`, `WordcloudViewModel`, `HarmajaOutput`, `OriginAccessIdentity`, `DeclarativeEnvironment`, `NumberListProps`, `SubtitlesCardBases`, `ItemStat`, `ExtraButtonComponent`, `SnackbarMessage`, `MaybeLazy`, `DynamoDB.UpdateItemInput`, `MediatorFactory`, `EmailVerificationToken`, `YallistNode`, `StaticCollider`, `RadarPoint`, `sdk.PullAudioInputStream`, `ImagePickerControllerDelegate`, `DeleteButtonProps`, `CloudWatch`, `SimpleExpression`, `Discord.Channel`, `Rank`, `NumberInputOptionProps`, `IDiagnosticsResults`, `FunctionAppContext`, `Zipper`, `UpdatableChannelDataStore`, `ILeaseState`, `IWaterfallTransaction`, `IExpectedArtifact`, `IExtentModel`, `lf.Predicate`, `ApiKey`, `ResponseInit`, `FlowBranchLabel`, `BundleModule`, `ListInstanceProfilesCommandInput`, `DefinitionFilter`, `THREE.WebGLRenderer`, `AgentQq`, `IRootPosition`, `ThemeOption`, `ExprDependencies`, `NamedDeclaration`, `CloudflareApi`, `FileRepositoryService`, `Pooling3DLayerArgs`, `BYOCLayer`, `CodeWriter`, `InternalUnitRuntimeContext`, `DeepImmutableObject`, `Resilience`, `KeyedSelectorFn`, `NavigationViewModel`, `ArchiveEntry`, `ListViewWrapper`, `SymbolSize`, `BezierCurve`, `CreateNetworkProfileCommandInput`, `anyNotSymbol`, `PowerShellScriptGenerator`, `DebugProtocol.Event`, `MessageMock`, `Decimal`, `ParameterDeclaration`, `SchemaMatchType`, `SavedObjectsIncrementCounterOptions`, `UUIDMetadataObject`, `ScriptThread`, `RegulationHistoryItem`, `DropInPresetBuilder`, `ValidateErrorEntity`, `ControlPanelState`, `Relationship`, `TaskContext`, `AxeResultsList`, `QueryEngineEvent`, `StartOptions`, `SvelteSnapshotManager`, `CharacterSetECI`, `TestClock`, `DeletePolicyVersionCommandInput`, `FileWithMetadata`, `TextTip`, `RBNFInst`, `AnimationKey`, `ComplexExpression`, `ValidationHandler`, `AthleteUpdateModel`, `RankingItem`, `ListProjectsCommand`, `MiddlewareCreator`, `CubeArea`, `StatusBar`, `SceneActuatorConfigurationCCGet`, `JPAResource`, `StyleSanitizeFn`, `ast.WhileNode`, `CaseBlock`, `PluginInitializerContext`, `SimulatedTransactionResponse`, `BuildMatch`, `StaffDetails`, `P2PMessagePacketBufferData`, `QuotaSettings`, `StrongExpectation`, `ParticipantsRemovedEvent`, `IndieDelegate`, `SavedObjectsClosePointInTimeOptions`, `d.CompilerSystem`, `ISdkBitrateFrame`, `FreeBalanceClass`, `DocProps`, `CardConfig`, `CreateRawTxOut`, `ElementPaint`, `DescribeImagesRequest`, `DomNode`, `TokenTransferPayload`, `d.ComponentCompilerStaticProperty`, `Knex`, `PDFFont`, `ArithmeticInput`, `Debugger`, `ReactEditor`, `EmberAnalysis`, `ShorthandRequestMatcher`, `PaginateResult`, `CommitOptions`, `HintManager`, `JestAssertionError`, `ParameterJoint`, `ObjectWithId`, `TabProps`, `FunctionTypeResult`, `LightBound`, `InterfaceWithEnumFromModule`, `IterationUse`, `EChartsOption`, `UnionOrIntersectionTypeNode`, `ExpressionAttributes`, `YamlMappingItem`, `CreateApiKeyCommandInput`, `LinesGeometry`, `OrgEntityPolicyOperations`, `UserEnvelope`, `MempoolTransaction`, `NgModuleType`, `requests.ListProtocolsRequest`, `HTMLIonModalElement`, `ReturnType`, `BeneficiaryDTO`, `FeatureFlagType`, `DependenceGroup`, `ZipOptions`, `ValidationFunction`, `SearchInput`, `AcceptCallbacks`, `d.Screenshot`, `ILineIndexWalker`, `StateObservable`, `QuerySnapshotCallback`, `ComponentPortal`, `LRUCache`, `CommentThread`, `WindowSize`, `CompressedJSON`, `IntegrationTypes`, `PlayerLadder`, `MessageExecutor`, `Robot`, `DlpServiceClient`, `ZoneManager`, `Red`, `Events.pointerenter`, `BlockFormatter`, `ErrnoException`, `ProfileProviderResponse`, `IndexedTrendResult`, `WalletDeploymentService`, `NonFungibleTokenAPI.Options`, `IJetURLChunk`, `NgIterable`, `RenderTarget_t`, `CircleBullet`, `InstructionWithTextAndHeader`, `ClassificationType`, `Buckets`, `ConflictException`, `DialogueTest`, `DataTable`, `Binary3x3x3Components`, `VdmEnumType`, `ElementAst`, `PartyJoinRequestList`, `TranslationFormat`, `SyncStatus`, `ICreateOptions`, `AddTagsToResourceMessage`, `cc.Event.EventKeyboard`, `GetRepositoryCommandInput`, `ZeroXPlaceTradeParams`, `InterfaceAlias`, `AliasName`, `StateNavigator`, `ValveState`, `PageSourceType`, `OAuthExtension`, `CartPage`, `CameraType`, `ButtonLabelIconProps`, `CalculationScenario`, `SFAMaterialBuilder`, `TokenStat`, `Pool.Options`, `RtcpPayloadSpecificFeedback`, `DisplayObject`, `ConfigurationPropertyDict`, `IResourceAnalysisResult`, `TooltipService`, `TItemsListWithActionsItem`, `LovelaceCardConfig`, `CallerIdentity`, `IOptimizelyAlphaBetaTest`, `ArrayLike`, `VFSEntry`, `ICompileService`, `ISubscriberJwt`, `AutoFilter`, `StampinoTemplate`, `SyncMember`, `ApprovalPolicyService`, `SmartHomeApp`, `ListFindingsRequest`, `Ink`, `IPayment`, `mendix.lib.MxObject`, `FormatterParam`, `JobTypes`, `ResolvedOptions`, `AccountSetOpts`, `VoiceChannel`, `SnapshotNode`, `AndroidConfig.Manifest.AndroidManifest`, `DefaultDataServiceConfig`, `WatchBranchEvent`, `PathOrFileDescriptor`, `CopySink`, `RuleMetadata`, `ReconciliationPath`, `AttributeDatabindingExpression`, `ApifySettings`, `SliderGLRenderer`, `LoggerOutput`, `CalcValue`, `DeploymentCenterFormData`, `GlobalTag`, `TemplateStringsArray`, `FoodRelation`, `SavedObjectDescriptor`, `FavoritePropertiesOrderInfo`, `PlanStep`, `Lead`, `ArrayRange`, `ApplicationEntry`, `VaultActive`, `IndexBuffer3D`, `ModelLayer`, `SpatialViewDefinitionProps`, `SourceLoc`, `EditorDescription`, `SessionsActions`, `WebLayer3DBase`, `TypedReflection`, `MultiKeyComparator`, `IAuthState`, `SchemaOverview`, `BaseService`, `EventsMessage`, `PiEditPropertyProjection`, `RequestContract`, `PendingAction`, `DelegatorReward`, `NoteService`, `ParameterOptions`, `ArrayBufferWalker`, `HeapInfo`, `NzMessageRef`, `AccountData`, `ValueSource`, `Serializer`, `ParticipantsJoinedListener`, `DynamicEntry`, `AirGapWallet`, `MangolLayer`, `IStaggerConfig`, `ISeed`, `HostCancellationToken`, `UrlGeneratorsStart`, `TileCoordinates`, `DeferredPromise`, `Client.ProposalResponse`, `ILoggerInstance`, `RootActionType`, `CoreUsageStats`, `GfxRenderPassDescriptor`, `IDomainEntry`, `GroupArraySort`, `Gatekeeper`, `ObjectList`, `TurndownService`, `FileDescription`, `ITreeData`, `VisContainerProps`, `BlogActions`, `ValidationOptions`, `ServiceIdentifier`, `CardsWrapper`, `PolyfaceVisitor`, `Conjugate`, `ContractWhiteList`, `Class`, `ProcessorInternal`, `IDynamicGrammarGeneric`, `SanityChecks`, `SpeakDelegate`, `IScore`, `FilesChange`, `PostsState`, `UsePaginatedQueryOptions`, `EVM`, `core.VirtualNetworkClient`, `ConstantArgs`, `ContactModel`, `LABEL_VISIBILITY`, `WetPlaceholder`, `IParseAttribute`, `FindByIdOptions`, `DeleteDistributionCommandInput`, `MBusTransaction`, `TableFormDateType`, `HammerLoader`, `Schema$Sheet`, `YawPitchRollAngles`, `SlashCommand`, `Express.NextFunction`, `TypeError`, `CrossConnectMapping`, `ProviderRpcError`, `T_0`, `JsonPath`, `RushConfiguration`, `GenericEvent`, `FiberNode`, `zmq.Pair`, `BlockchainTimeModel`, `TrackEventParams`, `GlobalSearchProviderResult`, `Eyeglasses`, `ColorPreviewProps`, `Fish`, `DiagnosticLevel`, `AssignedContentType`, `RowVM`, `CategoricalParameterRange`, `MethodDescriptorProto`, `HumidityControlMode`, `DefinitionRange`, `MagickReadSettings`, `GoalStatus`, `MaterialUiPickersDate`, `FB3ReaderPage.ReaderPage`, `AccessibilityOptions`, `EsErrors.ElasticsearchClientError`, `NextAuthOptions`, `MacroActionId`, `MailStatusDto`, `MdcSlider`, `Node_Enum`, `TestActionContext`, `TokenBucket`, `SkyBoxMaterial`, `ListTournamentRecordsAroundOwnerRequest`, `vscode.CompletionItemKind`, `CdkScrollable`, `DNSLabelCoder`, `SGDOptimizer`, `StringSet`, `ErrorEmbeddable`, `ObjectAssertionMember`, `IcuExpression`, `nsISupports`, `AutoCompleteEventData`, `ModalSize`, `NamedIdentityType`, `interfaces.Bind`, `ColumnDefinitions`, `EventNote`, `GameDataInterface`, `XMLElementOrXMLNode`, `ICloneableRepositoryListItem`, `CommandLine`, `SubscribeCommandInput`, `Polynomial`, `MultisigData`, `InputArgs`, `RequestTemplateReference`, `DurationInput`, `MangoClient`, `CameraRig`, `BooleanExpression`, `MarkdownTable`, `TemplateData`, `EnrichmentPipeline`, `DynamicCommandLineAction`, `ServiceDefinition`, `SwitchKeymapAction`, `CustomerContact`, `VisualEditor`, `EthAddress`, `AlertType`, `BindingAddress`, `HookFn`, `LinkProof`, `EventDestination`, `ITransformResult`, `RenderColorTexture`, `IBoxPlot`, `ColumnProp`, `AirlineService`, `FunctionField`, `SHA512`, `LevelUpChain`, `ButtonText`, `CurrencyMegaResult`, `ts.Decorator`, `WTCGLRenderingContext`, `SxSymbol`, `DelNode`, `SinonSpyCall`, `ActionType`, `ConfigurationManager`, `HSLVector`, `DiscordBot`, `CanvasKit`, `EditDashboardPage`, `SettingsValue`, `FreePoint`, `ManagementDashboardTileDetails`, `BackendError`, `BridgeConfig`, `TimeSeriesMetricDefinition`, `IVector4`, `HandshakeType`, `IVisualHost`, `FormInput`, `StackUtils`, `TypeReferenceSerializationKind`, `IHistorySettings`, `PlasmicLock`, `android.content.Context`, `FoodItem`, `IWorkflowBase`, `Escrow`, `Objects`, `ReleaseProps`, `vscUri.URI`, `Some`, `RootAction`, `ModalNavigationService`, `IAllTokenData`, `RenderTexture`, `FirebaseHostingSite`, `SharedAppState`, `GuildChannelResolvable`, `LiteralExpression`, `VantagePointInfo`, `IModelAnimation`, `PostCSSNode`, `UpdateRequestBuilder`, `GoThemeBackgroundCSS`, `ContextMenuDirection`, `JobRunSummary`, `ArgumentsType`, `StellarCreateTransactionOptions`, `TooltipModel`, `ReshapeLayerArgs`, `FindOneOptions`, `FlowTransform`, `FlexibleAlgSource`, `SignalState`, `GL2Facade`, `UniqueObject`, `AlertConfig`, `ListPager`, `WebhookSettings`, `IBaseRequestAction`, `IFileRange`, `FilterValue`, `chrome.contextMenus.OnClickData`, `SupportContact`, `IDrawData`, `IPeerLogic`, `ElementPropsWithElementRefAndRenderer`, `LineWidth`, `ConfigurationGroup`, `ExtraValues`, `GetRepositoryStatisticsPayload`, `CompositeMapper`, `IMapPin`, `SFieldProperties`, `CLICommand`, `SignCallback`, `IMesh`, `AltStore`, `MorphTarget`, `RequestInterceptor`, `IntType`, `MenuStateModel`, `JSONFormatter`, `OrmService`, `SessionConfiguration`, `CameraFrameListener`, `HALEndpointService`, `ValueMetadataDuration`, `RestoreWalletHandler`, `AuthAndExchangeTokens`, `GlyphData`, `TransitionController`, `HouseCard`, `RegionHash`, `AssetPropertyValue`, `PostProps`, `MarkupKind`, `UNK`, `BillDate`, `InstrumentName`, `EditStatus`, `QueryResultRow`, `DynamoDBStreamEvent`, `ButtonType.StyleAttributes`, `ICircuitState`, `SpekeKeyProvider`, `PlaceAnchor`, `FadingParameters`, `TokensList`, `GossipTimestampFilterMessage`, `mpapp.IPageProps`, `ClipPlane`, `NineZoneNestedStagePanelsManager`, `Principal`, `Highcharts.NetworkgraphLayout`, `VectorTransform`, `PackagerInfo`, `LabelDefinition`, `MDL0Model`, `SchemaCxt`, `BoardBuilder`, `SourceFileSystem`, `OutputProps`, `CustomerService`, `LanguageEntry`, `Push`, `DateParser`, `ViewModelQuery`, `yargs.CommandModule`, `RPCProtocol`, `Reverb`, `XroadIdentifier`, `PropertyDefinition`, `TickResultEnum`, `DetectionMetrics`, `Project.Root`, `GlobalConstraintRegistrarWrapper`, `SymbolIndex`, `DescribeRepositoriesCommandInput`, `React.ComponentType`, `Thunk`, `cloudwatch.MetricChange`, `RelationComparisonResult`, `AnnotationShape`, `CommandBuildElements`, `PubkeyResult`, `DescribeDBClusterParametersCommandInput`, `Json.Property`, `DataCardEffectPersonType`, `ActivityType`, `App.storage.ICachedSettings`, `thrift.TProtocol`, `MaterialAlertDialogBuilder`, `EntityCacheReducerFactory`, `ClusterContextNode`, `Types.Id`, `BeforeCaseContext`, `LabelOptions`, `StopTransformsRequestSchema`, `TypeOrUndefined`, `WebGLResourceHandle`, `ImportSpecifierArray`, `SocketMessages.produceNum`, `Id64Arg`, `SCSSParser`, `OperationResponse`, `FormlyTemplateOptions`, `ISuiteResult`, `PDFDropdown`, `IOAuthTokenResponse`, `PipelineRuntimeContext`, `IOSSplashResourceConfig`, `Decorator`, `DictionaryModel`, `ImportedRecord`, `ChangeVisitor`, `TransposeAttrs`, `GetAccessorDeclaration`, `... 15 more ...`, `SignatureHelpContext`, `AttandanceDetail`, `DataTypeResolver`, `LoadConfigResults`, `ViewManager`, `AsyncSubject`, `LexPosition`, `requests.ListSessionsRequest`, `Annotation`, `MeshComponent`, `ExportDeclaration`, `BinarySensorCCGet`, `FederationClient`, `CodeEdit`, `EmptyActionCreator`, `FirestorePluginOptions`, `TypeConfig`, `estypes.ErrorCause`, `PropTypesMapping`, `GetOpts`, `ActivityTypes`, `TextState`, `HandlerAction`, `UpdateChannelRequest`, `ChannelModel`, `UndoStack`, `HotkeyConfig`, `AppRegistryInfo`, `SubscriptionService`, `OptionGroup`, `BatteryStateEntity`, `Web`, `MediaTags`, `EstimateGasValidator`, `VueTag`, `IGLTFLoaderExtension`, `IWarningCollector`, `PathBuilder`, `IRemix`, `ProgressionAtDayRow`, `RollupCache`, `PriceScale`, `TableModelInterface`, `EnhancedItem`, `SignedTokenTransferOptions`, `CellGroup`, `LabelChanges`, `ProjectedXY`, `Identifiers`, `NBTPrototype`, `HomePluginStartDependencies`, `AstPath`, `TextSelection`, `ImGui.Style`, `SpendingConditionOpts`, `SQLNode`, `ScraperArgs`, `cytoscape.CollectionElements`, `ListAppInstanceUsersCommandInput`, `CompletionItem`, `Mounter`, `GetResourcesCommandInput`, `PainlessCompletionResult`, `ScheduleItem`, `IOrderResult`, `CreateServerCommandInput`, `HealthType`, `DetailViewData`, `ListSecretsRequest`, `MutationFunc`, `RedisAdapter`, `MutationTypes`, `IExecuteFunctions`, `TsxComponent`, `AlphaTest`, `CompareMessage`, `ContainerRepository`, `NefFile`, `BracketTrait`, `VideoPreferences`, `HtmlOptions`, `ProductInformation`, `DeleteMemberCommandInput`, `RemoveOptions`, `TimelineBuckets`, `ModernServerContext`, `DeviceDescriptor`, `BeneficiaryApplication`, `ObstaclePortEntrance`, `EvaluatorUsage`, `MoveType`, `IColorHierarchy`, `NatGateway`, `MongoCron`, `CharData`, `Profiler`, `CertificateResponse`, `FieldMetadata`, `TestHookArgs`, `requests.CreateConnectionRequest`, `GeistUIThemes`, `CommandValues`, `MutableList`, `BaseUAObject`, `TResponse`, `SortField`, `AnimatedValue`, `CompressionTextureTypeEnum`, `ApiPipeline`, `CardRenderDynamicVictoryPoints`, `FloatValue`, `InterpolateExpr`, `AzureWizardPromptStep`, `PersonStatusType`, `Queryable`, `AdmZip`, `EventActionHandlerActionCallableResponse`, `SubqueryProject`, `InjectionKey`, `ValueTypeOfParameter`, `CompletionTriggerKind`, `AnyPatternProperty`, `PaletteThemeConfig`, `DraggableList`, `ParsedProperty`, `CharLevelState`, `Events.precollision`, `EntitySchemaService`, `FileEntry`, `CompiledCard`, `TelemetrySavedObject`, `Nexus`, `ENABLED_STATUS`, `CursorBuffer`, `ScreenEventType`, `ExpenseService`, `CellClassParams`, `DeSerializers`, `StoreChangeEvent`, `TorusStorageLayerAPIParams`, `RelatedRecords`, `BaseAxisProps`, `CategoryDataStub`, `Defunder`, `WorkspaceFolder`, `FrameworkEnum`, `requests.ListKeyStoresRequest`, `StateManagerImpl`, `RegularStep`, `LuaState`, `CrochetCommand`, `AnyRegion`, `ListSnapshotBlocksCommandInput`, `MerchantGameActivityEntity`, `SettingsModel`, `FuzzyScore`, `LayoutDto`, `IArtist`, `BufferLines`, `PartytownWebWorker`, `MyAudioContext`, `ApiConfig`, `GraphPath`, `SourceRenderContext`, `FabricGatewayRegistry`, `JsxSpreadAttribute`, `IUpworkApiConfig`, `Mutator`, `HdPublicNode`, `IOfflineData`, `TemplateFile`, `IWrappedExecutionContext`, `JointOptions`, `RookCephInputs`, `CfnParameter`, `SharePluginStart`, `SyncArgs`, `RSTPreview`, `StackScreenProps`, `VpcConfiguration`, `RadioProps`, `ProcessListener`, `TransportResponse`, `ITableData`, `ReStruct`, `GridReadyEvent`, `ResourceChange`, `SaveFileWriter`, `TestNode`, `PluginsSetup`, `TexFunc`, `ViewFilesLayout`, `DefaultAzureCredential`, `ItemDataService`, `TimefilterSetup`, `ICommandOptionDefinition`, `DatModelItem`, `d.SourceMap`, `LocalizedLabels`, `ParsedMessagePartICUMessageRef`, `CurriedGetDefaultMiddleware`, `TweetMedia`, `FooBar`, `IListener`, `UnionOptions`, `DAL.DEVICE_ID_SYSTEM_TIMER`, `InputHTMLAttributes`, `BarRectangleItem`, `ExtractedAttr`, `SankeyPoint`, `EllipseEditUpdate`, `TidalExpression`, `IProjectData`, `DefaultDataServiceFactory`, `CampaignsModelExt`, `ConceptInstance`, `DerivedKeys`, `Transformer`, `ServiceGetPropertiesResponse`, `DashboardConfig`, `ResourceActionMap`, `CreateRoomRequest`, `SimplifiedType`, `QuantumMove`, `Container`, `PortMapping`, `AnnotatedError`, `SqlTuningTaskCredentialTypes`, `core.ApiRequest`, `ParticipantsLeftListener`, `ProjectStorage`, `EngineResults.ListMigrationDirectoriesOutput`, `LayerConfig`, `ExtractCSTWithSTN`, `vscode.Memento`, `WebClient`, `PrimitiveModeEnum`, `TerminalOptions`, `IToolchian`, `CONTENT`, `ExceptionBreakpoint`, `ErrorsByEcoSystem`, `ListAppsCommandInput`, `DataSetupDependencies`, `ExpBoolSymbol`, `React.FunctionComponent`, `LayoutManager`, `DescribeVpcPeeringConnectionsCommandInput`, `VueConstructor`, `TImageType`, `requests.ListOceInstancesRequest`, `ListJobsCommand`, `ResultInterface`, `DependencyOptions`, `BoundingBox`, `IndexPatternDeps`, `DocViewInput`, `Convolver`, `GeometricElement`, `PageQueryOptions`, `IParam`, `Suggest`, `GfxDeviceLimits`, `AuthenticateDeviceRequest`, `RpcConnectionWriter`, `AwrDbCpuUsageSummary`, `ItemPriceRate`, `BigInt`, `AcctStoreDict`, `bitcoin.Psbt`, `Arweave`, `IAjaxSettings`, `Matrix4x4`, `SerializedConcreteTaskInstance`, `btCollisionShape`, `ArrayProps`, `ODataFunctionResource`, `IGetExportConfigsResponse`, `IModelType`, `ZWaveError`, `IconConfig`, `Rebind`, `RunningGameInfo`, `IApiTag`, `EllipticPair`, `SurveyResultModel`, `GetMembersCommand`, `V1Service`, `XmlNamespacesCommandInput`, `K3`, `AccountFilterParams`, `ZosJobsProvider`, `ICombo`, `B11`, `OpenApiOperation`, `SkinnedMesh`, `IsSkipFeature`, `ToolChoice`, `GetStaticPaths`, `CreateCommentDto`, `ServiceMonitoringServiceClient`, `UnicodeSurrogateRangeTable`, `AnyFn`, `BlockInfo`, `Web3.CallData`, `ioBroker.Object`, `RefLineMeta`, `ITemplateMagic`, `AssignmentStatus`, `StubHelper`, `Highcharts.MapLatLonObject`, `ContentLoader`, `MappableType`, `SuiComponentFactory`, `HTTPMethod`, `FormContextValue`, `PopStateEvent`, `PluginWriteActionPayload`, `TextDocumentContentChangeEvent`, `PluginsServiceSetupDeps`, `NumRange`, `SizeNumberContext`, `MonitorRuleDef`, `ClockFake`, `ex.ExcaliburGraphicsContext`, `IndexRangeCandidate`, `ListVodSourcesCommandInput`, `PopperOptions`, `GetServerSideProps`, `BuildEdgeStyle`, `ChoicesType`, `AuditLog`, `ResolvedLibrary`, `CounterST`, `ReadyPromise`, `PaintServer`, `ANSITerminalStyleRenderer`, `BeanDefinition`, `ScopeSelector`, `ContractAbstraction`, `React.Props`, `InboundMessage`, `MongoManager`, `RawBlockHeader`, `TagExpr`, `Geom.Rect`, `HomeAssistant`, `ImageMimeType`, `PureComponent`, `MetaType`, `IToast`, `IconService`, `tcp.Connection`, `AddToLibraryAction`, `Definition`, `RTCRtpReceiver`, `PropertyNode`, `CustomFormControl`, `TRK1AnimationEntry`, `PluginWrapper`, `mapProperties`, `MangaDetailsFields`, `LogValueArgs`, `ParsedLocator`, `TdpClient`, `ToolAttr`, `ReportData`, `Dir`, `AssetModule`, `ChromeConnection`, `DMMF.ArgType`, `postcss.Rule`, `ExportData2DArray`, `WebElement`, `ResolvedSimpleSavedObject`, `hapi.Request`, `JobStatusResult`, `FileManager`, `RuleResult`, `OneNotePage`, `DidSaveTextDocumentParams`, `InstanceMember`, `PR`, `HsCommonLaymanService`, `RtcpSrPacket`, `IndexSymbolData`, `GeoVector`, `tl.FindOptions`, `AmbientLight`, `Work_Client.WorkHttpClient2_1`, `BrowseCloudDocument`, `apid.EncodeId`, `ClassThatUseDifferentCreateMock`, `Attribution`, `SequelizeModuleOptions`, `AbstractControl`, `OptionName`, `WheelEventState`, `Moltin`, `ListUnspentOptions`, `BulkActionProps`, `AutorestDiagnostic`, `IStdDevAggConfig`, `DataSourceSpec`, `IDynamicOptions`, `MDCRippleFoundation`, `TModel`, `Pitch`, `ManifestData`, `keyboardJS.KeyEvent`, `BrowserWindowConstructorOptions`, `DragEventHandler`, `SnapshotPublicData`, `TaxonomicFilterGroup`, `YellowPepperService`, `PDFWidgetAnnotation`, `BatchCertificateClaim`, `ShapeField`, `ICommandItem`, `GraphQLTaggedNode`, `IDejaDragEvent`, `ITourStep`, `InvoicePromo`, `SubjectDataSetFilter`, `IGitExecutionOptions`, `TransactionWithStatus`, `NetworkSettings`, `CountdownEvent`, `BlockData`, `PresentationManager`, `ParjsCombinator`, `TestData`, `JustifyContent`, `MapLayersService`, `BridgeToken`, `ColumnConfiguration`, `AssociatePackageCommandInput`, `FsFolder`, `mjAlerts`, `ArrayList`, `ChartParameters`, `requests.ListHttpMonitorsRequest`, `CssParser`, `capnp.Orphan`, `ISelectProps`, `ListContactsCommandInput`, `LoopAction`, `ElemAttr`, `jasmine.SpyObj`, `TemplateNode`, `ScannedDocument`, `IGetTimeLogInput`, `CLINetworkAdapter`, `ConfiguredPluginsClient`, `FrameParser`, `RX.Types.DragEvent`, `ObjectMakr`, `EC`, `RPC.KVClient`, `RefForwardingComponent`, `RuleTypeRegistry`, `ts.Block`, `ReadModelRegistry`, `MockAirlineService`, `ConnectState`, `StateChannelExitClaim`, `SimpleASTNode`, `RollupTransaction`, `EmbeddableEditorState`, `CSSResultGroup`, `Ulonglong_numberContext`, `CanvasThemePalette`, `Http3RequestMetadata`, `ICoords`, `SFUISchema`, `DestinationJson`, `TestReader`, `ExpirationDateVerification`, `ReadyType`, `EntityField`, `IndexedClassRewrite`, `InputFieldDefinition`, `ModelOptions`, `Filter`, `Bbox`, `TSelected`, `ColumnChunk`, `PostFrameUpdateType`, `FocusEventHandler`, `ResourceDayHeaderWrapper`, `IDeliveryNetworkResponse`, `ITitusServerGroupCommand`, `RBNFSymbols`, `ListPingProbeResultsRequest`, `GeneratorState`, `ts.LanguageServiceHost`, `MethodNames`, `HdDogePaymentsConfig`, `NotifyArgs`, `IDireflowConfig`, `NgrxJsonApiZone`, `CrochetCommandBranch`, `DirectoryIndexOptions`, `CreatePipelineCommandInput`, `ITransactionIdentifier`, `TinyColor`, `VoidAnyEvent`, `AlainDateRangePickerShortcutItem`, `Hentai`, `GraphQLRequestContext`, `ShareAdditionContent`, `SdkRemoteParticipant`, `QueueSSEService`, `MikroORM`, `ReportFilter`, `WorkspaceExtImpl`, `Submit`, `BookmarkMetadata`, `SetVaultParameter`, `CollisionShape`, `angular.IScope`, `ProcessDataService`, `MentionData`, `serviceDefinition`, `FunctionWithKey`, `UrlForwardingPlugin`, `WebContents`, `HealthCheckResult`, `QueryBus`, `UserMentionEntity`, `OrderStatusReport`, `MagentoProduct`, `EventInfo`, `ChecklistTask`, `JobName`, `IChangeDiscussionItem`, `ReadStorageObjectsRequest`, `UpSetAddons`, `ContractManifest`, `ArrayComparator`, `GenesisProtocolProposal`, `AssociationLifecycleState`, `SavedObjectManagementTypeInfo`, `OmvGeometryType`, `Vector2Like`, `EIP712TypedData`, `ExportFormat`, `OperatorValueFilterDescriptor`, `TxtParentNode`, `CourseActions`, `CountModel`, `MomentDateAdapter`, `LogItemProps`, `GraphQLRequestConfig`, `ParsedExampleTree`, `msRest.Mapper`, `BaseEncryptedPacket`, `DefaultItemType`, `MockMessage`, `ChangeProjectCompartmentDetails`, `InMemoryFileSystem`, `MidiDevice`, `MMOnlineStorage`, `BazelBuildEvent`, `PartialResolvedId`, `StateChannelJSON`, `XPCOMObserverTopic`, `ImageProvider`, `SapphireDbService`, `IMessageFromBackground`, `SharedTreeSummaryBase`, `Hono`, `StopFlowCommandInput`, `DsnComponents`, `DataFactoryClient`, `d.PrerenderStartOptions`, `TypedMessageRendererProps`, `model.domain.DomainElement`, `WebSocketServer`, `ComponentOrTag`, `LoDashStatic`, `Plugin`, `FunctionMap`, `SpeechRecognitionEventArgs`, `FrameResult`, `QueryMiddlewareParams`, `BuildImpl`, `TypedMap`, `WikiPage`, `OhbugMetaData`, `GetterTree`, `HtmlNode`, `GraphQLServer`, `Strip`, `DataLimit`, `GenericTwoValues`, `LRUItem`, `LatLngExpression`, `ErrorListener`, `FailureInfo`, `GluegunAskResponse`, `BodyPixOperatipnParams`, `CollectionDataService`, `EnvironmentVariable`, `DevtoolsPluginApi`, `ReleaseOptions`, `ConfirmationDialogService`, `TodoItemEntity`, `IFormControlProps`, `TopMiddleBottomBaseline`, `LogBuilder`, `Rpc`, `AggregatedResult`, `MetricServiceClient`, `LGraphNode`, `RadarrSettings`, `TreeSeriesNodeItemOption`, `DeviceAccess`, `IndexAliasData`, `jsPDFDocument`, `TapGesture`, `IPlayer`, `ProjectId`, `DatedAthleteSettingsModel`, `ModuleConfiguration`, `RemoteService`, `TwingTokenStream`, `ExprWithParenthesesContext`, `BitbucketAuthTokenRepository`, `SobjectResult`, `THREE.Light`, `PaginationResult`, `CommonPrefix`, `ApiResult`, `TService`, `MacroKey`, `PolyDrawing`, `KillRingEntity`, `FlagsT`, `PDFAcroRadioButton`, `PropTypes`, `PatternLibrary`, `IEditorStore`, `IMacroBuffer`, `CodeLensParams`, `LineMetrics`, `RetryConfigState`, `SchemeObject`, `InlineControl`, `GraphQLCompositeType`, `ParserOptions`, `DissociatePackageCommandInput`, `OperationRequestDetails`, `MovementType`, `FeedPost`, `MultiChannelAssociationCCSet`, `MockErc20Token`, `AccountingTemplateService`, `IBuffer`, `DeferredDefinition`, `DatabaseStatus`, `ApiOperation`, `IErrorInfo`, `PropTypeFinder`, `IProtocolConstructor`, `Bodybuilder`, `DefaultOptionType`, `IMeetingRepo`, `StateFor`, `TestEnvironment`, `d.JsonDocsEvent`, `SymbolSet`, `AppStore`, `CalendarCell`, `PortablePath`, `XMLBuilderContext`, `WorkingHour`, `VisualizeEmbeddableConfiguration`, `TouchingElementInfo`, `OrganizationPoliciesConfig`, `StringEncodedNumeralFormat`, `FunctionDefinitionNode`, `IProposal`, `FieldsConfig`, `SpeakersState`, `HdDogePayments`, `ApplicationContainerState`, `PageScrollService`, `StrokeProtocol`, `DefaultKernel`, `JsonVisitor`, `numericRootOfPolynomial`, `TaskCallback`, `ChannelItem`, `V`, `ChooseImageSuccessCallbackResult`, `execa.Options`, `EventKind`, `DeployHelper`, `DFS_Config`, `UserFormValues`, `JWK.Key`, `Walker`, `ImportBlock`, `TupleData`, `CombatStateRecord`, `PythonPathResult`, `LRParser`, `ShapeT`, `CpuUsage`, `DeleteChannelBanCommandInput`, `Bip32Options`, `ServerlessAzureConfig`, `AccessorEntry`, `JiraColumn`, `MessageConfig`, `SendTx`, `IncrementDirection`, `MetricsPublisher`, `DeployedPlugin`, `CalculatePvService`, `Union`, `DecodedAddress`, `WritableStreamDefaultWriter`, `IntervalSet`, `MultProof`, `EmbeddableStart`, `FunctionalUtilities`, `IRowAPI`, `PlexMetadata`, `MockSelector`, `ComboBoxGroupedOption`, `InanoSQLTable`, `UpdateLongTermRetentionBackupParameters`, `Articulations`, `ECR`, `AnyId`, `ProjectInitializerConfig`, `requests.ListUserGroupMembershipsRequest`, `HttpPrefixHeadersCommandInput`, `OpticsContext`, `fun`, `StandardContentToolsProvider`, `JoinOptions`, `MrujsPluginInterface`, `MetaProps`, `PasswordHistoryView`, `IGceHealthCheck`, `fs.PathLike`, `WinstonLogger`, `UpdateProjectDto`, `FeedbinConfigs`, `SVString`, `ModelObject`, `ResourceKind`, `VirgilPublicKey`, `Survey.JsonObjectProperty`, `TutorialSchema`, `HelpError`, `CalloutArrow`, `VpcContextQuery`, `IBinaryDataConfig`, `ts.ExportAssignment`, `ConstantState`, `K.ExpressionKind`, `PointCloudOctree`, `WrapperLayerArgs`, `WaveformItem`, `InferGetStaticPropsType`, `DiffResultMessage`, `ConfigMetaFormat`, `CocSnippetPlaceholder`, `DescribeOrderableDBInstanceOptionsCommandInput`, `HelpCenterArticleService`, `BoolValue`, `LuaFiledCompletionInfo`, `PutConfigurationSetReputationOptionsCommandInput`, `CHR0_NodeData`, `SubschemaArgs`, `TSESTree.CallExpression`, `SelectionRangeParams`, `WexBimProduct`, `QueueNode`, `StorageFieldItem`, `NpmPackageManipulator`, `BinaryPaths`, `CreateGlobalClusterCommandInput`, `LanguageModelCache`, `LightGroupCircuit`, `GetUpdateConfigParams`, `RollupOptions`, `MockSocket`, `TreeCheckboxStateChangeEventArgs`, `ContextMenuRenderer`, `LaunchOption`, `DrawerHelperOptions`, `LatLngBounds`, `MsgRevokeCertificate`, `TimeRanges`, `InputAndOutputWithHeadersCommandInput`, `IHeaderState`, `ScalarTypeDefinitionNode`, `Collateral`, `i18n`, `ReadTransaction`, `TypeType`, `RangeSliderProps`, `IRuleConfig`, `StateMachine.State`, `ProfileStates`, `DrawerProps`, `SavedObjectsOpenPointInTimeOptions`, `VocabularyCategory`, `FormArrayState`, `ResponseReceivedEvent`, `QuadrantType`, `THREE.Mesh`, `RegistryDocument`, `PostgresClient`, `DescribeCertificatesCommandInput`, `ListSchema`, `IRemoteRoom`, `FabFilesObject`, `WithGenericsSub`, `BaseRenderer`, `RenderFlex`, `PmsiListType`, `InterfaceTypeWithDeclaredMembers`, `Phaser.Input.Pointer`, `ServerTreeItemPageObject`, `BSQRegex`, `TemplateWrapped`, `OperationStack`, `IAnyExpectation`, `BinaryStream`, `Node.Event`, `google.maps.MouseEvent`, `MigrateResolve`, `YfmToc`, `TrackedHasuraEventHandlerConfig`, `VulnerabilityAssessmentName`, `NodeGroup`, `FACE`, `Prefixer`, `Denomination`, `IFile`, `NextCommandOptions`, `PouchFactory`, `IArea`, `SeriesDataSortingOptions`, `StmtDiff`, `SoundService`, `ChainType`, `EventBus`, `AnimationInfo`, `Hooker`, `ScryptParams`, `Tenant`, `STComponent`, `ServiceEndpointPolicyDefinition`, `EmbeddableStartDependencies`, `ArticleList`, `TokenAmount`, `ManagementDashboardSummary`, `ObjectProperty`, `PipelineStatus`, `InternalApplicationSetup`, `PerformanceObserver`, `StateDecorator`, `TypeCheck`, `HapiResponseAdapter`, `DelayFunction`, `DynamicRepository`, `QueryExpressionBodyContext`, `ClrQuickListValue`, `LookupDescriptor`, `NamedMatchMediaProps`, `XmlComponent`, `PrunerPiece`, `Luna`, `IOrchestratorState`, `MangolState`, `ConfigurationPropertyValue`, `IAnalyticsService`, `Boost`, `Discord.Message`, `ComponentConfiguration`, `Remirror.CommandDecoratorOptions`, `MockResponse`, `TransactionInput`, `IDiagnosticsRow`, `Errorable`, `TimestampFormatHeadersCommandInput`, `ReadonlyVec4`, `CompositionTypeEnum`, `PossiblyAsyncOrderedHierarchyIterable`, `d.CssToEsmImportData`, `ImageFiltering`, `TasksStore`, `PhantomWallet`, `ModifyDBSubnetGroupCommandInput`, `VirtualDirectory`, `ChannelPermissionOverwrite`, `NamedArrayBufferSlice`, `d.TestingConfig`, `HttpsAgent`, `IMergeFile`, `BackgroundReplacementVideoFrameProcessorObserver`, `CreateRegexPatternSetCommandInput`, `ExpectedResponse`, `NodeRange`, `RequireStatementContext`, `SetupFunc`, `OnFailure`, `TouchEventHandlerType`, `DBType`, `GraphQLArgument`, `Chart.CallbackFunction`, `SmallLicense`, `NormalMod`, `requests.ListTopicsRequest`, `AuthCore`, `BaseAppearanceService`, `NumberInput`, `ITelemetryErrorEvent`, `ProjectRisk`, `DeployedWallet`, `Completion`, `Apply3`, `I18NService`, `AuthenticationProvider`, `FilterCondition`, `PushResponse`, `ISearchStart`, `FnU3`, `InsertionType`, `GridPattern`, `Study`, `EngineArgs.MarkMigrationRolledBackInput`, `HandleElement`, `SegmentRange`, `BorderStyleProps`, `CoreEditor`, `S`, `BasicObstacleSide`, `MetadataPackage`, `VtxLoaderDesc`, `EntryObject`, `CollisionDirector`, `RawCard`, `GetInviteCommand`, `fs.Stats`, `BackwardScanner`, `CipherAlgorithm`, `SlideUIEvent`, `IHttpService`, `LocaleMap`, `StockData`, `HaveIBeenPwnedApiResponse`, `RoadmapType`, `ClientItemViewModel`, `instantiation.IConstructorSignature4`, `Quote`, `ts.TypeChecker`, `IFiles`, `CellInfo`, `BlockAction`, `BezierCurve3d`, `LaunchTemplateSpecification`, `CreateAppOptions`, `IMetricListener`, `Loader`, `ReserveData`, `TimelineRowStyle`, `Actor`, `ListNamespacesCommandInput`, `ActiveSpeakerPolicy`, `CSSDesignToken`, `GenericStatusModel`, `BandFillColorAccessorInput`, `AppCommitment`, `FetchMock`, `SectionProps`, `UserGroupList`, `ExpandPanelAction`, `ResponseStatus`, `UpdatePhotoDto`, `IContentSearchResponse`, `JudgeClientEntity`, `RestModelEntry`, `ViewElement`, `MathViewProps`, `AgentConfigOptions`, `ITextModel`, `Preflight`, `RouteRecognizer`, `StynRule`, `StrokeCountMap`, `PageTitleService`, `EntryType`, `CursorConnectionType`, `GetMemberCommandInput`, `ListModelsCommandInput`, `MigrationStates`, `RouterSpec`, `InitializeMiddleware`, `TSerDeOptions`, `XmlBlobsCommandInput`, `LgQuery`, `dStage_stageDt_c`, `ErrorReporterConstructorContract`, `SaplingNativePlugin`, `Handshake`, `FabricEnvironmentRegistry`, `tags.Table`, `Cohort`, `TemplateManifest`, `IRecordedDB`, `ThemeSettings`, `DeleteAppInstanceAdminCommandInput`, `DMMF.SchemaArg`, `HomeOpenSearchDashboardsServices`, `ComponentMeta`, `TokenPair`, `ReferenceDirection`, `MatchedMiddleware`, `requests.ListDbHomePatchesRequest`, `ITreeNode`, `SVGSVGElement`, `ChartActionContext`, `PolicyDocument`, `PadModel`, `DisplayValueSpec`, `requests.ListVmClusterUpdateHistoryEntriesRequest`, `StoreGroupLike`, `preference.Set`, `MarvinImage`, `NgAddOptions`, `ReadableByteStreamController`, `DevtoolsInspectorProps`, `DevtoolsBackend`, `TriggerId`, `Tab`, `d.ModeStyles`, `RelativeBandsPadding`, `AdapterFindOptions`, `requests.ListAutonomousExadataInfrastructuresRequest`, `MDCTabDimensions`, `AnalyzedStyle`, `KeyStrokeOptions`, `ShowOptions`, `d.OutputTargetCopy`, `ThyScrollService`, `ISearchEventDataTemplate`, `AppContextService`, `TagResourceCommandInput`, `AnnotationLayer`, `WidgetRegistry`, `ShareContextMenuPanelItem`, `LetAst`, `Studio.App`, `ExclamationToken`, `LibrarySeriesSeasonEpisode`, `EthereumLedger`, `Box2`, `ViewerParameters`, `DefinitionParams`, `CollisionGroup`, `TagsBase`, `EC2`, `ItemList`, `DoorLockCCConfigurationReport`, `TRuleResolver`, `ThyFullscreenRef`, `TranslationDictionary`, `TagListMessage`, `FilterFn`, `ModItem`, `IResultSetUpdate`, `FileChange`, `Assert`, `MethodMaterial`, `DBClient`, `Iterate`, `DeviceManagerClient`, `IncrementalNode`, `MoveOptions`, `ListPackagesRequest`, `Auditor`, `GraphQLRequestContextWillSendResponse`, `FullPageScreenshotDataOptions`, `AppLogger`, `TracerConfig`, `TextBuffer`, `AsBodilessImage`, `AppComponent`, `SharedValue`, `ResourceLines`, `Boss`, `TypeSystemPropertyName`, `ConnectionOptions`, `TestAwsKmsMrkAwareSymmetricKeyring`, `UrlLoader`, `IMrepoDigestConfigFile`, `React.DetailedHTMLProps`, `moneyMarket.overseer.CollateralsResponse`, `EntityMetaData`, `Applicative`, `LazyResult`, `PropertyDeclaration`, `TaggedNumericData`, `Sheets`, `IContainerContext`, `ServiceConfigs`, `IDestination`, `FileBuffer`, `ListDomainDeliverabilityCampaignsCommandInput`, `DispatchFunc`, `parse5.Element`, `ExpressionServiceParams`, `FounderConfig`, `ICompanionElement`, `SpotifyApi.CurrentUsersProfileResponse`, `BaseFee`, `StitchesProps`, `RetryPolicy`, `Classification`, `SessionPort`, `DescribeDBClusterEndpointsCommandInput`, `Alert`, `Pojo`, `VersionRange`, `InternalRequestParams`, `ClientRequestResult`, `ErrorRes`, `DropTargetOptions`, `Complex`, `ServeD`, `ContractDecoratorKind`, `OnUpdate`, `common.Keybinding`, `Department`, `FieldResolver`, `OsdServer`, `ContentService`, `ExtendedCanvasRenderingContext2D`, `S2CellType`, `ZoneInfo`, `IKeyboardDefinitionAuthorType`, `NewsItemModel`, `FileChunkIteratorOptions`, `GitCommitLine`, `AssetID`, `tabBrowser`, `TronSignedTransaction`, `DayStressModel`, `BMDObjectRenderer`, `NodeSubType`, `RpcMessage`, `DevcenterService`, `FeatureOptions`, `ResponseIssue`, `WebElementPromise`, `EChartsType`, `EpochTracker`, `ContentControl`, `Battle`, `ModifyDBClusterParameterGroupCommandInput`, `TitleVisibility`, `UserIdentity`, `ts.TaggedTemplateExpression`, `AvailabilityDomain`, `H5GroveEntityResponse`, `EthereumTransactionOptions`, `jasmine.CustomMatcher`, `DeepMapResult`, `Create`, `DaffCompositeProductItemOption`, `... 12 more ...`, `NSAttributedString`, `RemoteVideoStreamState`, `UpdateApplicationCommandInput`, `CompositeReport`, `SnippetsMap`, `CreateContextOptions`, `CodeGenFieldConnection`, `IAzExtOutputChannel`, `BarGeometry`, `requests.ListExportsRequest`, `kbnTestServer.TestElasticsearchUtils`, `EventType.onInit`, `ChainTransaction`, `SeparableConvParams`, `MatchProps`, `ModelsTreeNodeType`, `SubscriberRepository`, `TMouseEventOnButton`, `Socket`, `NonTerminal`, `Storage`, `FocusTrapInertStrategy`, `d.E2EProcessEnv`, `AnyQuery`, `PropertyContext`, `IUnlisten`, `Key3`, `OneIncomingExpectationRepository`, `CollectMultiNamespaceReferencesParams`, `MemberService`, `DownloadStreamControls`, `GitlabAuthResponse`, `DescribeConfigurationRevisionCommandInput`, `IDimensions`, `GraphicsItem`, `Times`, `ServiceOptions`, `Value2D`, `UI5Class`, `HTMLAttributes`, `INormalAction`, `CommonTokenStream`, `Http3QPackDecoder`, `MimeBuffer`, `ShaderityObject`, `JSXAnalysis`, `CompletionsCollector`, `UpdateGroupCommandInput`, `PitchShifter`, `NzModalService`, `BlockDisk`, `NavigationGuard`, `NodeData`, `TargetTypeMetadata`, `FileCommitDetails`, `PlotLineOptions`, `ElementFlags`, `BuildArtifacts`, `aws.s3.Bucket`, `InternalStack`, `OnTabReselectedListener`, `FsWriteResults`, `FilterCategory`, `TextEditorElement`, `TaskInfoExtended`, `ODataPropertyResource`, `EmissionMaterial`, `Platform`, `SingleObjectWritableStream`, `BoundingRect`, `ActorAnimKeeperInfo`, `OAuth2Service`, `T.ID`, `HTMLTemplateElement`, `WidgetView.IInitializeParameters`, `ModeRegistration`, `StatementContext`, `ArticleItem`, `FrameRateData`, `filterSymbols`, `PropertyAccessExpression`, `SCNNode`, `NgModuleTransitiveScopes`, `RpcResponseAndContext`, `RetryConfig`, `LikeNotification`, `CacheListener`, `BearerTokenResponse`, `OrderedId64Iterable`, `SetValueOptions`, `UpdateGlobalSettingsCommandInput`, `Motion`, `EnumTypeDefinitionNode`, `QueryState`, `IEventStoreData`, `ManifestInfo`, `INodeDef`, `TradeResponse`, `IndyWallet`, `MsgType`, `TemplateValidatorOptions`, `SubStmt`, `SavedObjectDashboard`, `MiscellaneousField`, `IArrivalTimeByTransfers`, `PageInfo`, `PadchatRpcRequest`, `TypeSystemEntity`, `ActionImpl`, `FrameTree`, `Shading`, `solG2`, `requests.ListVaultsRequest`, `requests.ListNatGatewaysRequest`, `T18`, `IGherkinDocument`, `CmdletParameters`, `ExitStatus`, `CodeExecutionEmitter`, `DeliveryOptions`, `SelectionModel.ClearMode`, `FileSystem`, `IStaticMeshComponentState`, `EditState`, `LogicalElement`, `com.google.firebase.firestore.Query`, `ReadFn`, `FullNote`, `PointerDragEvent`, `MoonbeamCall`, `DescribeIndexCommandInput`, `StatusChartStatusMesh`, `Resort`, `ApolloQueryResult`, `LineChartProps`, `UnitValue`, `QuerySubState`, `LoggingOptions`, `ITelemetryData`, `DaffCartLoading`, `ServerConfiguration`, `CompilerEventBuildStart`, `GX.KonstColorSel`, `PropagationResults`, `UseStylesProps`, `SuperExpression`, `ServerAccessKeyRepository`, `CreateDBParameterGroupCommandInput`, `SharedContentInfo`, `LeafletMouseEvent`, `Cluster`, `ViewPortItem`, `NodeCryptoCreateCipher`, `requests.UpdateJobRequest`, `RLANAnimation`, `WorkItemQuery`, `NavigateToPath`, `PouchDatabase`, `GenericResource`, `EndOfLine`, `LeafletContextInterface`, `FirebaseFirestore.DocumentReference`, `Mp4BoxTree`, `RequestParams`, `Preprocessors`, `ViewerOptions`, `TypeSelectionProps`, `NgScrollbarBase`, `CssAstVisitor`, `BluetoothRemoteGATTServer`, `OrgType`, `IDynamicStyleProperty`, `HdTronPaymentsConfig`, `CmsEntryPermission`, `HsLayerFlatNode`, `ItemsList`, `IntNumber`, `InterpolationType`, `ParsedConfig`, `ItemUUID`, `EasyPzCallbackData`, `LogicalCpuController`, `VertexAttribute`, `WorkspaceState`, `JsonlDB`, `OutputsType`, `EnumValues`, `TileInputs`, `MediaStreamAudioDestinationNode`, `GraphWidget`, `FontWeight`, `TAuthor`, `ListOperations`, `BackblazeB2File`, `WidgetManager`, `UserSubscriptionsInfo`, `ElementOptions`, `ConsoleMessageLocation`, `CompilerSystemWriteFileResults`, `IImposer`, `PyteaOptions`, `DejaTilesComponent`, `DraymanComponent`, `DatabaseItem`, `LayerStyle`, `CallSignatureDeclaration`, `SerializableState`, `ListModelConfig`, `unchanged.Unchangeable`, `IReversibleJsonPatch`, `PathHash`, `Route`, `RegistryVarsEntry`, `SfdxFalconResultRenderOptions`, `NodeCG`, `requests.ListDbHomesRequest`, `TsGenerator.Factory.Type`, `HTMLProps`, `KernelProfile`, `DrawConfig`, `MockedFunctionDeep`, `PlacementProps`, `SymbolAccessibilityResult`, `d.Logger`, `MethodResponse`, `ExceptionHandler`, `ColumnAnimationMap`, `MessageMatcher`, `ExecInspectInfo`, `ThyTreeService`, `EventTypeMap`, `IAsyncParallel`, `ConnectableObservable`, `ProgressTracker`, `SortPayload`, `RTCIceParameters`, `Announcement`, `MiddlewareOverload`, `FixtureSetupDeps`, `GlyphElement`, `UserDetails`, `DynamicGrammarBuilder`, `EventMetadata`, `DepthModes`, `Living`, `WatchOfConfigFile`, `GfxDebugGroup`, `FreezerInstance`, `ParsingMetadata`, `QueueService`, `DocumentType`, `ElementRenderer`, `PinOverrideMode`, `MapObjActorInitInfo`, `DirectiveType`, `SavedObjectsFindResult`, `PropertyKey`, `IRules`, `ComponentMetadata`, `ParameterizedContext`, `RootConnection`, `VisitorContext`, `MuteRoomTrackRequest`, `ItemDataType`, `ModelIndexImpl`, `ChannelResult`, `AsyncTask`, `CookieStorage`, `IUserSession`, `serviceRequests.GetJobRequest`, `ObservableDbRef`, `RtkQueryMonitorState`, `XPathData`, `DateBatch`, `PutSessionCommandInput`, `ControllerAction`, `DateProfileGenerator`, `ActionFunction1`, `requests.ListContainerDatabasePatchesRequest`, `DeleteExperimentCommandInput`, `GroupIdentifier`, `DAGDegrees`, `DryRunPackagePolicy`, `d.JsonDocsComponent`, `PropertyToValues`, `DropDownElement`, `OutStream`, `DragRefInternal`, `DealRecordsConfig`, `ResultTreeNode`, `ReakitTabInitialState`, `MaxHeap`, `SQLQuery`, `AccountGameCenter_VarsEntry`, `SendPayload`, `UpdateIntegrationCommandInput`, `ViewCompiler`, `RelocateNodeData`, `DecorationRenderOptions`, `GetCertificateResponse`, `SfdxTask`, `NormalizedEntrypointItem`, `RecurringBillId`, `FileMap`, `GeocoderQueryType`, `SerializationContext`, `IViewModel`, `CountryCode`, `Mongoose`, `NavNodeInfoResource`, `BaseShape`, `Cocoen`, `ElevationRangeSource`, `IPortfolio`, `StringTypeMapping`, `ConditionGroup`, `CustomSprite`, `PxtNode`, `StageCrewMember`, `ListExportsRequest`, `Permission`, `NoteName`, `AlertClusterStatsNode`, `XMLHttpRequest`, `TrackEventType`, `ProblemEntity`, `RestManagerRequestData`, `BackwardIterator`, `AddSourceIdentifierToSubscriptionCommandInput`, `ScrollToOptions`, `AsyncStorageHandler`, `EmitOptions`, `ControlFlowGraph`, `RectL`, `DocFn`, `Float32Array`, `WarpPod`, `FileReader`, `PluginManifest`, `HasLocation`, `SceneExport`, `CrossTypeHost`, `BlockbookBitcoin`, `BlockClass`, `ClassificationResult`, `IndexNode`, `Atom.Range`, `IndexPatternPrivateState`, `INamedVector`, `DetailListService`, `BasePathCoverage`, `InstallationsFile`, `MailSettings`, `IAuthUserWithPermissions`, `ISearchState`, `RenderNode`, `Iso`, `FiltersCreationContext`, `UpdateDomainCommandInput`, `AttributeToken`, `AuthStatus`, `MenuBuilder`, `StepperState`, `NetNode`, `Sky`, `IFilterInfo`, `Modal`, `SelectContainerProps`, `HsvaColor`, `PluginStreamActionPayload`, `ParsedInterface`, `NineZoneStagePanelsManager`, `AESKey`, `RegistrationType`, `IPrimitiveExpression`, `GPUTextureView`, `MemoizedSelectorWithProps`, `TreeNodeWithOverlappingSubTreeRoots`, `TStoreName`, `DeleteApplicationCommandOutput`, `CharUnion`, `ToastActions`, `TEffects`, `NavigationEnd`, `FragmentableArray`, `RRule`, `FileTransfer`, `XmlRecording`, `LicenseType`, `messages.Source`, `GameObjectGroup`, `DaffCategory`, `UInt32Value`, `WebviewEvent`, `WidgetOpenerOptions`, `ReceiverEstimatedMaxBitrate`, `DataPin`, `React.KeyboardEventHandler`, `WorkerPool`, `ApolloCache`, `MockProviders`, `JsonSchemaRegisterContext`, `GroupData`, `GraphExecutor`, `StateType`, `android.view.LayoutInflater`, `BoxPlotPoint`, `UIPageViewControllerImpl`, `BitcoinSignedTransaction`, `SetOptions`, `EmitOutput`, `DefinedSmartContract`, `UrlObject`, `UploadState`, `KayentaCredential`, `JobMetadata`, `Fig.Generator`, `DatepickerDialog`, `IStandardEvent`, `Turmoil`, `IStatisticSum`, `DukBreakPoint`, `DotenvLoadEnvResult`, `SessionResponse`, `IStructuredSearch`, `IOrchestrationFunctionContext`, `ParserAstContext`, `ProposalMessage`, `Upgrades`, `SignupRequest`, `ScanMetadata`, `NotificationList`, `STPAPIClient`, `vscode.SymbolKind`, `El`, `PlayerList`, `RegistryPackage`, `BlockchainContext`, `BotFilterFunction`, `PresentationPreviewAttribute`, `Separated`, `LoanMasterNodeRegTestContainer`, `CurrentUserType`, `SystemVerilogContainerInfo`, `IImageFile`, `FluentDOM`, `eventHandler`, `FoundationElementRegistry`, `ObjectAssertion`, `SceneObjectBehavior`, `EvaluatedStyle`, `RateType`, `IAudio`, `RBTree`, `ts.PropertyAssignment`, `HoverInput`, `PointString3d`, `InvalidatorSubscription`, `CurveLocationDetailArrayPair`, `PDFContext`, `MDCChipSetAdapter`, `RectangleConstruction`, `ICSVInConfig`, `IEmployeeUpdateInput`, `NotificationTemplateRepository`, `QueryCacheKey`, `PaymentRequest`, `Conic`, `HttpServiceBuilderWithMetas`, `KeyFunc`, `FluentRuleCustomizer`, `Channels`, `ButtonToggleComponent`, `KeyframeAnimationInfo`, `messages.PickleTable`, `IGetActivitiesInput`, `SQLiteTableDefinition`, `IModelIdArg`, `PathProxy`, `LayerDescriptor`, `StatementListNode`, `SpecQuery`, `AccountRegistry`, `PropertyDescriptorMap`, `RouteRecordNormalized`, `SubscriptListResult`, `DndService`, `ClubEvent`, `MutationListener`, `PathInfo`, `Json.StringValue`, `NameInfoType`, `I18nEntries`, `WalletSigner`, `BigNumber.Value`, `CircularDependency`, `ConnectionCredentials`, `RouteParams`, `ServerCertificateRequest`, `RequireContext`, `StringTableEntry`, `Distributes11`, `NativeContractStorageContext`, `RailsDefinitionInformation`, `GeneratorCore`, `ILinkedListItem`, `ReflectionKind`, `RolePermission`, `RedBlackTreeStructure`, `UILabel`, `PropertyEditorProps`, `VpnServerConfiguration`, `Pools`, `RnM2Node`, `Parse`, `HTMLScWebglBaseChartElement`, `YColumnsMeta`, `DeclarationFlags`, `TabLayoutNode`, `OpenCVConfig`, `AbsoluteSizeSchema`, `BotTimer`, `Now`, `DateInputFormat`, `ExternalServiceIncidentResponse`, `E1`, `Limits`, `TSDocConfiguration`, `ConstructSignatureDeclaration`, `TypeFormatFlags`, `CacheProvider`, `ScrollData`, `GridsterItem`, `UserCourseModel`, `PointList`, `Conv3DInfo`, `ElementAccessExpression`, `MeshColliderShape`, `OrderDTO`, `ClockMock`, `DaffRouteWithDataPath`, `IBookmark`, `LoadedEnv`, `KnotVector`, `ParaType`, `AnnotationChart`, `DebugLogger`, `LabeledScales`, `DecompileResult`, `PostfixUnaryExpression`, `SavedQueryMeta`, `UnauthorizedErrorInfo`, `HdTronPayments`, `ODataConfiguration`, `Snippet`, `IContextProvider`, `TimeInstant`, `NestedPayloadType`, `RTCRtpTransceiver`, `PipelineProject`, `requests.ListManagementAgentInstallKeysRequest`, `V1RoleBinding`, `TargetResourceType`, `GetSemesterTimetable`, `IComparer`, `RollupResult`, `Positions`, `SagaMiddleware`, `Hookable`, `AttributeService`, `SetOptional`, `Id64Array`, `ProfileServiceAPI`, `SetStateCommitmentJSON`, `InviteMemberCommand`, `Common`, `LocalFluidDataStoreContext`, `WalletContext`, `WriteResult`, `Lineup`, `KeyringPair`, `ValidationConfig`, `TaskName`, `TextWriter`, `StepResultAfterExpectedKey`, `CdkDialogContainer`, `ImportSteamFriendsRequest`, `AliasedFeature`, `AutorestArgs`, `IAppVersion`, `ReactiveController`, `TNSImageAssetSaveFormat`, `GXRenderHelperGfx`, `SearchMode`, `OutputAsset`, `Apply2`, `d.ComponentCompilerMeta`, `GroupDocument`, `WorkingDirectoryFileChange`, `CommandClasses.Basic`, `StoreProvider`, `DeploymentCenterData`, `BitcoinNetworkConfig`, `Peer.DataConnection`, `AccidentalMark`, `ProviderResource`, `GetLoggingConfigurationCommandInput`, `AuthResourceUrlBuilder`, `DeltaChangeContext`, `LinkRenderContext`, `FunctionRunner`, `MapEventsManagerService`, `RequestTypes`, `Archives`, `IStepDefinition`, `RangeSelector`, `WorkspaceResourceName`, `SettingsPriority`, `EntityWithEquipment`, `ArrayLiteralExpression`, `AstMetadataApiWithTargetsResolver`, `GetTraceSummariesCommandInput`, `ComplexBinaryKernelImpl`, `IReferenceLayer`, `CorrelationsParams`, `SponsoredAuthorization`, `IndicatorNode`, `IINode`, `ApiDefForm`, `EntityQuery`, `IKeyState`, `OperatorLogPoint`, `GfxrRenderTargetDescription`, `ICreateChildImplContext`, `RequestQueryParamsType`, `Appender`, `ParsedElement`, `TVSeason`, `ValidatePurchaseGoogleRequest`, `ISeinNodeExtension`, `LogDescription`, `Types.ObjectId`, `MsgCreateBid`, `WebRequestMethod`, `LoadableComponent`, `Toc`, `AuthenticateOptions`, `AttachVolumeCommandInput`, `MockDocumentFragment`, `RoxieService`, `EntityCollection`, `Evidence`, `double`, `ProposalTransactionJSON`, `Fontkit`, `CacheRecord`, `LensMultiTable`, `StandardFontEmbedder`, `VisibilityFilters`, `SuiSelectOption`, `ExiftoolProcess`, `IEntity`, `NestView`, `SourceDescriptionItem`, `SendResponseParams`, `CONFIG`, `IGroupDataArray`, `Quad`, `Dependencies`, `SMTIf`, `CombinedVueInstance`, `t.ObjectExpression`, `TSPropertySignature`, `PluginFunctions`, `PrimitiveTypeKind`, `BankAccountService`, `requests.ListVcnsRequest`, `CanvasPinRow`, `StableVer`, `RunService`, `N7`, `RemoteVideoStream`, `ObservableParticle`, `Quantifier`, `React.MouseEvent`, `RequestQueryBuilder`, `RuleViolation`, `ReadonlyESMap`, `AnalysisDataModel`, `CosmosDBManagementClient`, `ChainManifest`, `WatchDog`, `ParticipantsAddedListener`, `StructureLink`, `KeyframesMap`, `SourceTypes`, `TaskFolder`, `BoundElementPropertyAst`, `ContextTransformInfo`, `NpmPublishClient`, `SymbolDataVisibility`, `CurrencyId`, `GitConfig`, `TransactionEventBroadcaster`, `ExtendedChannel`, `FormOptions`, `MutableMatrix44`, `RCloneFile`, `Turn`, `PlatformContext`, `TestContextCustom`, `ITaskWorker`, `MethodNext`, `IParamSignature`, `TSVideoTrack`, `PutRecordCommandInput`, `EnumDescriptorProto_EnumReservedRange`, `Commander`, `BigNumberish`, `ZonedMarker`, `SubnetDescription`, `AccessorCreators`, `VennDiagramProps`, `Travis`, `IRootScopeService`, `WalletName`, `Dialogic.DefaultDialogicOptions`, `TechniqueDescriptor`, `ResourceSettings`, `dGlobals`, `WritableStreamDefaultController`, `ForwardedRef`, `TBase`, `ScreenName`, `ApiParameter`, `NotificationMessage`, `IMouseEventTrigger`, `ErrorExpressionCategory`, `QueryParserListener`, `IProvisionContext`, `CustomMaterial`, `ScraperOptions`, `IIndexPattern`, `MovimientoModel`, `GX.TexGenSrc`, `DefinitionNode`, `AnalyzerNodeInfo`, `ThisParameterType`, `DaffCategoryFilterRangeNumeric`, `VRMBlendShapeGroup`, `RNNCell`, `FieldFormatsSetup`, `SocialTokens`, `PatternClassArgumentNode`, `LaunchConfiguration`, `messages.Envelope`, `LinterMessage`, `UserQuery`, `IModelReflectionData`, `MacroAction`, `HappeningsInfo`, `WorkRequestClient`, `vscode.ExtensionContext`, `EntityManager`, `TokenProps`, `WordMap`, `vscode.Terminal`, `ScopedKeybinding`, `INodeUi`, `StoryMenuItemProps`, `MailerService`, `Helper`, `EventSubscriptionCallback`, `OperatorUser`, `BottomNavigationTab`, `SurveyLogicType`, `request.SuperTest`, `RootParser`, `IConfigService`, `FabricEvent`, `ModelConfig`, `Payment`, `StellarRawTransaction`, `OpenYoloCredentialHintOptions`, `Utilities.EventWrapperObject`, `QueryValue`, `StructName`, `SuiteWithMetadata`, `MergeCSSProperties`, `LinkedContracts`, `ListenerHandler`, `ElementArrayFinder`, `NamespaceMember`, `ParsedParameters`, `PrimitivePropertyValueRenderer`, `TelegramBot`, `IMdcCheckboxElement`, `PropertiesMap`, `CreateEmailTemplateCommandInput`, `AnimationRange`, `IRuleApiModel`, `ISegment`, `SpecPage`, `InjectorService`, `Script3D`, `InitializeResult`, `Roots`, `XUploadNode`, `Result`, `ClientKeyExchange`, `DeleteAppInstanceCommandInput`, `VaultActivity`, `PathNodeItem`, `KeplrSignOptions`, `ScaleType`, `Module1`, `NumberWidget`, `DMMF.Field`, `RequestBodyMatcher`, `SOClient`, `keyComb`, `GraphQLOutputType`, `Models.CommandInput`, `ModuleBuilder`, `SlashArgRecord`, `UpdateGroup`, `NavigationStart`, `DatastoreType`, `StripeShippingMethods`, `ESLint`, `HeatmapData`, `CommentEntity`, `SelectMenuProps`, `RTCDataChannelEvent`, `TimestampsToReturn`, `ParsedResponseHeaders`, `EntitySystem`, `RecordingStream`, `IpRangeKey`, `DOMParser`, `LastError`, `DynamicDialogRef`, `CircleDatumAlternative`, `NodeBank`, `NamedCurveAlgorithms`, `GetCustomVerificationEmailTemplateCommandInput`, `XmlElement`, `ImageMetadata`, `NextRouter`, `BScrollConstructor`, `_STColumn`, `MatchmakerMatched_MatchmakerUser`, `IFaction`, `theia.Uri`, `SchemaRootKind`, `DChoice`, `DocumentMapper`, `RangeProps`, `PropertyRecord`, `ReturnStatement`, `CallAst`, `EncodedPart`, `LayerNormalizationLayerArgs`, `DeclarationParams`, `System_Array`, 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`MDCTextFieldLineRippleAdapter`, `SentryUser`, `QueryMode`, `Reminders`, `FieldName`, `StockItem`, `HydratedFlag`, `CallOverrides`, `RenameMap`, `ICustomClassUIMethod`, `Command`, `Path6`, `SessionWorkspace`, `AlphaConfig`, `HistoryLog`, `PlaceTradeDisplayParams`, `DataEventEmitter.EventDetail`, `ConvertedDocumentFilePath`, `GlobalTime`, `InjectionMap`, `CustomFont`, `DkrLevel`, `ListAccountsCommandInput`, `ToggleButton`, `IGroupSharingOptions`, `Vault`, `HelpCenterService`, `To`, `DeletePipelineCommandInput`, `CourseTask`, `Calibration`, `d.CompilerJsDoc`, `ZoneOptions`, `IQueryParameters`, `SetMap`, `IOperand`, `TimerState`, `AgentPubKeyB64`, `DAL.KEYMAP_KEY_DOWN_POS`, `Wall`, `SignalingClientEvent`, `requests.ListWorkRequestsRequest`, `TleParseResult`, `ParseTreePatternMatcher`, `requests.ListNetworkSourcesRequest`, `ClusterResource`, `peerconnection.Data`, `Content`, `messages.PickleTag`, `Emitter`, `ListRoutesCommandInput`, `AccessControl`, `ITransportConstructor`, 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`NamedCurveKeyPair`, `py.ScopeDef`, `ExtendableEvent`, `ApplicationConfig`, `AnalyticUnitId`, `RangeSelector.RangeObject`, `RemoteNode`, `ITests`, `DashboardId`, `MarkdownString`, `ParsedAcceptHeader`, `SettingsProperty`, `ResolvedDependencies`, `CallErrorTarget`, `PLSQLSymbolKind`, `DefaultOptions`, `Shader_t`, `Events.preframe`, `Sequelize`, `Scene`, `ResolvedRoute`, `BeanObserver`, `BackwardRef`, `FilamentSpool`, `IMatrix33`, `WriteableStream`, `EntityRemote`, `ComponentSingleStyleConfig`, `UsersServiceTest`, `OpenOrCloseListener`, `UpdateModelDetails`, `EventPluginContext`, `DataStream`, `INumberColumn`, `EntryModule`, `PrereleaseToken`, `AdaptFuncT`, `FreeStyle`, `TmpfileOptions`, `TestDtoFilter`, `CipherWithIds`, `ControllerEvent`, `SuiModal`, `KVStore`, `AttachmentRequest`, `IGetTimeLogReportInput`, `EventAggregatorService`, `types.UMLClassMember`, `MapMesh`, `Cookie`, `ITree`, `CollisionParts`, `GroupLocalStorage`, `ApplicationCommandData`, `ConsoleService`, `GoogleTagManagerService`, `EntityComponent`, `DIALOG`, `DropdownState`, `SNSNoAuthorizationFault`, `ContactLightweight`, `TodoStore`, `PopoverInitialState`, `PouchdbDocument`, `UniqueSection`, `d.OptimizeJsResult`, `CompletionEntryData`, `ValidationComposite`, `IFindQuery`, `PaginationComponentOptions`, `WalletInfo`, `FileEditActions`, `ScopedDeployment`, `AccessRule`, `PortalManager`, `ListRoomsRequest`, `MessageRecord`, `TransportStream`, `BackgroundColor`, `EthereumSignatory`, `IAgreementConnector`, `ResTable`, `FortaConfig`, `MockWindow`, `OperationGroup`, `NormalItalic`, `AddressService`, `ListDatasetsRequest`, `TilemapData`, `TransactionService`, `OrganizationEmploymentType`, `Getters`, `MalSeq`, `TFile`, `StreamerConfig`, `BattleModel`, `Endianness`, `Armature`, `UpdateArgs`, `RationalArg`, `CharacteristicSetCallback`, `UserProfileFactory`, `OptionInfo`, `FormData`, `Animatable`, `UIColor`, `AnimatorSet`, `StatFilter`, `Codec`, `UpdateResponderRecipeResponderRule`, `JavaScriptRenderer`, `ManagementAgentPluginAggregation`, `GetFreeBalanceStateResult`, `BuildVideosListQueryOptions`, `BindingElement`, `RegionInfoProviderOptions`, `EditableTextBase`, `PageInfoListItem`, `AnnotationsOptions`, `DeviceConfigIndex`, `CategoryService`, `RO`, `DailyApiResponse`, `NodeJS.EventEmitter`, `CompletionStatus`, `Stretch`, `OverpassElement`, `Association`, `SimpleChartDataType`, `DaffCategoryFilterEqualOptionFactory`, `JSON`, `RouteHandlerMethod`, `ListDeviceEventsCommandInput`, `PageLayout`, `FunctionLikeDeclaration`, `CommandPath`, `SQS.Message`, `React.ReactInstance`, `Constructable`, `WifiConfigureRequest`, `ChannelProperties`, `SvelteDocument`, `SecurityHub`, `PredicateWithIndex`, `JsonComposite`, `ListDomainsForPackageCommandInput`, `types.IDynamicOptions`, `BlockCompiler`, `ArgError`, `STPPaymentMethod`, `GoGovReduxState`, `MetricTypeValues`, `ButtonInteraction`, `IPartialLocaleValues`, `BreadcrumbsOptions`, `TabLocation`, `SurveyConfig`, `RequestMethods`, 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`Binding`, `SubscribeParams`, `BehaviorTreeNodeInterface`, `Room`, `MetadataAccessor`, `MapContext`, `AdjacentZones`, `Get`, `ts.NewExpression`, `i18n.IcuPlaceholder`, `ICommandDefinition`, `IKeyboard`, `Checkpoints`, `VerifiedHierarchy`, `EllipseEditOptions`, `tl.VariableInfo`, `AccountInfo`, `PluginResourceSettings`, `GesturesObserver`, `ethers.providers.FallbackProvider`, `ICandidateUpdateInput`, `ApplyAssetContext`, `UiButton`, `AnnotationState`, `NineZoneStagePanelPaneManager`, `CollisionScaleType`, `Graph2`, `SpatialCache`, `ThyDragHandleDirective`, `DataTableEntry`, `Finding`, `JavaDownloadRelease`, `PluginDescriptor`, `CreateResolversArgs`, `Timestamped`, `interfaces.Factory`, `MessagePort`, `MintGenerativeData`, `HydrateCacheOptions`, `PadCalculator`, `ElementType`, `teacher`, `TernarySearchTreeNode`, `Setter`, `OutgoingResponse`, `RunnerOption`, `ChatClientState`, `HTMLUListElement`, `PutRequest`, `WorkerManager`, `IRandom`, `ReadFileFailCallbackResult`, `PrimaryExpression`, `ShareTransferStore`, `BufferComposer`, `RenegotiationIndication`, `WebSiteManagementClient`, `SMTEntityDecl`, `DatatableColumn`, `PassThrough`, `Algebra.RootNode`, `ShipPlugin`, `EventService`, `styleProps`, `ExpressionLoader`, `FrameworkConfiguration`, `DeleteParams`, `FormatTypeFlags`, `TypesModule`, `ICurrency`, `Right`, `SimpleRecordInput`, `IHealthCheckResult`, `ParsedItem`, `ECInstancesNodeKey`, `DeleteConnectionResponse`, `Vector`, `ModuleSpecifier`, `EvaluatedScript`, `SslSupport`, `IonRouterOutlet`, `apid.VideoFileId`, `RGB`, `SnackbarAction`, `EdmxParameter`, `HistogramBucketAggDependencies`, `TextureSourceLoader`, `requests.ListDrgsRequest`, `ILocalValue`, `SetupContext`, `DialogflowMiddleware`, `MatDialog`, `FastifyInstance`, `TypeParameter`, `CanvasSystemIcon`, `BooleanLike`, `UiState`, `Unlisten`, `SVGDOMElement`, `MinMaxNormArgs`, `SecurityContext`, `FormBuilder`, `CommonWalletOptions`, `ICXMakeOffer`, `_PresignUploadRequest`, `IAllExecuteFunctions`, `d.PrerenderHydrateOptions`, `DataConverter.Type`, `p5.Vector`, `CallAdapterState`, `StructFieldInfo`, `InitConfig`, `SharedControlConfig`, `KeyValueCollection`, `ListServicePipelineProvisionedResourcesCommandInput`, `Bid`, `SVInt`, `coreClient.RawResponseCallback`, `DeclarativeCall`, `SFCStyleBlock`, `ISettingAttribute`, `ShapeViewModel`, `CreateMeetingCommandInput`, `Init`, `SupCore.RemoteClient`, `StaticDataView`, `DOMRectList`, `UpgradePolicy`, `DescriptorTypeResult`, `FindProsemirrorNodeResult`, `TreeOption`, `DebugProtocol.DisconnectResponse`, `GraphicOptions`, `IntCodeComputer`, `Vector3d`, `SpriteSheetSpacingDimensions`, `SelectListItem`, `IPermission`, `File`, `DefUse`, `XMLNode`, `TestLegacyLoanToken2`, `DynamicFormControlEvent`, `CompressedPixelFormat`, `TypeBase`, `ThemeBuilder`, `FormActionType`, `test.Test`, `requests.ListDrgAttachmentsRequest`, `IEthUnlock`, `RefreshTokenDto`, `HsvColor`, `Quakeml`, `Bound`, `AccountDoc`, `TranslateService`, `WizardForm`, `ClientUser`, `ReactSource`, `UniformRandom`, `AbiOwnershipTransaction`, `RTCSessionDescriptionInit`, `InterpolationStep`, `NodeResult`, `IParameter`, `JsonRpcPayload`, `Dialogic.State`, `BubleDataType`, `ResourceProps`, `PNG`, `AppHandler`, `ImageTileEnt`, `AudioProcessingEvent`, `SymmetricCryptoKey`, `XPCOM.nsXPCComponents_Classes`, `LitecoinSignedTransaction`, `GitLabFixtureClient`, `IUserWithRoles`, `ISourceNode`, `DefaultContentNode`, `DemoVariable`, `ObjectLiteralElementLike`, `NdArray`, `ValueProvider`, `MainState`, `CannonRigidbody3D`, `SchemaEnum`, `SaleorThemeColors`, `ISpecModel`, `paper.PointText`, `EuiValues`, `UrlType`, `UniqPrimitiveCollection`, `JwtHelperService`, `IFormItemTemplate`, `ContainerWithState`, `Instance_t`, `RheaEventContext`, `Geoset`, `ZoneLocator`, `TransactionContext`, `DsProcessorService`, `CredentialTypesClass`, `IAtomMvhd`, `ListViewCell`, `ScrollStrategy`, `Args`, `RedisCacheAdapterContext`, `DescribeEnvironmentsCommandInput`, `BeanProvider`, `ASTVisitor`, `ArticleEntity`, `ChatMessageWithStatus`, `VersionDataService`, `bigInt.BigInteger`, `SubstrateExtrinsic`, `Mocked`, `IsEqual`, `Signal`, `ICell`, `IFetchParams`, `UriMatchType`, `AdditionalDetailsProps`, `NbDialogRef`, `PosBin`, `NzTreeNode`, `DescribeDBParametersCommandInput`, `DBArg`, `Credential`, `GrantIdentifier`, `d.DevServerContext`, `UnitFormService`, `MUserWithNotificationSetting`, `Mysql`, `ParseConfigFileHost`, `PvsProofCommand`, `UnsubscribeSnapshot`, `DeleteFleetCommandInput`, `requests.ListSteeringPolicyAttachmentsRequest`, `AnimatedAddition`, `AttachmentOptions`, `TransferListOptionBase`, `AlertController`, `StaticJsonRpcProvider`, `EndPoint`, `PaginatedList`, `TaskOptions`, `LibraryItem`, `ThunkResult`, `StringMap`, `SavedMultisigEntry`, `CancelRequest`, `NavigationViews`, `SpaceID`, `FILTERS`, `ResponderDimension`, `ProductCategory`, `ExcaliburGraphicsContext`, `LoadedVertexLayout`, `TransferState`, `GetConfigurationSetCommandInput`, `btVector3`, `OperationInstance`, `NetworkType.Mainnet`, `IAlbum`, `ControlledProp`, `BooleanResponse`, `CSSProps`, `CreateTodoDto`, `FilterExpressionNode`, `GetPrTimelinePayload`, `RPC`, `ArgResult`, `IMenu`, `EntityEffects`, `MessageHandlerContext`, `DaffAddress`, `TickSignal`, `UpdatePipelineCommandInput`, `TSInterfaceDeclaration`, `PythonPreview`, `Conv2DTranspose`, `ILogParseHooks`, `HitCircle`, `USBDevice`, `Hint`, `PrivateApiImpl`, `TimetableSession`, `TeslaStyleSolarPowerCard`, `SRWebSocket`, `sdk.VoiceProfileClient`, `IDocumentSnapshot`, `DataValue`, `ScannedPolymerProperty`, `CreateApplicationCommand`, `EmbeddablePersistableStateService`, `TiledTSXResource`, `TableService`, `KeyInKeyof`, `TableConfig`, `MongoClientConfig`, `SchemaNode`, `PivotQuery`, `ChatCompositeProps`, `IThemedToken`, `ReviewerEntity`, `TaskTypeDictionary`, `IsometricGraphic`, `TestRaster`, `EnvironmentRecord`, `Compute`, `CompilerOptions`, `RobotsByNameMap`, `ProtocolPeerInfo`, `VoilaGridStackWidget`, `ThyDialog`, `HeaderTransformer`, `bigInteger.BigInteger`, `JupyterFrontEnd`, `CalculateBoundsOptions`, `ApplicationCommandRequest`, `WexBimGeometryModel`, `CSR`, `A8`, `PerpV2Fixture`, `DocumentRange`, `common.EventData`, `ITool`, `TestDTO`, `KMSKey`, `OscillationState`, `IColorV`, `TypeVarMap`, `DeltaType`, `NotSkeletonDeep`, `DeleteStudioCommandInput`, `StringAttribute`, `SankeyDiagramDataView`, `VnetInfoResource`, `TriDiagonalSystem`, `DemoBlockType`, `ProxyAccessor`, `DecimalSource`, `RecordModel`, `CommitData`, `BetterMap`, `IThrottlerResponse`, `ManagerConfig`, `DemoExecutor`, `F1TelemetryClient`, `ts.Diagnostic`, `AuthMachineEvents`, `StateAccount`, `GridItemEvent`, `AllDecorators`, `RenderedItem`, `StatusFieldProps`, `TEElement`, `Models.IPositionStats`, `DirectoryTree`, `DaffCartAddress`, `IProducer`, `OperationArgs`, `ForwardDefinition`, `DocumentWrapper`, `Alternatives`, `IPlDocTemplate`, `RouterNavigation`, `HoveredResult`, `SetStateAction`, `ListenDecorator`, `Activation`, `EncryptedMessage`, `CreateChannelParams`, `ColumnConfigArg`, `ISharedObjectRegistry`, `SuperResolutionConfig`, `EfsMetricChange`, `ComponentVariablesPrepared`, `LendingReserve`, `PutFileContent`, `ImportedConfiguration`, `IPNResponse`, `SelectionOptions`, `IRECAPIClient`, `ResourceSpans`, `WriteLeaderboardRecordRequest`, `IFormSectionData`, `SetupFunction`, `TestTree`, `TokenFetchOptionsEx`, `IC`, `NineStar`, `VercelRequest`, `Physics2DDirectBodyStateSW`, `ElasticsearchClient`, `IMetric`, `CdkStepper`, `_OIDCConfiguration`, `authors.Table`, `BrowseDescriptionLike`, `Assignment`, `TestComponentBuilder`, `PlayerInstant`, `RegionType`, `EntitiesState`, `ResourceNotFound`, `HsAddDataOwsService`, `HttpErrorContext`, `AbstractMesh`, `ApplicationSummary`, `MatSidenav`, `DescribeRegionsCommandInput`, `AllTokens`, `Drawer`, `PolicyBuilderPaths`, `VisEventToTrigger`, `VNodeData`, `CallbackList`, `MatSort`, `FlattenedXmlMapCommandInput`, `DiscordMessageActionRow`, `ConditionalTransferCreatedEventData`, `SavedObjectMetaData`, `XUL.chromeDocument`, `DslQuery`, `MonitoringContext`, `HmrContext`, `SimpleUnaryOperation`, `TransactionParams`, `HMAC`, `ChildProcessByStdio`, `ResponseToolkit`, `IChangeTarget`, `CohortRepresentation`, `TypeConditionRestriction`, `ReshapePackedProgram`, `DBCoreTable`, `ILibraryRootState`, `PolicyViolation`, `LightGroupState`, `DaffCartOrderReducerState`, `Authenticate`, `TPluginSettingsProps`, `SingleKey`, `TextRenderParameters`, `TensorLike1D`, `IPed`, `SidePanelProps`, `SubmissionObjectEntry`, `GetArgs`, `TypeErrors`, `TSchema`, `MaxPooling2D`, `LiteralValue`, `AnnotationObject`, `IListenerRuleCondition`, `Events.pointerdragenter`, `XUL.browser`, `EnumValueDescriptorProto`, `Tlistener`, `ModelCtor`, `OperationNotPermittedException`, `ComicDownloaderService`, `AggsItem`, `IRoundState`, `DataRequestContext`, `QueryConstraint`, `TreeView`, `DockerImageName`, `FargateTaskDefinition`, `RenderableProps`, `SpellList`, `AudioMixObserver`, `IFunctionTemplate`, `NodeCache`, `WidgetAdapter`, `AssetState`, `OrderInfo`, `TraceCallback`, `DeleteObjectRequest`, `AttributeFlags`, `DownloadProgress`, `SlsConsoleFile`, `ReplyPackage`, `IMediatorMapper`, `VirtualWAN`, `Evaluation.Response`, `Replacement`, `MbMap`, `CreateAppInstanceUserCommandInput`, `BooleanSchema`, `IntermediateTranslationFormat`, `CLIOptions`, `LegendData`, `DpcMgr`, `IncompleteFormatStringSegment`, `ASTValidationContext`, `AnchorMode`, `SimpleState`, `AutoSuggestData`, `PathEndCoordinates`, `ManagedBackupShortTermRetentionPolicy`, `WebVRSystem`, `EngineResults.SchemaPush`, `BasicPoint`, `PatientService`, `StringInput`, `ForgotPasswordAccountsValidationResult`, `Villain`, `HTMLSuperTabButtonElement`, `UICollectionViewCell`, `InfraConfigYaml`, `FunctionInfo`, `IBrew`, `MyWindow`, `PicassoConfig`, `RouterTask`, `FlexLength`, `EPeopleRegistryState`, `Clickable`, `GetBranchCommandInput`, `DecimalPipe`, `SetIpAddressTypeCommandInput`, `ResourceDataGridWrapper`, `FunctionTemplate`, `IMatrix44`, `TransactionError`, `Docfy`, `sdk.BotFrameworkConfig`, `UpdateRoomCommandInput`, `collectSignaturesParams`, `Favor`, `ReplaySubject`, `InterfaceWithoutReturnValue`, `IStyleCollection`, `HsAddDataLayerDescriptor`, `DynamicFurParam`, `requests.ListVmClusterPatchesRequest`, `IncompleteUnescapedString`, `IPeer`, `SortedSetStructure`, `IHud`, `TreeNodesType`, `requests.ListManagementAgentPluginsRequest`, `GpuStats`, `FabricEventBase`, `CookiecordClient`, `ResultInfo`, `OrgEntityPoliciesPlan`, `DisposableCollection`, `ImageViewerState`, `IParseResult`, `SwaggerPath`, `DescribeAccountLimitsCommandInput`, `AutoRestExtension`, `NotificationEvent`, `ProviderProps`, `B0`, `TransformKey`, `WithElement`, `TEventType`, `ContractsService`, `Q.IPromise`, `ISO8601Date`, `MActorSignature`, `QueryObject`, `VPosition`, `SubstrateNetworkParams`, `Breakpoints`, `PathTransformer`, `ValidateArgTypeParams`, `BufferFormatter`, `CryptoFunctionService`, `MeasureStyle`, `vscode.WebviewView`, `RuleDescription`, `KeyEvent`, `DropInfo`, `VertexData`, `cdk.Construct`, `GfxRenderPipeline`, `AnimationCurveKeyframe`, `VirtualCell`, `socketIO.Server`, `EventProperties`, `A11ySettings`, `requests.ListCatalogPrivateEndpointsRequest`, `RenderPassId`, `IImportedArmy`, `Replacer`, `LayerId`, `UITextField`, `FormatErrorMetadata`, `PathfindingGraph`, `SQLError`, `S1Sale`, `ITimezoneOption`, `SavedReport`, `Node`, `JwtVerifier`, `ToastyService`, `YearToDateProgressPresetModel`, `IndexPatternField`, `AxisStyle`, `ethers.ContractTransaction`, `DashboardContainerFactory`, `IDateRangeActivityFilter`, `ResultPath`, `TriggerProps`, `ThLeftExpr`, `LengthPrefixedList`, `DragManager`, `LocationState`, `ServerSideEncryptionConfiguration`, `AnalysisEnvironment`, `ShadowTarget`, `ParticleSystem`, `ComposibleValidatable`, `GrowableBuffer`, `SinglelineTextLayout`, `CategoryCollectionStub`, `ResourceAction`, `displayCtrl.IInitConfig`, `MembersActions`, `React.Dispatch`, `DocumentSnapshot`, `DeploymentType`, `ProjectServer`, `Setup`, `TimedParagraphItem`, `AccountMeta`, `ast.ClassDeclaration`, `SessionAuthService`, `Symmetry`, `CVDocument`, `TypographyOptions`, `ContextCarrier`, `SecurityCCCommandEncapsulation`, `LayerProperties`, `CbExecutionContext`, `Id64String`, `Mod`, `Remarkable`, `DaffAccountRegistrationFactory`, `Decoder`, `TaskLibAnswers`, `FieldAccessor`, `GetOwnPropertyDescriptors`, `SurveyLogicItem`, `FileWatcherEventKind`, `SemVer`, `InjectionValues`, `INavFourProp`, `Original`, `BadgeSampleProps`, `PluginInitializer`, `InterpreterOptions`, `PiInterface`, `NavigableMap`, `ObstaclePort`, `WriteItem`, `NodeContext`, `TiledLayer`, `Grid3D`, `requests.ListListingsRequest`, `TrackList`, `ScaffoldType`, `ITagUi`, `TypeFacts`, `LoginEntity`, `UpdateArticle`, `ParsedCode`, `DescribeDataSourceCommandInput`, `sst.App`, `RelativePath`, `SerializedPrimaryKeyOptions`, `ClusterProvider`, `UISettingsStorage`, `IndexedMap`, `Resolver`, `ForwardingStatus`, `fpc__ProcessName`, `msRest.OperationQueryParameter`, `ng.IHttpProvider`, `OverflowT`, `PageBoundingBox`, `PostModel`, `TEasingFn`, `AnalyzerLSPConverter`, `DBCore`, `JavaMethod`, `VisualizeTopNavProps`, `IAccessInfo`, `MappingFactor`, `EndOfLineState`, `GatsbyConfig`, `ListDevicesRequest`, `PrivateProps`, `ICommandParsed`, `MarkerClustererOptions`, `SelectAmount`, `ChatConverseState`, `StringStream`, `Repl`, `ActionByType`, `ProtocolMessage`, `InputField`, `GfxBufferUsage`, `TweetResolvable`, `Bin`, `Mjolnir`, `NodePath`, `GrainPlayer`, `ColorService`, `NgOption`, `tr.commands.Command`, `CustomEndpointDetails`, `SecureCookieOptions`, `BarChartBarMesh`, `VectorSource`, `WorkingDirectoryInfo`, `ExampleRecord`, `ControlFormItemSpec`, `AlgPartDecoration`, `Fields`, `TestImageProps`, `DeviceFormPostData`, `CSharpNamespace`, `ApplicationTypes`, `EmailConfirmation`, `LoadDataParams`, `RequestAction`, `VirgilCrypto`, `ImportLookup`, `Attributes`, `HydrateComponent`, `PromiseSettledResult`, `PartitionLayout`, `EmbeddableFactoryProvider`, `ICnChar`, `IMinemeldConfigService`, `SyntaxCheck`, `FileSystemError`, `StringContent`, `Piece`, `HypermergeNodeKey`, `IDriverType`, `MDCSelectFoundation`, `GitAPI`, `AuthenticationStrategy`, `egret.TouchEvent`, `Utilities`, `TemplatePositionContext`, `MDCTextFieldLabelAdapter`, `StitchesComponentWithAutoCompleteForJSXElements`, `Hermes`, `CidConfig`, `IEventListener`, `UITabBarItem`, `SafeHTMLElement`, `ExternalData`, `Ptr`, `JitsiRemoteTrack`, `GameModel`, `RadixAtomObservation`, `MDCShadowLayer`, `ObserverActionType`, `NotifyOptions`, `GfxRenderHelper`, `ParsedUrl`, `NonNullExpression`, `messages.PickleStepArgument`, `VariableTable`, `TestStepResult`, `RelationInfo`, `UniversalCookies.Options`, `Addressable`, `SocketCustom`, `ColorRef`, `KeyframeNodeList`, `ShaderData`, `LCDClient`, `PartyPromote`, `LoggerConfigType`, `EasJsonReader`, `NameValuePair`, `FileSet`, `AssemblerQueryService`, `ApiMockRoute`, `RadioButtonComponent`, `NodeItem`, `GroupProblemData`, `ElementContainer`, `IParser`, `MovieDAO`, `VersionInfo`, `BackendContext`, `Stack.Props`, `TokenData`, `ApiEditorUser`, `CircuitMetadataBuilder`, `LSTMState`, `KeyRowEvent`, `changeCallback`, `MathBackendCPU`, `Voice`, `ParsedCommand`, `SetAccessorDeclaration`, `CLI_COMMAND_GROUP`, `NormalizedOutputOptions`, `OverviewSourceRow`, `PluginBuilderLens`, `CommandRole`, `XhrFactory`, `PresetMiniOptions`, `ElementInlineStyle`, `Merger`, `DAL.DEVICE_ID_RADIO_DATA_READY`, `SecuredSubFeature`, `DeleteEmailIdentityCommandInput`, `RawBuilder`, `VueFilePayload`, `cheerio.Cheerio`, `BindingContext`, `RenderableStylesheet`, `NodeMap`, `ShareArgs`, `SearchInterceptorDeps`, `ProperLayeredGraph`, `NodeTag`, `Coder`, `LocationItem`, `ListWorkflowsCommandInput`, `RollupCommonJSOptions`, `RepoError`, `DiagnosticChangedEventListner`, `PresSlide`, `LodashDecorator`, `CreateStudioCommandInput`, `PreviouslyResolved`, `TimeType`, `ChromeExtensionService`, `WindowComponent`, `LocationService`, `_THREE.Vector3`, `DatabaseSchemaImpl`, `WeightsManifestGroupConfig`, `SearchSourceOptions`, `AppServiceRegistration`, `APIGatewayEvent`, `LineProps`, `StoredTx`, `ExecFileException`, `HunspellFactory`, `CancelJobRequest`, `pxt.PackageConfig`, `SeparationInfo`, `TimeRangeBounds`, `StoreBase`, `RevalidateEvent`, `TrackEvent`, `ConcatInputs`, `d.Diagnostic`, `sst.StackProps`, `MappedField`, `PredicatePlugin`, `RemoteEndpointConfiguration`, `JobConfig`, `IndicesOptions`, `fetch.Response`, `CoreTypes.dip`, `PeopleSearchScroller`, `types.IActionInputs`, `LintMessage`, `HTMLLIElement`, `StudentBasic`, `IUserUpdateInput`, `GenerateFunctionOptions`, `NativeAppStorage`, `Mixin`, `JsxExpression`, `DataViewsService`, `SpringSequenceStep`, `ServiceConfig`, `GXMaterialHacks`, `PluralType`, `ISqlRow`, `NativeEventEmitter`, `Multicall`, `ListPatternType`, `IslandsByPath`, `xyDatum`, `FirebaseMachineLearningError`, `CustomConfigurationProvider1`, `ITextAndBadge`, `FlagValue`, `RecoilValue`, `KvPair`, `MapEntry`, `TaskOperations`, `SchemaFormOptions`, `SchemaDefinition`, `ICAL_ATTENDEE_STATUS`, `GroupPanel`, `TestArgs`, `FluidObjectSymbolProvider`, `NodePoolPlacementConfigDetails`, `FieldDescriptorProto`, `ReadableFilesystem`, `IEmeraldVault`, `ResolverMethodOpts`, `DocumentRef`, `DeviceConfigService`, `IFieldInfo`, `EventQueue`, `XyzaColor`, `RuleAttribute`, `FSMState`, `UpdateApplicationRequest`, `CoinSelectInput`, `ITableOfContents`, `TourStep`, `AlternativesSchema`, `UsageCollectionSetup`, `ClassPartObject`, `TransferEvent`, `BehaviorTreeBuilder`, `RtlScrollAxisType`, `Circle`, `Revision`, `JsonaProperty`, `TooltipAndHighlightedGeoms`, `SessionID`, `IUserIdentity`, `CasCommand`, `OptionElement`, `TraverseOptions`, `AzureWizard`, `EditableHippodrome`, `IValues`, `TransitionSettings`, `MyEpic`, `SubscribeFunction`, `VariablesManager`, `ApplicationSubmission`, `DeleteReportDefinitionCommandInput`, `MtxGroup`, `DataHolder`, `CKB`, `IBinaryTreeNode`, `KeyboardLabelLang`, `BoardService`, `GfxTexFilterMode`, `ReflectedType`, `Streamer`, `BuilderState`, `RpcSocket`, `Wechaty`, `CardRenderer`, `GetDomainRecordsRequest`, `SessionId`, `EntityId`, `ParsedSearchParams`, `CurrentUser`, `cback`, `RolandV8HDConfiguration`, `IRange`, `DataModifier`, `SpringSequence`, `SavedState`, `IIdentifier`, `ScryptedDevice`, `GraphQLRequestEnvelope`, `ExecutionArgs`, `IReq`, `TimeService`, `_TimerCondition`, `CustomEditor`, `ReactTestInstance`, `NoExtraProps`, `DateType`, `ThStmt`, `patch_obj`, `schema.Entity`, `CheckFunc`, `PlanetApplication`, `IParameterValuesSource`, `ForumAction`, `ITriggerPayload`, `FireClient`, `MemoryStream`, `BleepGeneric`, `IEventDispatcher`, `DeleteJobRequest`, `PiEditor`, `LastValueIndexPatternColumn`, `BitcoinCashBalanceMonitorConfig`, `requests.CreateProjectRequest`, `IDockerComposeOptions`, `WastePerDay`, `IProviderOptions`, `NullLogger`, `NpmConfig`, `EventsClientConfiguration`, `Brand`, `IEscalation`, `StatefulDeviceManager`, `SearchFilterState`, `WarriorLoader`, `AppStateStore`, `AccountRefresh_VarsEntry`, `ITicks`, `ESTreeNode`, `LMapper`, `ConfigDefinition`, `RumPublicApi`, `ITimeLogFilters`, `IApolloServerContext`, `TerminalProviderSeverity`, `UseSRTP`, `ApiAction`, `USBInTransferResult`, `StoreState`, `BandViewModel`, `CLI`, `LogAnalyticsSourceExtendedFieldDefinition`, `NormalizedOption`, `NewExpression`, `ConfigBundle`, `FormContextValues`, `MockElectron`, `PortRecord`, `EtcdOptions`, `MacroMap`, `VerifierOptions`, `HexLiteralNode`, `BluetoothError`, `LessParser`, `ConfigSetExecutionGroup`, `PathlessInputOperation`, `CliFlags`, `Tracker`, `EnvironmentAliases`, `RedisTestEntity`, `NugetPackage`, `GroupNode`, `ProgressCb`, `ViewTest`, `JsxAttributeLike`, `MotionValue`, `ToggledFiltersState`, `HTMLTextAreaElement`, `CSSInterpolation`, `ISendingUser`, `MockBackend`, `AST.ArrayAST`, `RTCIceCandidate`, `HierarchyRequestOptions`, `IFileEntry`, `HTMLAudio`, `DefaultEditorSideBarProps`, `AuthSettings`, `TodoListApplication`, `UseStore`, `ExecAsyncResult`, `IFilePane`, `IResultSetValue`, `ServiceConfigDescriptor`, `FiltersBucketAggDependencies`, `NotificationRepository`, `FindTaskQuery`, `ComparisonFunction`, `NetworkEndpointType`, `glTF.glTFNode`, `FacemeshConfig`, `RedisModules`, `UseFilterManagerProps`, `FormatRange`, `FontVersion`, `OutputSelector`, `TestTerminal`, `DeployedWithoutEmailWallet`, `GraphState`, `IDynamicValues`, `IResolvers`, `OutputStream`, `obj`, `INavigationFeature`, `LegendSpec`, `RelayerUnderTest`, `ThemeCreator`, `RecipientAmountCsvParser`, `IThunkAction`, `StatusBarItemsManager`, `RawConfigFile`, `ThemeLoadOptions`, `HEventType`, `CodedError`, `ComponentNode`, `SavedQueryService`, `Harmony`, `IExecutableContext`, `TableOfContents`, `MdDialogConfig`, `DocumentedError`, `DynamicAlternative`, `JPattern`, `StringKeyOf`, `MutationFn`, `DiezTypeMetadata`, `ReadValue`, `UIGestureRecognizer`, `CommandControlMessage`, `GuaribasAnswer`, `StyleMapping`, `SystemRequirement`, `EventDetails`, `UnionAccumulator`, `TypeOrmModuleOptions`, `IInsertInput`, `MiddlewareOptions`, `CardSpace`, `SongBundle`, `SlideElement`, `PropertyMap`, `DiscoverServices`, `IChangedArgs`, `KxxRecordBalance`, `VirtualFileInterface`, `DateRangePickerProps`, `SvgDebugWriter`, `social.InstancePath`, `DayGridWrapper`, `ManagerOptions`, `RemoteArtifact`, `SerializationStructure`, `LayoutRectangle`, `Border`, `GetIntegrationResponseCommandInput`, `GPGPUContext`, `BigDecimal`, `UpdateUserCommand`, `ComputedRef`, `IFormFieldValue`, `PluginStreamAction`, `AbstractViewer`, `DeleteRegexPatternSetCommandInput`, `PushTransactionArgs`, `JobMessage`, `SpaceFilter`, `AsyncPipeline`, `StringLiteralUnion`, `PrefetchIterator`, `QueryError`, `SearchConfigurationService`, `TaskManagerDoc`, `SAXParser`, `BlockNumberUpdater`, `MouseUpEvent`, `AnimatorRef`, `KPuzzle`, `HelmetData`, `ToggleProps`, `SentPacket`, `WebApiConfig`, `oicq.Client`, `CombinedText`, `IAutorestLogger`, `util.StringEncoding`, `logger.Logger`, `transcodeTarget`, `T`, `GithubClient`, `IFileBrowserFactory`, `alt.Vehicle`, `UseMetaStateOptions`, `OptionalIdStorable`, `ModuleJSON`, `IMaterialPbrMetallicRoughness`, `RuleScope`, `OutputBundle`, `ISubsObject`, `SortOptions`, `ProxyController`, `DownloadedBinary`, `IJSONSchema`, `AlignValue`, `OnEventCallback`, `SignKeyPair`, `OutputTargetDistLazyLoader`, `OptionType`, `ISharedMap`, `SCondition`, `IDocumentAttributes`, `pxtc.CompileResult`, `ConditionalTransaction`, `DownloadedFiles`, `TargetGraphQLType`, `IOneClickAppIdentifier`, `ControllerHandlerReturnType`, `EMailProcessingStatus`, `ComponentOpts`, `NgModuleFactory`, `AjvFactory`, `MediaDescription`, `UVSelect`, `PublishData`, `OperationSupportMatrix`, `ServerError`, `IStyledComponent`, `ExperimentSnapshotDocument`, `DiezType`, `ChooseActionStateMachine`, `LED`, `StopJobCommandInput`, `ArgsDescriptions`, `ToolbarTheme`, `ContractCaller`, `NormalizedTxBitcoin`, `GenericParameter`, `ESTree.Node`, `CacheObject`, `CompilerWorkerTask`, `XPlace`, `HandleActionSharedParams`, `JobRun`, `CdkStep`, `PlacementOptions`, `ReviewComment`, `Org`, `ImportPath`, `ReferenceCallback`, `BlockBlobClient`, `CustomPropertySetUsage`, `ResourceTimeGridWrapper`, `DriveManagerContract`, `CatchupToLatestShareResult`, `firebase.User`, `WithIndex`, `CancelTokenSource`, `CategoriaProps`, `NbThemeService`, `ISuite`, `BasicPizzasProvider`, `AuthenticationType`, `FlamelinkFactory`, `NumberSystemType`, `ImageStore`, `LuminanceSource`, `WithNode`, `S3Location`, `RtspSession`, `AttributeValue`, `Teacher`, `IZ64Main`, `FieldQuery`, `ts.TypeReference`, `LimitLine`, `ICamera`, `PubRelease`, `GetInfoResult`, `MockImportRegistry`, `IChannelDB`, `ApiRecord`, `CardListItemType`, `TemplateDeserialized`, `GitPullRequest`, `IGitManager`, `TypeDeclaration`, `NSVElement`, `WebDNNWebGPUContext`, `SankeyDiagramSettings`, `GridItemData`, `UdpTransport`, `TempStats`, `GridOptions`, `LogParser`, `CldFactory`, `VideoStreamRendererViewState`, `RowContext`, `FileLocationQuery`, `GoalSettingsService`, `ParjsResult`, `ITokenRequestOptions`, `CellRange`, `SmallMultipleScales`, `StepResultGenerator`, `WithPromise`, `ts.server.PluginCreateInfo`, `TextBox`, `ProjTreeItem`, `glTF1`, `Checkout`, `NavigationContainer`, `PathExpression`, `ProtoKeyType`, `ConstantsService`, `IQueryFeaturesOptions`, `InitiateAuthResponse`, `TextureSource`, `GX_Material.GXMaterialHacks`, `VisualizeServices`, `model.TypeName`, `DragDropRegistry`, `SortKeyRule`, `PTestNode`, `IKeyCombo`, `ScanResult`, `TranslationItem`, `BinaryOperatorToken`, `TypeIdentifier`, `ECDH`, `uint32`, `StyleBuilder`, `InlineVariable`, `OperationTypeNode`, `PTPDataView`, `SingleValueProps`, `GX.BlendMode`, `MutableImageRef`, `VariantAnnotationSummary`, `CatService`, `StatsNode`, `HALLink`, `BaseSourceMapTransformer`, `UserTie`, `FakePromise`, `LiteralShape`, `RSAPublicKey`, `SendMessageFn`, `ImageUrlTransformationBuilder`, `PromiseRes`, `Applicative4`, `ApplyGlobalFilterActionContext`, `TimefilterConfig`, `IPageProps`, `MessengerTypes.Message`, `UploadResult`, `requests.SearchListingsRequest`, `DoorLockCCConfigurationSet`, `GenericTestContext`, `AppManager`, `GameState`, `ImportMode`, `ViewCommon`, `Crawler`, `LastFmApi`, `pingResponse`, `ISearchStrategy`, `IPositionCapable`, `WirelessMode`, `ResultSet`, `LogConfig`, `SortedArray`, `PluginName`, `JsCodeShift`, `ITaskContainer`, `ObjectContaining`, `SizeConfig`, `BodyDefinition`, `MkDirOptions`, `CycleDimension`, `GetInstanceProfileCommandInput`, `IPluginData`, `DeleteStorageObjectId`, `Occurrence`, `RequestDetailsProps`, `ColorPickerService`, `GraphQLInputFieldMap`, `PointStyleAccessor`, `TypeConstructionContext`, `ITeam`, `TensorWithState`, `Web3Service`, `SubmitHandler`, `io.Socket`, `AreaUI`, `ListEndpointOptions`, `ListMemberAccountsCommandInput`, `IModule`, `Box3`, `CPlusPlusRenderer`, `RawNavigateToItem`, `ShareCallbackFunction`, `CompositeMetric`, `AtomicAssetsContext`, `LabelStyle`, `MultiRingBuffer`, `GetExperimentCommandInput`, `QueryList`, `CreateBucketRequest`, `CustomDomComponent`, `Monad1`, `requests.ListIdentityProvidersRequest`, `WordCache`, `GLTFResource`, `AuditAssertion`, `SongData`, `UserProps`, `UUID`, `RouterLoaderOptions`, `ESTree.MethodDefinition`, `HistoricalEntityData`, `KyselyPlugin`, `CompletionItemData`, `SchemaField`, `EffectDef`, `Array`, `IHDPreviewState`, `FileFlatNode`, `HierarchyDefinition`, `ActionsSdkConversation`, `IAppVolume`, `SoundChannel`, `MockCustomElementRegistry`, `UpdateVolumeCommandInput`, `ModalContextProps`, `RigConfig`, `MyItem`, `ICoordinates3d`, `BindingHelpers`, `CLM.ExtractResponse`, `CommandClassDeserializationOptions`, `Worker`, `DataTransferEvent`, `CubeTexture`, `DeployProxyOptions`, `ErrorMark`, `GeoPath`, `IndexedCollectionInterval`, `DataVariable`, `Truffle.Contract`, `Tasks`, `AccountConfig`, `TimelineTrack`, `Event24Core`, `Renderable`, `GanttUpper`, `SteeringPolicyAnswer`, `API.IMiscInfos`, `ChannelBytes`, `CompletionInfo`, `DownloadedImage`, `GridStackModel`, `CfnExperimentTemplate`, `ValidatorResult`, `InstanceConfiguration`, `TestClassesVariant`, `LanguageClient`, `HOC`, `Tipset`, `GX_VtxDesc`, `ApiTreeItem`, `AlreadyExistsException`, `SSM`, `Offer`, `OptionDetails`, `protocol.FileLocationRequest`, `PubkeyInfo`, `InjectorContext`, `IInspectorRow`, `ImagePipe`, `LineBatch`, `AlertResult`, `InputRule`, `EditorState`, `MiddlewareConsumer`, `JsPsych`, `SandDance.VegaDeckGl.types.VegaBase`, `AuthUtilsService`, `JacksonError`, `GeneratePrivateKey`, `DiagramMaker`, `ConstantAst`, `Angulartics2IBMDigitalAnalytics`, `SystemModule`, `RuleGroup`, `DateFormatterFn`, `MatchPairsOptions`, `UtilityNumberValue`, `WorldObject`, `CreditCard`, `MessagesBag`, `Buff`, `FileOverwriteOptions`, `ScanOptions`, `StringFormat`, `AccessLog`, `ExpoConfig`, `requests.ListDrgRouteTablesRequest`, `X12FunctionalGroup`, `USBEndpoint`, `integer`, `HotkeysEvent`, `Getter`, `TestInstance`, `SafeSignature`, `DefaultEditorControlsProps`, `BuildingState`, `PaginateQuery`, `Mongoose.Model`, `StringLookupMap`, `CssDimValue`, `WindowsLayout`, `ButtonDefinition`, `DoneFn`, `GroupId`, `EngineArgs.SchemaPush`, `CreateTestRendererParams`, `LegacyCompilerContext`, `ServerSyncBufferState`, `AppAPI`, `SnackbarContext`, `Knex.Config`, `EventActionHandlerCallableState`, `ToastButton`, `IEmployeeStatisticsHistoryFindInput`, `GfxMipFilterMode`, `InteractionEvent`, `BeforeInstallPromptEvent`, `IOdataAnnotations`, `PointerType`, `NavLink`, `Export`, `GlobalUserData`, `Octant`, `StandardEvents`, `ValuesStoreParams`, `RequestMatcher`, `RPCClient`, `MotionData`, `DataProxyErrorInfo`, `MessageAction`, `IComponentComposite`, `ReportBuilder`, `HashConstructor`, `GitTag`, `LinkComponent`, `AssertionError`, `IPropertyTypeValueDescriptor`, `IModelAppOptions`, `SortingOption`, `DocumentHighlight`, `GooglePlus`, `ECClass`, `ReadModelMetadata`, `IGetPaymentInput`, `MediaUploadForm`, `ISerialFormat`, `SurfaceLightmapData`, `ArticleProps`, `JobTrigger`, `AbstractValue`, `PixelLineSprite3D`, `TransitionSpec`, `MDL0_NodeEntry`, `PreQuestInstance`, `SceneStore`, `Compartment`, `WithId`, `FactRecord`, `BitBuffer`, `ThroughputSettingsGetResults`, `JsDocAndComment`, `ACLCanType`, `ControllerData`, `IViewPort`, `ActionDefinition`, `PageBlobGetPageRangesResponse`, `ApplicationEventData`, `PrivateApi`, `ReactiveEffectRunner`, `AutoScalingConfigurationSummary`, `BSPBoxActor`, `IEnhancer`, `StackGroupPath`, `ScalarType`, `InputConfig`, `Consultant`, `ContentDimensions`, `Arg0`, `AudioPlayer`, `ConnectionUI`, `UpdateFn`, `BackgroundPageStyles`, `ARUIViewOptions`, `DefaultInspectorAdapters`, `SettingsOptions`, `BindingInfo`, `RollingFileContext`, `ItemSection`, `HttpResponseBase`, `JsonRpcParams`, `ListPicker`, `DynamoDB.BatchGetItemInput`, `FileSystemResolver`, `InvariantContext`, `RemoteResource`, `IKeypair`, `DeviceConfigIndexEntry`, `BottomNavigationItem`, `CommentStateTree`, `BatchResponse`, `CustomLocale`, `GeolocationPosition`, `Pin`, `IRestApiResponse`, `NPCActorItem`, `HierarchyNode`, `FenceContext`, `CanvasView`, `TReturnType`, `ISelectOption`, `ITokenParser`, `FaunaTime`, `FlowTreeTopicNode`, `ReactPDF.Style`, `LiteralReprAll`, `ModelState`, `KeysToCamelCase`, `BoardDoc`, `IntrospectionInputValue`, `TabInstance`, `DispatchByProps`, `WglScene`, `CountService`, `ColorSwitchCCGet`, `IWinstonData`, `Wins.RankState`, `SparseMatrix`, `KeyBindingProps`, `MagitChange`, `ReportingCsvPanelAction`, `ScaledUnit`, `ICommands`, `HsAddDataUrlService`, `d.CollectionManifest`, `AnalyzerEntry`, `TabItemSpec`, `SankeyLink`, `textViewModule.TextView`, `CharacterClass`, `GeometryContainmentRequestProps`, `CanvasEngine`, `VcsAccountDatabase`, `getSubAdapterType`, `WidgetDef`, `IDataFilterInternal`, `BinanceWebsocket`, `ModelPrivate`, `VisConfig`, `BluetoothScale`, `TypeHierarchyItem`, `requests.ListVolumesRequest`, `StoredEncryptedWallet`, `NoteResouce`, `MultipleClassDeclaration`, `ConvCommitMsg`, `BufferContainer`, `ArrayBindingPattern`, `FileFormat`, `ArrayObserver`, `LogAnalyticsLabelDefinition`, `OafService`, `ZoneState`, `IExpressServerOptions`, `BUTTON_SIZE`, `AccessoryTypes`, `ConsumerContext`, `UpdateServiceRequest`, `ColumnSettings`, `ITransformHooks`, `RealtimeChannelInfo`, `ContentTypeProps`, `IDocumentSystemMessage`, `TreemapSeriesData`, `ChangesetProps`, `MaterialInstanceState`, `MarkType`, `SprottyWebview`, `NineZoneState`, `SVGPathElement`, `Curl`, `CostMetric`, `ISequence`, `DispatchPattern`, `Arithmetic`, `AccountBalanceService`, `HistoryStore.Context`, `DeterministicDeploymentInfo`, `ITranslationService`, `FakeUsersRepository`, `AnimeDetailsFields`, `ApmSystem`, `ITextFieldProps`, `Dashboard`, `EdmxFunctionImportV4`, `NormalExp`, `SurveyObjectProperty`, `LintConfig`, `Linker`, `VisualGroup`, `op`, `InputChangeEvent`, `B3`, `InvalidRequestException`, `VideoStreamRendererView`, `GraphFrame`, `SonarrSettings`, `WrappedComponentType`, `RangePartType`, `OpenAPIObject`, `CreateAccountsRequestMessage`, `Arena`, `AwsService`, `DateAdapter`, `App.webRequest.IRequestMemory`, `PortalWorldObject`, `Paragraph`, `SequentialLogMatcher`, `IPagingTableColumn`, `PluginLoader`, `DesignerNode`, `IterableExt`, `GraphQlQuery`, `VarSymbol`, `A1`, `SignerFetchRpc`, `GenerateTypeOptions`, `PoseNetOperatipnParams`, `Camera`, `CardActionConfig`, `IBlocksFeature`, `SupEngine.Actor`, `AsciiOperatipnParams`, `ISetupFunction`, `TabsState`, `DecodedRouteMode`, `PositionObject`, `Yendor.BSPNode`, `d.TypesImportData`, `IHttpClientOptions`, `ProgressOptions`, `SwaggerBaseConfig`, `ObservableInput`, `TestRenderer`, `WorkloadType`, `ExercisePlan`, `TypeEnvironment`, `K7`, `LanguageMode`, `PromiseAndCancel`, `BlockExport`, `ChatClient`, `FetchHeaders`, `MemberName`, `VideoStreamDescription`, `InMemoryCache`, `PolicyDetails`, `ProblemIndication`, `OutputOptions`, `BertNLClassifierOptions`, `IncomingWebhookSendArguments`, `PROTOCOL_STEPS_ID`, `IObserverHandle`, `MagicExtensionError`, `ValueID`, `SliderOpt`, `OpenFileFilter`, `ReportTarget`, `DocumentNode`, `UpdateConnectionResponse`, `TransformedData`, `CurrencyService`, `DebtRegistryEntry`, `RateLimitState`, `AbstractOptions`, `CornerMarker`, `PipeDef`, `UITransform`, `SchedulerPromiseValue`, `EntityTypeProperty`, `CommitOrderCalculator`, `ResizeGripResizeArgs`, `Observable`, `Group.Point`, `IDeploymentTemplate`, `RoundingModeType`, `DataPublicPluginSetup`, `Inventory`, `ILinkedClient`, `MeetingParticipant`, `CircularLinkedListNode`, `PoiTable`, `ILoaderOptionsPipe`, `vec2.VectorArray`, `AnalyticsDispatcher`, `ConfigurationProps`, `MasternodeBlock`, `AggDescriptor`, `TransactionalFileSystem`, `SwiftVirtualNetwork`, `ElementKind`, `BackupData`, `PageComponent`, `KinesisFirehoseDestination`, `DataModel`, `CallResult`, `InputProps`, `TemplateParameters`, `PreferenceChange`, `FunctionFiber`, `vscode.CodeLens`, `ToastData`, `IContractWrapper`, `d.ResolveModuleIdOptions`, `IEcsTargetGroupMapping`, `OutputTargetStats`, `SFUISchemaItemRun`, `SearchResults`, `IGLTFNode`, `StyleProp`, `CredentialRecord`, `__HeaderBag`, `AsyncOrderedIterable`, `TupleTypeNode`, `NVM3Page`, `requests.ListTaggingWorkRequestLogsRequest`, `UserLoginResource`, `EventListeners`, `IChannelSigner`, `SetValue`, `Global`, `TarTransform`, `IResultTab`, `MagicSDKAdditionalConfiguration`, `GetUserCommandInput`, `ErrorAlertOptionType`, `FakePrometheusClient`, `ANodeExpr`, `TDataGroup`, `Discord.TextChannel`, `BubbleChartData`, `T4`, `requests.ListMetricsRequest`, `btCollisionObject`, `Party`, `RemoteData`, `MorphTargetManager`, `NzGraphDataDef`, `DukDvalueMsg`, `PaneProps`, `RuntimeError`, `RemoteTokenCryptoService`, `DomEventArg`, `OOPTypeDecl`, `SelectCard`, `QueryParamsType`, `ParseTreeMatch`, `TriggerPosition`, `ManagementClient`, `ReferenceRenderHandler`, `ProjectMetadata`, `ModuleWithProviders`, `HttpException`, `KeyType.rho`, `TheoryItem`, `GraphLayoutType`, `EventDescriptor`, `DeleteOrganizationCommandInput`, `FactoryIndex`, `ReactHarness`, `IResolvedQuery`, `JobChannelLink`, `SequenceNumber`, `TextureType`, `ThunkType`, `ProcessRepresentationChainModifier`, `AppThunkDispatch`, `PyteaService`, `DetachPolicyCommandInput`, `_resolve.AsyncOpts`, `PrunerConfig`, `ObservedDocument`, `TrackFormat`, `DependencyGraphNodeSchema`, `IPermissionSearchFilters`, `DomainItems`, `MapSearchCategory`, `CreateProcedureWithInput`, `CanaryAnalysisConfiguration`, `DeleteLeaderboardRecordRequest`, `GradientVelocity`, `SpringRequest`, `GetWrongDependenciesParams`, `StateAccessor`, `JestProcessRequest`, `TemplateListItem`, `LoggerFunction`, `MessageBundle`, `IEvent`, `IdentityProvider`, `SteemiaProvider`, `FieldsService`, `AssertionLevel`, `ContactConstraintPoint`, `Tweenable`, `UpdateProfileRequest`, `WaterfallChartData`, `gameObject.Battery`, `GfxCoalescedBuffersCombo`, `MerchantGoodsEntity`, `ICUToken`, `MatchDataSend`, `LogWrapper`, `XlsxService`, `MetadataClient`, `VisualizeAppStateTransitions`, `WorkDoneProgressReporter`, `RequestOptionsArgs`, `React.AnimationEvent`, `DraggableLocation`, `extendedPingOptions`, `CurveType`, `Ranking`, `FilePropertyReader`, `IdentifiedReference`, `ExitCode`, `ParameterListDetails`, `IEntrypoint`, `SnsDestination`, `IEntityRef`, `YDefinedFn`, `AbortMultipartUploadCommandInput`, `MockUser`, `JsonRpcError`, `AlignmentTypes`, `BaseCursor`, `StateChangeEvent`, `ColumnDefinition`, `SavedObjectsUpdateObjectsSpacesOptions`, `Alias`, `TTree`, `GraphicsGroup`, `AwaitedMessageEntry`, `i18n.Placeholder`, `GenericObject`, `NotifyParams`, `RematchDispatch`, `MockHTMLElement`, `OnboardingItem`, `Bip32Path`, `TKeyboardShortcut`, `CallEndReasons`, `ListRange`, `monaco.CancellationToken`, `StreamLabs`, `CSSDocument`, `KeyResultService`, `SObject`, `SavedObjectsClientCommonFindArgs`, `TransformOriginAnchorPosition`, `vscode.ProviderResult`, `ITokenModel`, `SteeemActionsProvider`, `EvmNetworkConfig`, `Snackbar`, `IArray`, `CustomAction`, `MenuInner`, `ComputedShapeParams`, `AppDispatch`, `OutputTargetCustom`, `Container3D`, `DataSourceItem`, `ExprContext`, `EventRegisterer`, `RARC.RARCFile`, `TLinkedSeries`, `RoutingTable`, `Credit`, `V0RulesService`, `QueryCapture`, `LitParser`, `FieldSetting`, `RolesEnum`, `ColorBlindnessMode`, `JsonObject`, `STAT`, `NetworkRequest`, `ICompileProvider`, `CurlCode`, `HeaderMapType`, `ConstructorDeclaration`, `ImportOptions`, `ApiScope`, `GLuint`, `AccountFilterData`, `EditDialogData`, `ClassNameStates`, `NodeHeaders`, `PredictableSupportCode`, `LoadingEvent`, `algosdk.Transaction`, `IDocumentInfo`, `TestMaskComponent`, `GlobalPooling2DLayerArgs`, `AdminService`, `IImageExtended`, `FilterizrOptions`, `RobotStateAndWarnings`, `ServiceErrorType`, `NativeActivation`, `PersistedLogOptions`, `FeedbackShowOptions`, `DynamicTreeCollisionProcessor`, `n`, `CalendarProps`, `GunNode`, `SubMesh`, `PlayerBattle`, `UpgradeSchemeWrapper`, `ICustomData`, `ODataModelEntry`, `CreateSessionCommand`, `Kernel.IOptions`, `MicrosoftComputeExtensionsVirtualMachineScaleSetsExtensionsProperties`, `VertexAttributeDefinition`, `UseTournamentRoundsState`, `LambdaHandler`, `SavedSearchTypes`, `NgZone`, `ElementFactory`, `ManagementAgentGroupBy`, `StatedFieldMeta`, `ScalingPolicy`, `DateProfile`, `Input.Gamepad`, `RequestConfiguration`, `BaseImageryMap`, `GithubConfiguration`, `Position`, `FunctionTypeFlags`, `Extra`, `FunctionMutability`, `BreakStatement`, `ClanAggHistoryEntry`, `InternalConfig`, `TestProvider`, `ts.ConditionalExpression`, `d.ResolveModuleIdResults`, `Backup`, `CommandInstance`, `BaseSymbolReference`, `ChangeType`, `IGrid`, `InterfaceWithConstructSignature`, `IIconSubset`, `Converter`, `UtilConvertor`, `BaseIncrementOptions`, `InterpolationPart`, `PatchRequest`, `EnumerateVisualObjectInstancesOptions`, `IExchange`, `FtpNode`, `UnregisteredAccount`, `MediaQueryList`, `FModel.LoadSettings`, `IFoo`, `IORouterRegistry`, `BitBucketCloudPRDSL`, `StyleMapLayerSettings`, `ICtx`, `Jimp.Jimp`, `ServerPlatform`, `M3ModelInstance`, `OAuthScope`, `ICoordinateData`, `GradientSize`, `IDejaDropEvent`, `TypeBuilder`, `Display`, `NormalizationHandler`, `CodeModDefinition`, `TranslationsType`, `UdpTally`, `FigmaPaint`, `DocMetadata`, `SfdxFalconProject`, `IWithComputed`, `DocumentHighlightParams`, `UIWaterStorage`, `TestEmitter`, `SimpleTemplateRunner`, `OptionsInterface`, `ResolveReferenceFn`, `PotentialEdgeInfo`, `PDFDict`, `IMapItem`, `IHsl`, `InternalModifiers`, `EndpointOptions`, `OrderData`, `BasePackageInfo`, `ExtendedCompleteItem`, `LayoutConfigJson`, `WriteBatch`, `SingleSelectionHandler`, `LoaderFn`, `IProperty`, `SuggestionsService`, `FinalizeHandlerArguments`, `SpecConfiguration`, `OPENSEARCH_FIELD_TYPES`, `DocumentRequest`, `SysMenu`, `IDataSlice`, `DataSourceSettings`, `CyclicTimeFrame`, `IPipeFn`, `VertexEvent`, `ISolutionExplorerService`, `mssql.config`, `RulesPosition`, `Injector`, `jsmap`, `EditProps`, `vscode.MarkdownString`, `BabelChain`, `ExperimentInterface`, `StackResult`, `CalculatedIndicatorValues`, `GridMaterial`, `WheelEvent`, `sdk.SpeechConfig`, `Float`, `ActiveDescendantKeyManager`, `PDFPageTree`, `VcsItemRef`, `MetaTagState`, `AuthPipe`, `p5ex.p5exClass`, `XTheme`, `HostKind`, `TagValidation`, `SyncProtocol`, `IpcMainInvokeEvent`, `CreateSecurityProfileCommandInput`, `M3Model`, `IRuleSpec`, `TProviders`, `RegionService`, `IHttp`, `ActorPath`, `ActionReducerMap`, `IRegisteredPlugin`, `JointComponent`, `FormattedBuilderEntry`, `CreateFunctionCommandInput`, `NzNotificationDataOptions`, `cxapi.CloudFormationStackArtifact`, `K5`, `RuleCatalog`, `SelectionInterpreter`, `IVorbisPicture`, `MenuComponent`, `GasModePage`, `ScalarsEnumsHash`, `FormOutput`, `SubmitKey`, `L1L2`, `BFBBProgramDef`, `Ship`, `GetDeploymentCommandInput`, `VLIEOffset`, `CapDescriptor`, 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`CalendarViewEvent`, `ContactService`, `ExtensionProps`, `VaultOptions`, `CommentDocument`, `GluegunCommand`, `ScopedObjectContextDef`, `AbiEvent`, `postcss.Root`, `PropertyMeta`, `ShuftiproKycResult`, `PDFRef`, `Dot`, `MultiChannelAssociationCC`, `ChatThreadPropertiesUpdatedEvent`, `FullLink`, `INgWidgetSize`, `KeysData`, `sdk.SpeechRecognitionResult`, `DisplayProcessor`, `ContentObserver`, `Generator`, `DeprecatedButtonProps`, `MutableControlFlowEnd`, `MoneyAmount`, `CreateProcedureWithoutInput`, `RegisterCertificateCommandInput`, `ICommandWithRaw`, `i128`, `BaseView`, `RelativeFunction`, `ExactC`, `IConstruct`, `VerticalAlignment`, `DatePicker`, `RuleFilter`, `TradeHistoryAccount`, `RetryOptions`, `Scoreboard`, `QueryData`, `RegisteredServiceAttributeFilter`, `MatSelectChange`, `VariableDefinitionContext`, `ListNodegroupsCommandInput`, `Parser.ASTNode`, `CurrentItemProps`, `StyledTextNode`, `TableListParams`, `WordcloudSpec`, `GridTile`, `IPageInfo`, `MongoCommand`, `ParentType`, `IAssetSearchParams`, `RuntimeExtensionMajorVersions`, `PadchatMessagePayload`, `RenderContext`, `ListRegexPatternSetsCommandInput`, `TransformationContext`, `JsonBuilder`, `OutfResource`, `RoomTerrain`, `PrivateCollectionsRoutes`, `MatchHandler`, `PartialValues`, `CLM.Condition`, `CompositeGeneratorNode`, `requests.ListVolumeAttachmentsRequest`, `Paging`, `Identifiable`, `PongMessage`, `IHomebridgeUiFormHelper`, `GraphQLEnumValue`, `Coords3D`, `Blockly.WorkspaceSvg`, `IGitResult`, `GridModel`, `RequestBodyObject`, `DAVObject`, `FullIconCustomisations`, `Additions`, `StyleIR`, `Extension`, `RxLang`, `SourceData`, `NoteRepository`, `OrganizationAccount`, `PointMesh`, `FeatureModule`, `RequestEntry`, `SyntheticPointerEvent`, `SearchOption`, `ChainableComponent`, `SnapshotFragmentMap`, `CreateGatewayCommandInput`, `DigestCommandOptions`, `TorrentDAO`, `BaseDataOptionType`, `ScopeNamer`, `ExclusiveDrawerPluginConstructor`, `ProjectUploader`, `ThemeStore`, `RegistrationService`, `SyncService`, `AdaptContext`, `SimulateOptions`, `ChannelResource`, `SortColumn`, `UIClass`, `DocBlockKeyValue`, `WindowModule`, `ISkillInfo`, `ImageItem`, `ExplicitPadding`, `SDKError`, `TokenPricesService`, `ActionDefinitions`, `MapControls`, `SingleOrArray`, `IEstimation`, `GfxCompareMode`, `Re_Exemplar`, `ConnectionCallback`, `MergedCrudOptions`, `WaterInfo`, `IXMLFile`, `CloudBuildClient`, `SwaggerDocument`, `BoxOptions`, `ParsedQs`, `GeoSearchFeature`, `MegalodonInterface`, `PutConfigurationSetDeliveryOptionsCommandInput`, `ISharePointSearchQuery`, `BasicCCGet`, `DriverContext`, `TrackByFunction`, `InboundStream`, `QueryObjOpts`, `DaffCartItemFactory`, `TreeviewFlatNode`, `EncodingType`, `Seconds`, `ResourceConfig`, `DiscoverPlugin`, `RouterStub`, `Interceptor`, `AdminJS`, `LocationSource`, `ExternalSubtitlesFile`, `LSTMCell`, `HttpInterceptord`, `STData`, `RepoOptions`, `Sources`, `ISignaler`, `UpdateBuilder`, `ParseCssResults`, `Seam`, `IEntityOwnership`, `ImageLike`, `BSplineSurface3dH`, `SfdxFalconError`, `ValueFormatterParams`, `GamepadButton`, `AmmConfig`, `ProjectModel`, `TypographyVariant`, `Automerge.Diff`, `QuestionMapType`, `ChildProcess.ChildProcess`, `WechatMiniprogram.CanvasContext`, `ListPublicKeysCommandInput`, `LiteralLikeNode`, `BuddyBuild`, `IAmAnotherExportedWithEqual`, `PrismaClientValidationError`, `TilePathGroup`, `ListStreamsRequest`, `RegExp`, `TransactionResponseItem`, `DeleteApplicationReferenceDataSourceCommandInput`, `ComponentInstruction`, `requests.ListSoftwareSourcePackagesRequest`, `UsedSelectors`, `PyJsonDict`, `TPT1AnimationEntry`, `BaseOperation`, `ResolvableCodeLens`, `DLabel`, `IndentedWriter`, `Session.IModel`, `AnkiOperationSet`, `MatrixModel`, `Explanation`, `CheckoutAction`, `StackLineData`, `ExportNodeProperties`, `AccessPolicy`, `IReCaptchaInstance`, `Relation`, `SecurityPluginSetup`, `requests.ListQuickPicksRequest`, `PubGroup`, `SettingName`, `PrincipalPermissions`, `MapType`, `IParentNode`, `AddressInfo`, `ParameterMetadata`, `IGarbageCollectionState`, `THREE.WebGLCapabilities`, `NoiseServer`, `ChangeAuthMode`, `MdastNodeMapType`, `PiExpression`, `HierarchyCircularNode`, `server.IConnection`, `apid.GetRecordedOption`, `IProject`, `BasicDataPropertyForAdvice`, `i.PackageInfo`, `CW20Addr`, `UsageInfo`, `SessionKeySupplier`, `LayerNormalization`, `ComponentDefinition`, `GetDetailRowDataParams`, `DemoteGroupUsersRequest`, `OrOptions`, `AdaptMountedPrimitiveElement`, `HttpsCallable`, `UseMutationReturn`, `ShowProgressService`, `SlotTreeItemBase`, `EveError`, `LineElement`, `CraftDOMEvent`, `IconElement`, `DOMHighResTimeStamp`, `AutoScalingConfiguration`, `RequirementFn`, `GetLifecyclePolicyCommandInput`, `SFC`, `LinearScale`, `ElementRefs`, `ComputerPlayer`, `GenericDispatch`, `ButtonStyle`, `TagAttributes`, `Syntax`, `puppeteer.ElementHandle`, `ListWorkRequestErrorsResponse`, `TestActions`, `Substream`, `UsableDeclaration`, `WowContext`, `FactReference`, `ExecutionError`, `MemoryShortUrlStorage`, `UseHydrateCache`, `YamlMapping`, `LabelUI`, `IDateRangeInputState`, `DescribeJobLogItemsCommandInput`, `TypeScriptType`, `TransactionHash`, `KeyAgreement`, `Marble`, `ServerErrorResponse`, `CephPoint`, `fhir.Patient`, `ImagePreviewProps`, `IReference`, `Mine`, `JOB_STATE`, `WalletTreeItem`, `FrontstageDef`, `CopySource`, `ControllerFactory`, `PoolMode`, `Gravity`, `ContextConfig`, `OpenSearchSearchHit`, `InsightInfo`, `UnescapedString`, `MessageFileType`, `PartyAccept`, `UpdateLaunchConfigurationCommandInput`, `ManifestActivity`, `StorageKey`, `MonsterProps`, `MigrationOptions`, `ParserFactory`, `DiscoverFieldProps`, `RegisterReq`, `HttpSetup`, `Knex.QueryBuilder`, `FrequencySet`, `ClassOrFunctionOrVariableDeclaration`, `MapperForType`, `SvelteComponentDev`, `DirectionalLight`, `IJwtPayload`, `TimePickerComponentState`, `BrowserController`, `RSAKeyPair`, `MetricFilter`, `t.Errors`, `FixedTermLoanAgency`, `MySQLClient`, `ZoomState`, `Twilio`, `MessageState`, `CompilationParams`, `InteractionStore`, `Pets`, `Q`, `KeyframeAnimation`, `DeviceVintage`, `FieldValues`, `ServerClosure`, `TypeAssertion`, `GeometryPartProps`, `TableCellProps`, `TagResourceResponse`, `PropertyOperation`, `WWA`, `NodeTypesType`, `AddTagsCommand`, `FindProjectQuery`, `TypedMutation`, `SavedVisState`, `ResourceConfiguration`, `Http3ReceivingControlStream`, `FileDto`, `DatosService`, `IAssetInfo`, `IndexPatternSpec`, `AnimationBuilder`, `HistoryAction`, `IQuickeyOptions`, `ThyButtonType`, `JsonSchema.JSONSchema`, `DOMAPI`, `ActionFactory`, `ListIdentityProvidersCommandInput`, `DescData`, `D`, `ModuleResolutionCache`, `TriplesecDecryptSignature`, `MapboxMarker`, `IWorkflowExecuteHooks`, `ResponsiveAction`, `WorkerAccessor`, `NumericF`, `HSD_TExpList`, `ArgSchemaOrRolesOrSummaryOrOpt`, `HostFileInformation`, `OpenSearchDashboardsReactContextValue`, `OutputParametricSelector`, `DbTx`, `TActor`, `Creep`, `BitstreamFormatDataService`, `WorkerMainController`, `MsgUpdateProvider`, `ITableColumn`, `IResolveResult`, `Particle`, `IFluidSerializer`, `HighlightSpan`, `VerifierConfig`, `CommerceTypes.ProductQuery`, `FeatureSource`, `CommandLinePart`, `ColorSwitchCCSet`, `OutputTargetDistGlobalStyles`, `BufferAttribute`, `ExtendedHttpTestServer`, `DescribeAlgorithmCommandInput`, `Dialogue.Argv`, `AccountEntity`, `InspectorEvents`, `SuiAccordionPanel`, `Margin`, `Span_Link`, `TransitionState`, `ILocationProvider`, `BaseInput`, `BaseRender`, `Patterns`, `IOrganizationContact`, `IconItem`, `SArray`, `TwitchServiceConfig`, `ISmsOptions`, `IErrorPositionCapable`, `BirthdayService`, `Matrix3`, `WorkspaceEntry`, `ReadonlyUint8Array`, `RequestHandler0`, `StyProg`, `AggArgs`, `CollidableLine`, `FilePathStore`, `d.OutputTargetDistLazyLoader`, `EnhancementRegistryDefinition`, `MountAppended`, `TSelectActionOperation`, `Impl`, `DeploymentNetwork`, `NextApiHandler`, `SelectBaseProps`, `Runtime.MessageSender`, `OrderFormItem`, `Foxx.Request`, `ValueOrFunction`, `AdministratorName`, `PeriodKey`, `DbObject`, `ExtendedSettingsDescriptionValueJson`, `SourceEntity`, `TestAwsKmsMrkAwareSymmetricDiscoveryKeyring`, `GLfloat`, `PaperInputElement`, `ExecutionEnvironment`, `SignatureKind`, `SchedulerApplication`, `GetApplicationCommandInput`, `EntityRecord`, `Frame`, `TodoItemNode`, `DraggingPosition`, `LibraryType`, `SlatePluginDefinition`, `PreferencesStateModel`, `IExecutionResponse`, `P8`, `DialogResult`, `RepositoryFacade`, `ZoomStore`, `UrlGeneratorsDefinition`, `MockNode`, `DeferredValue`, `RoomVisual`, `CameraService`, `DataSourceState`, `StatsModuleReason`, `WebhookOptions`, `GroupDataService`, `RendererInfo`, `MeasuredBootEntry`, `GroupsPreviewType`, `InputConfiguration`, `SharedPropertyTree`, `PutLifecyclePolicyCommandInput`, `StudioServer`, `tape.Test`, `TopicOrNew`, `MeterCCReport`, `ImplicitParjser`, `Override`, `RawConfigurationProvider`, `MeshAnimationTrack`, `CreateSubscriberCommand`, `KeyedAccountInfo`, `ILanguageRegistration`, `fabric.IEvent`, `RecordC`, `NoteDoc`, `VisualizationData`, `DataKind`, `RawNode`, `ThrottledDelayer`, `UpdateServiceCommandInput`, `ContentOptions`, `IMasks`, `RouteFilter`, `OrmConnectionHook`, `RadixTokenDefinition`, `ChildProcessWithoutNullStreams`, `Extrinsic`, `requests.ListAnnouncementsPreferencesRequest`, `MakeSchemaFrom`, `ProvideCompletionItemsSignature`, `ImageStyleProps`, `ConfigHandlerAndPropertyModel`, `CheckpointsOrCheckpointsId`, `BroadcastEventListener`, `DirectiveOptions`, `SequenceInterval`, `PSIVoid`, `OpenAPIV3.Document`, `DomElement`, `LeaveRequest`, `UntagResourceCommandOutput`, `RefetchOptions`, `JSDocTypeReference`, `IOrganizationContactCreateInput`, `PrismaClientFetcher`, `GraphQLResolveInfo`, `ResourcePackWrapper`, `ComponentWithAs`, `OptionParams`, `ModelMapping`, `requests.SearchSoftwarePackagesRequest`, `TypeAcquisition`, `SubjectSetConstraint`, `LockFileConfigV1`, `PredicateOperationsContext`, `Notifier`, `Web3`, `ScheduleConfiguration`, `RecordProvide`, `DeleteAppRequest`, `Axes`, `IDeviceWithSupply`, `BrowserInterface`, `ItemMetadata`, `RoosterCommandBarButtonInternal`, `api.Span`, `StatusUnfollow`, `IssueTree`, `KeyValueChangeRecord`, `ChangePart`, `Benchee.Benchmark`, `IndexOptions`, `IObservableValue`, `Meal`, `DefinitionResult`, `ast.ExternNode`, `League`, `SubjectKeyframes`, `Swagger2`, `IBoxPlotColumn`, `HappeningBreakpoint`, `Builtins`, `Composer`, `LazyDisposable`, `Stream.Readable`, `RouteComponentProps`, `CallMemberLikeExpression`, `Web3ProviderType`, `debug.IDebugger`, `TabInfo`, `FieldFormatEditorFactory`, `ServerMode`, `PacketParams`, `tfc.Tensor`, `mozEvent`, `IncomingMessage`, `ObservableSetStore`, `Input`, `TypeAlias`, `RouterAction`, `ParsedEnumValuesMap`, `EffectFallbacks`, `ReferencedSymbol`, `CircuitGroupState`, `SetConstructor`, `u32`, `UpdateDatasetCommandInput`, `Severity`, `Cwd`, `PathFilterIdentifier`, `Human`, `AdvertiseByoipCidrCommandInput`, `URLTransitionIntent`, `IElementRegistry`, `OrphanRequestOptions`, `BattleFiledData`, `PerformOperationResult`, `SpriteFontOptions`, `RootContext`, `CommunicationIdentifierKind`, `Protocol.ServiceWorker.ServiceWorkerVersion`, `RouterEvent`, `ObsidianLiveSyncSettings`, `ButtonWidth`, `RegisteredConnector`, `AnimKeyframe`, `FFT`, `BuildNode`, `RequestInformationContainer`, `SRTFlags`, `SettingModel`, `ESTree.Class`, `EstimateGasEth`, `apid.UnixtimeMS`, `ShouldSplitChainFn`, `DaffCart`, `TwingNodeType`, `SelectTool`, `AgentService`, `CategoryDescription`, `d.OutputTargetDist`, `ImageAlignment`, `SearchParameters`, `IVirtualDeviceResult`, `TestAudioBuffer`, `UnwrapNestedRefs`, `BVHNode`, `PropertyDetails`, `NamedImportBindings`, `RepoBuilder`, `TreeConfig`, `DataChunk`, `ToastrService`, `NotFoundErrorInfo`, `Stats`, `RenderInfo`, `UpdateChannelCommandInput`, `Network`, `EntityDispatcherDefaultOptions`, `MockCanvas`, `PurchaseProcessor`, `IMatrixConsumer`, `Chorus`, `GetRevisionCommandInput`, `TextProperty`, `CommandData`, `CallLikeExpression`, `IAccessToken`, `EntityDefinitionService`, `ConstantQueryStringCommandInput`, `AbstractMessageParser`, `WebpackWorker`, `ExecSyncOptions`, `IOSNotificationCategory`, `ImageLocation`, `TagScene`, `AcMapComponent`, `SFUManager`, `FactoryUser`, `ts.Symbol`, `SocketClass`, `IElementStyle`, `HttpFetchOptionsWithPath`, `PackagerAsset`, `VariableContext`, `Parameters`, `EventHit`, `GeomNode`, `BuildResults`, `sharp.Sharp`, `RangePointCoordinates`, `JSDocReturnTag`, `Config.InitialOptions`, `TObj1`, `SavedObjectsCreatePointInTimeFinderOptions`, `datetime.DateTimeData`, `FleetStatusByCategory`, `Transformed`, `ListManagementAgentPluginsRequest`, `SceneNode`, `UnionOrIntersectionType`, `FormModel`, `Stripe.PaymentIntent`, `PatchType`, `RecoveredSig`, `MODNetConfig`, `IORedis.RedisOptions`, `Models.CurrencyPair`, `CERc20`, `Hash`, `TInjectItem`, `ModelStoreManager`, `JoinTournamentRequest`, `HistoryRPC`, `ILabel`, `UnlitMaterial`, `Warning`, `ItemGroup`, `LogsEvent`, `SortedReadonlyArray`, `ConstantTypes`, `InvalidArgumentException`, `IStoreService`, `StacksConfigRepository`, `keyboardState`, `WebSocket.ErrorEvent`, `CreateApplicationResponse`, `TargetDisplaySize`, `TypeLiteralNode`, `ScreenshotDiff`, `LogMethod`, `ResolverClass`, `TaskWrapper`, `MapMaterialAdapter`, `NextConfig`, `ViewsWithCommits`, `AbstractCrdt`, `LazyIterator`, `CancellationTokenSource`, `Electron.IpcMainInvokeEvent`, `CodeType`, `QueryBeginContext`, `CombatantViewModel`, `IDebugResult`, `SupCore.PluginsInfo`, `ComponentDef`, `MediaQueryListEvent`, `SQLiteDb`, `OrganizationSlug`, `Assertion`, `DescribeEnvironmentManagedActionHistoryCommandInput`, `MemBank16k`, `OfflineSigner`, `GeneralObject`, `SemanticsFlag`, `SnotifyToastConfig`, `ButtonGroupProps`, `TensorArrayMap`, `ListRecipesCommandInput`, `PrerenderConfig`, `ListAutoScalingConfigurationsCommandInput`, `vscode.TextEditorDecorationType`, `StreamEmbedConfig`, `MarkSpec`, `OAuthConfig`, `DevicesButtonProps`, `UiActions`, `UriService`, `ExperienceBucket`, `InterceptorContext`, `requests.ListCertificatesRequest`, `ExternalSourceAspectProps`, `TouchControlMessage`, `HistoryEnv`, `ServiceFlags`, `IStringStatistics`, `IOEither`, `ToastMessage`, `ComponentCompilerWatch`, `MemoryX86`, `W7`, `SourceState`, `UITableView`, `Mail`, `InferenceFlags`, `AttributeValueSetItem`, `IManifest`, `EmployeeAppointment`, `Items`, `CostMatrix`, `Material`, `UploaderBuilder`, `TransportRequest`, `Nibble`, `SubInterface`, `CombinedReportParameters`, `Callback`, `HookName`, `GeoUnits`, `MultiIndices`, `CompletionMsg`, `estypes.SearchResponse`, `responseInterface`, `UserIdentifier`, `GoAction`, `CustomerRepository`, `LSPConnection`, `CellValue`, `MapOfClasses`, `CrowdinFileInfo`, `FormatCompFlags`, `AlarmSensorType`, `DeveloperExamplesSetup`, `CFCore`, `UpdateNote`, `THREE.Scene`, `ItemSpec`, `TdDataTableService`, `UpdateServerCommandInput`, `TextFont`, `ConfigArgs`, `DiscoverSetupPlugins`, `HttpService`, `JSDocAugmentsTag`, `FoamFeature`, `ImportClause`, `EntityCollectionServiceElementsFactory`, `PlayerLink`, `APIWrapper`, `IGiftsGetByContactState`, `CsvReadOptions`, `AxisScale`, `Fetcher.IEncrypted`, `PuppetASTClass`, `AutorunFunction`, `RollupBuild`, `StackProc`, `AwsVpcConfiguration`, `EngineConfigContent`, `StreamManager`, `GauzyAIService`, `PendingModifiedValues`, `UpSampling2DLayerArgs`, `GLTFNode`, `IRenderFunction`, `GLsizei2`, `InDiv`, `DataBySchema`, `TransportWideCC`, `FormProperty`, `FindQuery`, `ExpensiveResource`, `requests.ListModelsRequest`, `interfaces.BindingOnSyntax`, `ts.LeftHandSideExpression`, `TreeStructure`, `TimeSeries`, `SchemaConfigParams`, `core.IHandle`, `SphereGeometry`, `DAL.DEVICE_ID_THERMOMETER`, `ThermostatFanMode`, `GfxFormat`, `CompletionExpressionCandidate`, `NetworkState`, `PiLangExp`, `ISocket`, `RElement`, `AstNodeParser`, `ReactNativeContainer`, `IssueStatus`, `ConeLeftSide`, `SmoldotProvider`, `ResolvedEntityAtomType`, `ISlope`, `DateIntervalFormatOptions`, `PromiseQueue`, `VolumeTableRecord`, `Tmpfs`, `NotificationId`, `SwitchOrganizationCommand`, `DescribeExportTasksCommandInput`, `XDate`, `PlatformRender`, `ItemDefBase`, `SparseArray`, `UIResource`, `CollectionPage`, `ClassType`, `Variant`, `OpsMetrics`, `WorldmapPointInfo`, `IMonitoringFilter`, `UnlinkFromLibraryAction`, `WriteContext`, `IMigrationConfig`, `StyleRules`, `IndexKind`, `U8Archive`, `InitialStatistics`, `ScatterPointItem`, `CommandQueueContext`, `Typeless`, `Sorting`, `WasmSceneNode`, `LexoRank`, `pouchdb.api.methods.NewDoc`, `RateLimiter`, `StringASTNode`, `ManagedDatabaseSummary`, `MatDialogRef`, `FormControlProps`, `FormikErrors`, `MsgCloseBid`, `SkipListMap`, `BuildTask`, `CreateTemplateCommandInput`, `RtkQueryApiState`, `JobPostLike`, `IApiComponents`, `PokerScoreService`, `Stash`, `LeveledDebugger`, `ObjectGridComponent`, `SqrlKey`, `ElementSet`, `Repository`, `PartialEmoji`, `T.LayerStyle`, `Bluetooth`, `ThreadState`, `ParamIdContext`, `ValidationService`, `PointStyle`, `RateProps`, `fs.WriteStream`, `MemoryHistory`, `fGlobals`, `MetaDataModel`, `CandidateInterviewersService`, `Uint32Array`, `RenderArgs`, `ContractService`, `GetCommandInvocationCommandInput`, `StackMap`, `UrlParam`, `PossibleValues`, `StorageReference`, `AbbreviationTracker`, `MediaInfo`, `models.ChatNode`, `MutationResolvers`, `Survey.Base`, `Choice`, `ContentGroup`, `InstanceInfo`, `LinkParticle`, `PartialItem`, `ThyNotifyOptions`, `XsuaaServiceCredentials`, `BTI_Texture`, `CollectionDataStub`, `ScoreInstrument`, `AddTagsToResourceCommandInput`, `ThemePair`, `EnvironmentService`, `PropertyDrivenAnimation`, `TaskModel`, `Criteria`, `ColumnsSortState`, `QueryCache`, `ErrorMiddleware`, `BufferedTransport`, `AllSettings`, `ProfileIdentifier`, `CompilerEventDirDelete`, `AudioSelector`, `HubPoller`, `WindowsJavaContainerSettings`, `PeerRequestOptions`, `WrappedFunction`, `KaizenToken`, `IMiddleware`, `ICurve`, `BuilderRuntimeEdge`, `ISmartMeterReadingsAdapter`, `ValidationRuleMetaData`, `AvailableSpaceInConsole`, `PickTransformContext`, `QueryGroupRequest`, `ImageStyle`, `Router`, `PlanningRestriction`, `DataAdapter`, `SavedObjectsRawDocParseOptions`, `BulkUnregistration`, `ReactiveArray`, `IStandaloneCodeEditor`, `BoxShadow`, `Clique`, `LineType`, `NodeId`, `XPathResult`, `MenuServiceStub`, `MeshRenderer`, `ProposalTx`, `RemoteFilter`, `JsonParserTransformerContext`, `ProtocolName`, `ExtendedChannelAnnouncementMessage`, `PullAudioOutputStreamImpl`, `BuildOptions`, `MySQLParserListener`, `FirmaSDK`, `InvalidGreeting`, `Tensor1D`, `WeConsoleScope`, `PreviewService`, `ValueFillDefinition`, `IClassification`, `Git.VersionControlRecursionType`, `MdcDialogPortal`, `PacketEntity`, `AccountingEvent`, `DeleteApiKeyCommandInput`, `APISet`, `TimerActionTypes`, `Prism`, `TransformFunction`, `TableDifference`, `IGatsbyImageData`, `CompletionsProviderImpl`, `PointLight`, `ConstantExpressionValue`, `GetReplicationConfigurationCommandInput`, `MessageConnection`, `IPluginBinding`, `CurrentVersion`, `DocHeader`, `MarketData`, `ThanksHistory`, `LabelMap`, `GX.IndTexMtxID`, `BeancountFileContent`, `T.Layer`, `SourceEngineView`, `TwingCallable`, `Semester`, `AnyMap`, `MeetingSessionVideoAvailability`, `Foxx.Response`, `CSSSnippetProperty`, `EngineArgs.MarkMigrationAppliedInput`, `IGameCharaUnit`, `PipelinePlugin`, `com.mapbox.pb.Tile.IFeature`, `TypedGraph`, `Level`, `SerializedCrdtWithId`, `EnvelopesQuery`, `RefreshInterval`, `TransactionProto.Req`, `SupportedExt`, `sbvrUtils.PinejsClient`, `ProcessGraphic`, `SrtcpSSRCState`, `ModuleG`, `TextTheme`, `CanvasTypeVariants`, `MutationName`, `ConfigFileExistenceInfo`, `ContextValue`, `OptionComponent`, `ModifyGlobalClusterCommandInput`, `Movement`, `TemplateContext`, `PackageMeta`, `ESTree.Identifier`, `requests.ListDatabaseSoftwareImagesRequest`, `KeyboardLayout`, `NodeMaterial`, `SequenceDeltaEvent`, `SqrlErrorOutputOptions`, `ActiveToast`, `OhbugEventWithMethods`, `CoreConfig`, `SignedContractCallOptions`, `WordCharacterKind`, `HdEthereumPaymentsConfig`, `BracketPair`, `NonFungiblePostCondition`, `capnp.Data`, `Multiset`, `CandidateCriterionsRatingService`, `AuthenticatorFacade`, `IMemFileSystem`, `LayerListItem`, `xml.ParserEvent`, `EncodingQuery`, `ChannelContext`, `OriginOptions`, `GitHubCommit`, `ShellCommand`, `PutResourcePolicyCommandOutput`, `IDatabaseResultSet`, `requests.ListPingProbeResultsRequest`, `INamesMap`, `Builtin`, `UnlockedWallet`, `InvalidationLevel`, `Controller2`, `DiagramModel`, `RepositoryOptions`, `End`, `TextElementLists`, `ProjectControlFunction`, `DescribeAppInstanceCommandInput`, `backend_util.ReduceInfo`, `Sink`, `FSAOptions`, `StepName`, `SubmissionJsonPatchOperationsService`, `FnCall`, `FileStatWithMetadata`, `PuppetASTResolvedProperty`, `AzExtClientContext`, `ConfigurationDTORegions`, `IJetView`, `Serverless.Options`, `IMappingFunction`, `CertificateVerify`, `CreatePostDto`, `CreatePagesArgs`, `DatabaseContract`, `CheckReferenceOriginsParams`, `UIState`, `SyncRule`, `HeaderColumnChain`, `LocalMarker`, `ServerTranslateLoader`, `TextureCube`, `Sheet`, `ListOptions`, `IRequest`, `ProgressStep`, `CombinedScanResult`, `BillingModifier`, `GX.RasColorChannelID`, `GithubService`, `StateTree`, `MonthPickerProps`, `CSSDataManager`, `Cancel`, `TestIamPermissionsRequest`, `PlaneAltitudeEvaluator`, `SearchError`, `WebSocketEvent`, `AudioVideoEventAttributes`, `StridedSliceDenseSpec`, `Tied`, `TEConst`, `ChangeInstallStatus`, `OpenYoloCredential`, `ValuesDictionary`, `AttributeData`, `RemoteStream`, `ExtendedSocket`, `SeriesRef`, `AggregationRestrictions`, `ContractEventDescriptor`, `Mutable`, `NewsroomState`, `HandlerDefinition`, `IGarbageCollectionDetailsBase`, `GetObjectCommandInput`, `UnocssPluginContext`, `ItemSpace`, `EventSubscriber`, `UseRefetchReducerState`, `ConversationTarget`, `ts.EnumMember`, `ParsedAuthenticationInstructions`, `TokenRecord`, `InheritanceNode`, `NormalizedRuleType`, `EngineAPI.IApp`, `GenericTable`, `KoaContextWithOIDC`, `ReactText`, `ts.NodeArray`, `MovementComponent`, `MetamaskNetwork`, `ReadonlyQuat`, `V1StatefulSet`, `InvalidFormatError`, `IGeneratorData`, `ViewModelReducerState`, `CollectionInstance`, `UsageExceededErrorInfo`, `TransportType`, `HelloResponse`, `ExtractorResult`, `Shipment`, `NavigationTrie`, `IPeripheral`, `NoteItemComponent`, `Quantity.OPTIONAL`, `UpdateInputCommandInput`, `ENUM.SkillRange`, `AssetModel`, `MerchantStaffEntity`, `Factor`, `WlMedia`, `ExecutionMessage`, `LambdaType`, `UpdatePartial`, `TransitionStatus`, `WorkNodes`, `VerificationMethod`, `CellRenderer.CellConfig`, `DescribeDBSubnetGroupsCommandInput`, `Form`, `ModuleElementDeclarationEmitInfo`, `MutationArgsType`, `BuiltinFunctionMetadata`, `LIST_ACTION`, `Shadow`, `SearchStrategySearchParams`, `PredicateContext`, `TopNavMenuData`, `IContentItem`, `CreateSavedObjectsParams`, `BuildSettings`, `ScheduleState`, `Positive`, `BufferChannel`, `People`, `RouteDataFunc`, `ParameterApiDescriptionModel`, `ExpressionRenderHandler`, `Unchangeable`, `DeclarationInfo`, `BoostDirectorV2`, `PackageUser`, `ConditionsType`, `fhir.DocumentReference`, `UniqueEntityID`, `RecordBaseConcrete`, `Variable`, `NohmModelExtendable`, `Union3`, `JSXTemplate`, `IFileMeta`, `IStateBase`, `ParameterWithDescription`, `PropertyChangeResult`, `common.AuthParams`, `LinksFunction`, `IEmployeeProposalTemplate`, `GlobalContext`, `SecurityPermission`, `IWalletContractService`, `EntityApi`, `RequestEntryState`, `BSONType`, `OneOfAssertion`, `ListRoomsResponse`, `StackSpacing`, `QueryOrderOptions`, `BTCMarkets.currencies`, `OrganizationDocument`, `sdk.CancellationDetails`, `S3Resource`, `ClientJournalEntryIded`, `QuestionProps`, `ModelInfo`, `TestRunArguments`, `SymbolDisplayPart`, `ISemver`, `GanttBarObject`, `TopicInterest`, `HdPublicKey`, `VerifiedParticipant`, `React.ReactText`, `PatchSource`, `IKChain`, `ModuleSystemKind`, `ApplyPredicate`, `GfxSamplerFormatKind`, `ConfigurationLoader`, `PoolSystem`, `AggObject`, `IGenericEntity`, `PlacementResult`, `PlanetGravity`, `BitcoinPaymentsUtils`, `FinalDomElement`, `ODataEntitySetResource`, `RebootInstanceCommandInput`, `BuildState`, `CategoriesService`, `PiStyle`, `CliOutputOptions`, `DeleteJobCommandInput`, `Rarity`, `SolverConfig`, `PurchaseInfo`, `PageRect`, `LoggingInfo`, `ReactFrameworkOutput`, `MethodOptions`, `StateValue`, `RecordMap`, `EventUi`, `BIP44HDPath`, `OverlayConnectionPosition`, `TestCommander`, `ChartOffset`, `AppComponentDefinition`, `GeneralImpl`, `MessagePacket`, `UpdateWindowResizeSettings`, `UserRegistrationData`, `Showable`, `altair.LightClientUpdate`, `PrivateIdentifier`, `PDFKitReferenceMock`, `DigitalInOutPin`, `Git.IAuth`, `ListDatasetGroupsCommandInput`, `ReferenceSummary`, `IOOption`, `OperationLink`, `CloudAssembly`, `ListElementSize`, `FeatureState`, `GX.CC`, `DialogType`, `NamespacedAttr`, `SchemaArg`, `QueryCommand`, `PackageInfos`, `GoToTextInputProps`, `DiffuseMaterial`, `ElementDecorator`, `Units`, `QnaPost`, `LocalRenderInfo`, `LoadLastEvent`, `RetrievedCredentials`, `ServerSecurityAlertPolicy`, `AnimationBoneKeyFrameJson`, `TTypeProto`, `TransferParameters`, `SocketIoConfig`, `theia.WebviewPanelShowOptions`, `MatchedStep`, `CompileUtil`, `FacetSector`, `DefaultToastOptions`, `CacheManagerOptions`, `RippleSignatory`, `RewriteResponseCase`, `UpdateIdentityProviderCommandInput`, `LineRange`, `TextRenderStyle`, `d.FsWriteOptions`, `Operator`, `Dialogic.Item`, `SampleInfo`, `EntityFetcherFactory`, `IAnyObject`, `ComponentEventType`, `IndexInfo`, `VerticalAlignValue`, `SendMessageRequest`, `AS`, `IPluginConfig`, `TransactionsModel`, `ITagObject`, `UniversalRenderingContext`, `IScopedClusterClient`, `AuthorizationServiceSetup`, `InvokeCreator`, `DescribeScheduleCommandInput`, `ProjectTechnologyChoice`, `React.Reducer`, `SerializableObject`, `SerializationService`, `DeleteDBClusterParameterGroupCommandInput`, `UserSettings`, `XMLHTTPRequestMock`, `PreferenceProvider`, `QueryServiceClient`, `FrontMatterResult`, `TimeInput`, `SymbolResolutionStackEntry`, `UseQueryOptions`, `DestinationHttpRequestConfig`, `UnidirectionalLinkedTransferAppAction`, `ProductAction`, `DatasetStatistics`, `SpecQueryModel`, `AutoScalingMetricChange`, `DisclosureInitialState`, `SnapshotRelation`, `ServiceContext`, `SyntaxKind.Identifier`, `ICXSetup`, `AsyncBlockingQueue`, `HttpServiceSetup`, `ContextMenuItemModel`, `DirectionConfiguration`, `CapabilitiesProvider`, `NmberArray9`, `StandardAccounts`, `FocusOutsideEvent`, `ITransferItem`, `TranslationStorage`, `NamespaceObject`, `EventSummary`, `Ogg.IPageHeader`, `IUploadItem`, `IFinaleCompilerOptions`, `AzureCommunicationTokenCredential`, `IdentifierValue`, `SystemVerilogSymbolJSON`, `td.WebRequest`, `MouseWheelEvent`, `SettingActionTypes`, `WebGLRenderCompatibilityInfo`, `RawAbiDefinition`, `ChatStoreState`, `UnitState`, `TextProps`, `PymStorage`, `DataCharacter`, `CSharpField`, `AdbClient`, `OptimizelyXClient`, `ParameterConstraints`, `DashboardReport`, `CombatLogParser`, `RFNT`, `MockDocumentTypeNode`, `ProviderApi`, `AndroidActivityEventData`, `ApiResponseOptions`, `DaffNewsletterState`, `ObserverResponse`, `MockStoreCreator`, `WebCryptoEncryptionMaterial`, `ListTypesCommandInput`, `AppOption`, `Decipher`, `StripeModuleConfig`, `LegacySpriteSheet`, `KibanaFeatureConfig`, `RouterActions`, `VerificationClient`, `LoanCard`, `HierarchyChildren`, `RuntimeWorker`, `d.PrerenderConfig`, `TOptions`, `NetworkStatus`, `N1`, `MapPartsRailMoverNrv`, `RandomFunc`, `PackageJsonChange`, `IChangeInfo`, `ERC1155ReceiverMock`, `Arrow`, `PayloadInput`, `ConnectionContext`, `Equipment`, `Epic`, `GunScope`, `AndroidManifest`, `GlobalStateService`, `ExtractorEventEmitter`, `cdk.Stack`, `IApiConnection`, `moment.MomentStatic`, `NZBUnityOptions`, `CreateMemberCommandInput`, `BufferReader`, `ProfileData`, `AstSymbol`, `AddressAnalyzer`, `AnyItemDef`, `ProgressBar`, `METHOD`, `TestEnvironmentConfig`, `AnimVectorType`, `DocumentEntryIded`, `ZodTypeAny`, `VictoryPointsBreakdown`, `TransactionAndReceipt`, `ModuleLoaderActions`, `Web3Client`, `EntityID`, `TAbstractFile`, `ErrorChunk`, `CdkFooterRowDef`, `AttendanceMonth`, `ReactNodeArray`, `GameService`, `MessageDeserializationOptions`, `InteractiveState`, `CategoryType`, `FormatWrap`, `MoviesService`, `NbMenuService`, `PluginDebugAdapterContribution`, `ModifierToken`, `d.ServiceWorkerConfig`, `IMessageDefinition`, `Sequential`, `requests.GetZoneRecordsRequest`, `PartialCanvasTheme`, `SelectionShape`, `EventCreator1`, `GitLogCommit`, `Unit`, `ItemTypes`, `CORSOptions`, `TSESTree.Decorator`, `IndexMapping`, `IMainConfig`, `DatabaseQuery`, `VolumeBackupSchedule`, `HostService`, `AcceptFn`, `ConnTypeIds`, `TAggParam`, `AjaxConfig`, `ILocalDeltaConnectionServer`, `Prefs`, `EnvironmentTreeItem`, `FleetAuthzRouter`, `ListKeysRequest`, `Codefresh`, `StandardClock`, `IndicatorCCGet`, `GfxBufferP_GL`, `PagerXmlService`, `IndependentDraggable`, `TwitterUser`, `ManualServer`, `StatGroup`, `AngularFireStorage`, `GUIDriverMaker`, `BuilderDataManagerType`, `GanttDatePoint`, `PanelModel`, `requests.ListFunctionsRequest`, `EtherscanClient`, `IWorkflow`, `hm.BasicCredentialHandler`, `MsgStartGroup`, `SMTCallGeneral`, `KernelBackend`, `ChartSonify.SonifyableChart`, `IDocumentElementKey`, `NftType`, `NVM500Details`, `EntityTypeT`, `Val`, `X86Context`, `MutableVector3d`, `ClientStringService`, `DaffConfigurableProduct`, `PoiManager`, `LayerForTest`, `TrueFiCreditOracle`, `CreateTableOptions`, `Anomaly`, `BridgeInfo`, `ScopeGraph`, `ShaderSemanticsInfo`, `DebuggerMessage`, `SpotifyErrorResponse`, `cytoscape.EventHandler`, `SubFeaturePrivilege`, `IEventHubWizardContext`, `BaseQuery`, `ServiceScope`, `FormControl`, `BlockFactorySync`, `AuthenticationDataState`, `IColonyFactory`, `DashboardContainerFactoryDefinition`, `TwitchBadgesList`, `CompositeMenuNode`, `Code`, `RowHashArray`, `OptimizationContext`, `MultisigConfig`, `CoreModule`, `InternalOpts`, `IStorageUtility`, `d.JestEnvironmentGlobal`, `ReadonlyVec3`, `ItemUpdateResult`, `TFLiteNS`, `ExternalDMMF.Document`, `APIUser`, `PlotRowIndex`, `N5`, `FirebaseOptions`, `ClaimToken`, `KnobsConfigInterface`, `LedMatrixInstance`, `TestProject`, `KeyIdentity`, `LanguageCCSet`, `EventAxis`, `IApiProfile`, `TFLiteWebModelRunnerOptions`, `IConnectable`, `TreeView.DropLocation`, `OptionsAfterSetup`, `webhookDoc`, `PermissionDeniedState`, `Moc`, `OrderbookL2Response`, `requests.GetJobRequest`, `UserGeoLocations`, `KeyContext`, `vile.PluginList`, `ts.CommentRange`, `EventEmitter`, `LoopReducer`, `x.ec2.SecurityGroup`, `ng.ICompileProvider`, `InternalDiagnostic`, `ITestEntity`, `UpdateStackCommandInput`, `QueryParam`, `QPoint`, `FcNode`, `StoredPath`, `BlockchainClient`, `DisposeResult`, `PrintResultType`, `MathContext`, `IAttachmedFile`, `mat4`, `MediaSubtitlesRelation`, `TSlice`, `MDCTabBarView`, `RuleFix`, `Transactions`, `DrgRouteDistributionMatchCriteria`, `ArrayServiceArrToTreeOptions`, `LibraryEngine`, `firebase.firestore.FirestoreDataConverter`, `PyVar`, `t_44e31bac`, `EdgeCalculatorSettings`, `IncomeService`, `RouteDefinitions`, `Urls`, `BalanceChecker`, `PropsFieldMeta`, `ModelVersion`, `OhbugExtension`, `JStep`, `ISlideRelMedia`, `RecordSetWithDate`, `TCmd`, `BaseTask`, `QualifiedUserClients`, `GluegunFileSystemInspectTreeResult`, `UpdateActivatedEvent`, `CipherService`, `TsPaginatorMenuItem`, `d.HostConfig`, `Chatlog`, `ConstructorParams`, `LaunchContext`, `ManualOracle`, `AggregatedStat`, `PlayerEntity`, `DynamicActionsState`, `AnchorProps`, `FactoryRole`, `TagsViewState`, `mediaInfo`, `PrismaClientOptions`, `DescribeApplicationCommandInput`, `MsgSharedGroup`, `VRMSpringBoneGroup`, `_Transaction`, `VFS`, `pulumi.Resource`, `ComponentSetup`, `LoopBackFilter`, `AppxEngineStepGroup`, `UINavigationController`, `TagRenderingConfig`, `MatSnackBarRef`, `DocumentReference`, `QueryDeepPartialEntity`, `Subsegment`, `SWRKeyInterface`, `VideoTileController`, `ReadGeneratedFile`, `SwankConn`, `SplinePoint`, `HTMLMetaElement`, `BlobModel`, `ITestObjectProvider`, `GitManager`, `MultiSet`, `StatusIndicatorGenericStyle`, `JSXAttribute`, `LatLngLiteral`, `MenuItemConstructorOptions`, `EChartsCoreOption`, `DatabaseSchema`, `CompositeLocale`, `TextContent`, `ICustomerRepository`, `BillAmount`, `xlsx.Sheet`, `CursorPagingType`, `GatherShape`, `IEmbeddable`, `RumEvent`, `NexusPlugin`, `DraggableElement`, `CommentProps`, `GlobalEventDealer`, `GetBotCommandInput`, `PackagePolicyInputStream`, `DataWriter`, `IKernelConnection`, `PropertyPreview`, `DataModel.ChangedArgs`, `JMapInfoIter`, `HdBitcoinPaymentsConfig`, `Survey.Page`, `ToolingLog`, `EndCondition`, `AddMissingOptionalToParamAction`, `Envelope`, `ValueMetadataString`, `BuildFeatures`, `RealtimeAttendeePositionInFrame`, `MdDialog`, `SamplerDescriptor`, `CheckoutAddressesPage`, `DecorationSet`, `BellSchedule`, `NativeScrollEvent`, `ts.ObjectLiteralExpression`, `CancelableRequest`, `NodeFlags`, `CustomTypes`, `SubmissionSectionObject`, `requests.ListTaggingWorkRequestErrorsRequest`, `IPerformTasksCommandArgs`, `ARNodeInteraction`, `Routing`, `ValidationException`, `CeloTransactionObject`, `UpdateMigrationDetails`, `PrefV2`, `Install`, `JRPCResponse`, `StorageEvent`, `ColumnWidths`, `CandidateTechnologiesService`, `IExplanationMap`, `ThyTranslate`, `DocEntry`, `DashboardStart`, `RawSavedDashboardPanel620`, `MToonMaterial`, `JsonRpcResponseCallback`, `CompileContext`, `TypeConstructor`, `DownloadInfo`, `BaseOption`, `IHttpClient`, `ListEmailIdentitiesCommandInput`, `DescribeChangeSetCommandInput`, `ElementData`, `Log`, `FormatterOptionsArgs`, `GfxBufferP_WebGPU`, `SymbolOr`, `HostsByIpMap`, `NavigationGuardNext`, `Match`, `TestingModuleBuilder`, `com.nativescript.material.core.TabItemSpec`, `MSDeploy`, `ExceptionalOpeningHoursDay`, `SearchResponse`, `DueDate`, `RollupClient`, `SettingsType`, `TreeSelectionReplacementEventArgs`, `SearchComponent`, `IndicatorCCSet`, `KuduClientContext`, `MIRInvokeKey`, `SecretProvider`, `Specification`, `ChannelTreeItem`, `TextChangeRange`, `IIncome`, `TT.Step`, `CombinationKind`, `CSSVariables`, `DescribeDetectorCommandInput`, `ChartRequest`, `RedocThemeOverrides`, `Settled`, `Extras`, `SourceDir`, `NormalizedEsmpackOptions`, `xyData`, `monaco.editor.ITextModel`, `MatrixEntry`, `GetEnvironmentCommandInput`, `DbMempoolTx`, `PDFAcroText`, `MessageRequest`, `TxResult`, `CreatePresetCommandInput`, `RobotState`, `DBProvider`, `RegisterDomainCommandInput`, `NamespaceScope`, `AnyApi`, `LanguageCCReport`, `PluginSpec`, `SfdxOrgInfo`, `DynamoDB.ReturnConsumedCapacity`, `Frontstage1`, `vscode.TreeItem`, `DependencyDescriptor`, `ExpressMeta`, `FactoryResult`, `IWebhookMatchedResult`, `MVideoUUID`, `ReduxAction`, `Civil`, `Hostname`, `SubsystemType`, `PiTypeStatement`, `ExportInfo`, `UniswapVersion`, `Request`, `Widget.ResizeMessage`, `BalanceTransferPayload`, `SpotTag`, `PlayerInputModel`, `TrueConstraint`, `ContentTypeProperty`, `FetchableType`, `ITerminal`, `TestingRuntime`, `ResourceXML`, `PredicateProvider`, `FluidDataStoreContext`, `CoapForm`, `MediaManager`, `GenericDeclarationSupported`, `AzureDeployerService`, `IViewArgs`, `LibraryNotificationActionContext`, `CausalRepoCommit`, `ExpressionStatement`, `vscode.EventEmitter`, `ModifyPayloadFnMap`, `Cropping2D`, `ElementMeta`, `NormalRange`, `TSubfactionArmy`, `Telemetry`, `CheerioElement`, `CustomClientMetadata`, `ArcTransactionDataResult`, `ExoticComponent`, `TrueFiPool2`, `MountOptions`, `CompilerEventFileDelete`, `DateInput`, `ImportedCompiledCssFile`, `ViewportHandler`, `RNConfig`, `ListRuleGroupsCommandInput`, `NotificationType`, `ExportTypesRegistry`, `ErrorWithLinkInput`, `PropertyUpdatedArgs`, `ToastId`, `d.LoadConfigInit`, `GoalTimeFrame`, `QueueFunctions`, `requests.ListSourceApplicationsRequest`, `Bit`, `AuthenticationSession`, `cc.Node`, `GlyphplotComponent`, `JsNode`, `SimplifyOptions`, `ThisExpression`, `CanvasIconTypes`, `SpinnerProps`, `TaskGroup`, `Slicer`, `AppType`, `Deferred`, `ICanvasProps`, `UrlSegmentGroup`, `CommandLineParameter`, `TradeService`, `BlockchainService`, `TableRequestProcessorsFunction`, `ISdkBitrate`, `InitOptions`, `LinkedListNode`, `TileLevel`, `ZoneAwarePromise`, `IVec2Term`, `SerializeOpts`, `ChannelsSet`, `Bundler`, `CameraKeyTrackAnimationOptions`, `DidResolutionOptions`, `IResourceInfo`, `SecurityCCNonceReport`, `NgGridItemSize`, `AuxConfig`, `JobSavedObjectService`, `CompilerSystemRenameResults`, `Thenable`, `SymbolWithScope`, `Web3Utils`, `Builder`, `ChartTemplatesData`, `CloneOptions`, `ImportStatement`, `ListEnvironmentsCommandInput`, `ProfilePage`, `BaseField`, `Recipients`, `ShootingNode`, `yubo.IRecordMessage`, `AST.Node`, `GridGraphNode`, `RemoteUserRepository`, `WalletStore`, `CMB`, `Themed`, `CreateConnectionDetails`, `FlattenedFunnelStepByBreakdown`, `JobValidationMessageId`, `Pos`, `InterfaceDeclaration`, `IService`, `BaseCallback`, `GetConnectionsCommandInput`, `CombinedEntry`, `LicenseState`, `TimelineProps`, `CodeMirror.EditorFromTextArea`, `AWSOrganizationalUnit`, `UnvalidatedIndexingConfig`, `PullRequestReference`, `RoomLayout`, `MessageObject`, `RPCResponse`, `SelectBuilder`, `SectionState`, `ArrayTypeNode`, `ShortcutService`, `IndexPatternValue`, `CommandsMutation`, `AdminUserEntity`, `ExpressClass`, `workspaces.ProjectDefinition`, `IndexTemplate`, `AppConfirmService`, `FnU2`, `RunningState`, `AbstractCancellationTokenSource`, `three.Object3D`, `CoinPayments`, `ArmResourceTemplate`, `ColorModeRef`, `RewardManager$1`, `FundingStrategy`, `WalletMock`, `INetworkNavigatorNode`, `UserDescription`, `DependencyChecker`, `RockType`, `SVGMark`, `TableRowState`, `KeyRingService`, `Access`, `CountingChannel`, `LocalContext`, `KPuzzleDefinition`, `StorageObject`, `LocalStorageSinks`, `d.JestConfig`, `ConvectorController`, `STLoadOptions`, `EditArticleDto`, `VariableAST`, `Mapper`, `DockPanel`, `ITabData`, `SPort`, `TopAppBar`, `VitePluginConfig`, `SignatureDeclaration`, `EmailService`, `NodePbkdf2Fn`, `BitFieldResolvable`, `PurgeHistoryResult`, `next.Page`, `CurrencyDisplayNameOptions`, `MemoryInfo`, `IExpense`, `ISubgraph`, `SelectOptionBase`, `IResultGroup`, `Interaction`, `FixtureFunc`, `GfxrAttachmentSlot`, `StartInstanceCommandInput`, `ReqMock`, `word`, `EnumValueDefinitionNode`, `IRequestDTO`, `SecretWasmService`, `URIAttributes`, `UserProvider`, `GraphQLFieldConfigMap`, `CreateComponentCommandInput`, `EndOfDeclarationMarker`, `ExpressionFunctionTheme`, `TestRunner`, `QueryPlan`, `firebase.firestore.Timestamp`, `CachePolicy`, `SessionStorageSources`, `ReactElement`, `VroRestClient`, `TRPCClient`, `HydrateScriptElement`, `ViewEvent`, `IPropertiesElement`, `PdfCreator`, `Layouter`, `NodeTypes.IMessagingService`, `StringDocument`, `ITempDirectory`, `SkillLogicData`, `ng.ICompileService`, `ReduxReducer`, `ObservableQueryBalances`, `PrettierOptions`, `K.StatementKind`, `MatMulPackedProgram`, `DbService`, `ReportGenerator`, `BitmexSpy`, `OnTouchedType`, `VirtualCollection`, `Monster`, `VRMBlendShapeProxy`, `AutoCompleteContext`, `ITrace`, `DeleteApplicationRequest`, `Ellipse`, `DropOptions`, `NavAction`, `RedBlackTreeEntry`, `Alt`, `GanttService`, `CurveLocationDetail`, `WindupMember`, `EntityDto`, `TicketDoc`, `StylingContext`, `BilinearPatch`, `BaseTxInfo`, `Mountpoint`, `ArticleDetail`, `ModernRoute`, `next.Artboard`, `IEndpointOptions`, `IRepo`, `EndpointArgument`, `REQUIRED`, `PolyfaceAuxData`, `PutObjectCommandInput`, `ResolverRegistry`, `requests.ListCrossConnectsRequest`, `GetRequest`, `RpcClientFactory`, `GraphQLScalarType`, `configuration.uiType`, `CSG`, `CheckBoxProps`, `IUIProperty`, `Iterable`, `TypeNames`, `VariableLikeDeclaration`, `IFilterListItem`, `PreimageField`, `CreateAppInstanceCommandInput`, `RenameLocation`, `cc.Sprite`, `GoogleActionsV2AppRequest`, `StoreClass`, `IInputIterator`, `CompSize`, `AvailableMirror`, `Joi.ObjectSchema`, `MEvent`, `SharedMetricsPublisher`, `JsonFormsStateContext`, `CreateRuleCommandInput`, `PutDeliverabilityDashboardOptionCommandInput`, `Animated.Node`, `ProcessRepresentation`, `DataRow`, `SrtpSSRCState`, `GraphOptions`, `Circline`, `IInstruction`, `BlobEvent`, `GeoObject`, `ClientHttp2Stream`, `BNLike`, `GetAllAccountsRequestMessage`, `SessionsState`, `mat2d`, `ConfigKey`, `ProjectsActions`, `ViewContainerRef`, `ExecaReturnValue`, `DeepStateItem`, `SubmissionProgress`, `socketio.Server`, `MaterialData`, `ts.ModuleDeclaration`, `RequestsDataItem`, `ActionCreators`, `BuildListInstanceCreateOptions`, `SignedResponse`, `GameStateRecord`, `ListCV`, `messages.Pickle`, `TransactionDetails`, `LocationInformation`, `INetwork`, `RequestStatistics`, `CompilerEventBuildNoChange`, `Taro.request.Option`, `PriceSpec`, `CreateErrorReportInput`, `Models.GamePosition`, `Datafile`, `BuildVisConfigFunction`, `RecordSubType`, `apid.GetReserveOption`, `PostQueryVarsType`, `IGrid2D`, `RtcpTransportLayerFeedback`, `AnimationKeyframesSequenceMetadata`, `PcmChunkMessage`, `ConfigIntelServer`, `firebase.FirebaseError`, `Primitives.Point`, `ChangeInfo`, `LocalMicroEnvironmentManager`, `GaxiosResponse`, `ScaleContinuous`, `SafeHtml`, `IEventPlugin`, `Serenity`, `WindowManager`, `TypeDBTransaction`, `QualifiedRule`, `CreateDatasetImportJobCommandInput`, `ResolvingLazyPromise`, `MatrixArray`, `IHttpResult`, `DaoFilter`, `ISchema`, `UILog`, `Directionality`, `ProviderFrameElement`, `IpAddress`, `FilterEngine`, `Moized`, `State`, `NameBindingType`, `ColorSchemeName`, `WechatMaterialIdDTO`, `AttributionsWithResources`, `LoginItemProps`, `PSTTableBC`, `AllKindNode`, `ICommandPalette`, `GraphStoreDependencies`, `ImageDataLike`, `handleEvent`, `CreateChannelMembershipCommandInput`, `DefineMap`, `ABIDecoder.DecodedLog`, `GalleryActions`, `PasswordSchema`, `BoxGeometry`, `THREE.Box2`, `ts.TypeQueryNode`, `Sticker`, `IBuildTask`, `SnippetSession`, `HsQueryBaseService`, `Security2Extension`, `ClientHttp2Session`, `ByteWriter`, `A0`, `RenderCanvas`, `Waveform`, `IAggregateStructure`, `SearchResultsLayer`, `TokenResult`, `DiagnosticAddendum`, `SharedDelta`, `RouteArg`, `Whitelist`, `IParameterDefinitionsSource`, `RequestBody`, `ColDef`, `MergeQuerySet`, `StateContext`, `IConnectOptions`, `ICard`, `InvoiceEstimateHistoryService`, `TooltipPoint`, `Replace`, `LinearSearchRange2dArray`, `Unpacker`, `PixivParams`, `CSharpDeclarationBlock`, `EdmxMetadata`, `USB`, `ServiceHttpClient`, `ModalWindowProps`, `BitReader`, `LuaMultiReturn`, `IFileChanges`, `ConstraintTiming`, `TrendResult`, `requests.ListPublicIpsRequest`, `Sidebar`, `RoutingService`, `MatchCallback`, `SystemType`, `VIS0_NodeData`, `ChartConfig`, `GltfFileBuffers`, `ProfileStore`, `FetchArgs`, `PoolConnection`, `PostMessage`, `IsometricPath`, `PropertyDescription`, `InferredSize`, `IApiSecurityRequirement`, `TokenPosition`, `RenderableSprite3D`, `LoginModel`, `ScreenshotBuild`, `IAuthenticateOidcActionConfig`, `SignedOnUserService`, `ITestReporter`, `MagicMessageEvent`, `IndentToken`, `HashKeyType`, `RoomManager`, `HoveredNavItemPayload`, `CommandContext`, `TimeRaster`, `SceneMouseEvent`, `TRaw`, `SeoService`, `SuggestQueryInterface`, `HighlightRepository`, `NextcloudClientInterface`, `DataViewObject`, `IUserPPDB`, `FocusTrapManager`, `Uint64Id`, `ChatLoggedType`, `NativeReturnValue`, `RowList`, `MarkdownOptions`, `NodeCue`, `KeyboardNavigationAction`, `WebSocketAdapter`, `ComponentItem`, `IDeploymentStrategy`, `StynWalk`, `DBDocument`, `MapValue`, `ColumnsPreviewType`, `UniqueId`, `ConditionFilterType`, `UseCaseExecutorImpl`, `NetworkInterface`, `CommonStatusBarItem`, `SerializedPolicy`, `InputHandler`, `SessionTypes.Proposal`, `SnailfishNumber`, `IVottJsonExportProviderOptions`, `AssessmentTypeData`, `QR.QueryResult`, `IPty`, `UserAnnotation`, `PointComponentProps`, `ProtectedRequest`, `LogAnalyticsLabelView`, `DemoChildGenerator`, `XArgs`, `BOOL`, `FilterValueFormatter`, `SnackbarService`, `AkimaCurve3dOptions`, `BufferEncoding`, `msRest.RequestOptionsBase`, `ChildItem`, `UnauthorizedException`, `ITenantCreateInput`, `RequestHandlerEntry`, `HttpEffect`, `ITextFieldExpression`, `FieldTypeByEdmType`, `KeywordMatcher`, `ts.ClassDeclaration`, `Tenancy`, `UserSelection`, `egret.DisplayObject`, `GestureTypes`, `BigNumber`, `LastSnapshot`, `CopyImageCommandInput`, `AstNodeFactory`, `AddTagsCommandOutput`, `AsyncManager`, `RankState`, `ApiItem`, `P2PPeerInfo`, `IVueComponent`, `WebLayer`, `SubscriptionCallback`, `InsecureMode`, `ExtractResponse`, `Electron.App`, `Filesystem.FileExistsAsync`, `BaseError`, `TopicType`, `QueuePeekMessagesResponse`, `BuilderOutput`, `ExpressRouteCircuitPeering`, `TreeService`, `SketchName`, `BuilderDataManager`, `SqrlSlot`, `storeType`, `RecordsFetchFilters`, `NativeNode`, `BrowserIndexedDBManager`, `bbox`, `ContractFunction`, `requests.ListThreatFeedsRequest`, `UpdatePayload`, `VoyagerConfig`, `ExpressAdapter`, `TokenItem`, `monaco.editor.ICodeEditor`, `ShellString`, `LView`, `Year`, `TAuditReport`, `BriefcaseConnection`, `EqualityComparison`, `MutableVector4`, `RowAccessor`, `UserActionBuilder`, `Language`, `NodePositionOffset`, `DebugState`, `MultiMaterial`, `FrameOffset`, `SpeechRule`, `GetIdentityVerificationAttributesCommandInput`, `sdk.SpeechRecognitionEventArgs`, `ResolvedModuleFull`, `BankTransfer`, `ParseNode`, `ConstructionSite`, `ng.IFilterService`, `Meeting`, `NavigationEntry`, `TaskCustomization`, `RangeValue`, `IInjector`, `AtlasResourceSource`, `ITypedDump`, `IScoutStems`, `DocumentPositionStateContext`, `ServiceConfigurationOptions`, `MarkovChain`, `FileDoc`, `InternalDefaultExpression`, `URLDescriptor`, `ActionItem`, `TextInput`, `WhereGrouper`, `Filesystem.ReadJsonSync`, `MessageGeneratorImplementation`, `AttributeOptions`, `Evaluation`, `core.BIP32Path`, `AnyAction`, `CmsModelFieldToGraphQLPlugin`, `SearchResult`, `ITokenizer`, `RadixSpunParticle`, `NerModelVersion`, `WorkItemUI`, `LogItem`, `GfxTextureSharedP_WebGPU`, `ModuleDest`, `IESAggField`, `IDocumentReference`, `IdSelector`, `KnownDomain`, `IPdfBrick`, `Timers`, `ConditionOperator`, `server.Server`, `AppConfigType`, `VirtualFolder`, `PlacementType`, `Displayable`, `_Column`, `TextView`, `FormatterService`, `lsp.Connection`, `Stores`, `DeviceTypes`, `BotConfig`, `TimelineMax`, `CheckpointTrie`, `SupportedFiletypes`, `EnvPair`, `RARC.JKRArchive`, `ExecutableItem`, `CacheChangeEventData`, `ReviewId`, `EngineTypes`, `BitBucketServerPRComment`, `ServiceWorkerRegistration`, `DragAction`, `ObservableQuerySecretContractCodeHash`, `ApolloReactHooks.MutationHookOptions`, `TransferTransactionUnsigned`, `SurveyTemplateRendererViewModel`, `ViewType`, `NPCActorCaps`, `PathSolution`, `EndorsementPolicy`, `TArrayValue`, `TouchState`, `TIdType`, `GetStaticPropsContext`, `BinaryOpComplexProgram`, `ExplorationInfo`, `EntitySet`, `ListParticipantsRequest`, `PanelProps`, `FastifyTypeBoxRouteOptions`, `ReferenceArray`, `GVBox`, `PortRange`, `ObjectDefinitionBlock`, `CallHierarchyIncomingCall`, `UserUpdate`, `DataListItem`, `DepNodeAssembly`, `EdmxEntitySet`, `TraitLabel`, `FieldStruct`, `ObjectUpdatesService`, `WebsocketService`, `AnyProps`, `XDomain`, `IPercentileAggConfig`, `TestColdObservable`, `XNodeData`, `MessageWorkflowMapping`, `DatasetEntry`, `RawDimension`, `FileDiagnostics`, `JobCreatorType`, `FileChunkIterator`, `Progress.IChunk`, `Province`, `KVS`, `AutoFix`, `TestServiceContext`, `InputTypes`, `DiscoverUrlGeneratorState`, `AddValue`, `CallGNode`, `ContainerFormData`, `THREE.Camera`, `IBuildTaskConfiguration`, `PrefetchOptions`, `DefaultRouterOptions`, `EnableOrganizationAdminAccountCommandInput`, `SerialAPICommandContext`, `IOrganizationTeamCreateInput`, `AuthTokenResult`, `CheckoutState`, `any`, `NodeCryptoCreateHash`, `DetectionResultItem`, `EmitterSubscription`, `CodePointCharStream`, `CIImage`, `SNSTopicArnNotFoundFault`, `JSONWebToken`, `AppletType`, `CSSScope`, `CreateConnectorResponse`, `GetSessionCommandInput`, `DataState`, `...`, `ExternalModuleInfo`, `ImportedData`, `ForwardTsnChunk`, `SpriteArgs`, `ListItemBase`, `AppSources`, `CommandArgs`, `d.CollectionCompilerVersion`, `PerPanel`, `TimeScaleUnit`, `Checkpoint`, `ICoordinates`, `ReaderFragment`, `Uint8Array`, `ImGui.IO`, `ChangePasswordState`, `EarlyStoppingCallbackArgs`, `StableRange`, `IAmazonServerGroupCommand`, `SavedObjectsFindOptions`, `MGLMapView`, `DouyuPackage`, `ChromeBreadcrumb`, `DeserializeFunction`, `SearchThemeAttributes`, `CodeGeneratorFileContext`, `FormEntry`, `ConstructorTypeNode`, `FrameworkVersionId`, `RepositoryEditWriteModel`, `NPMContext`, `Failure`, `ArrayCriteriaNode`, `PrismaObjectDefinitionBlock`, `AuthResult`, `Collapse`, `ModelValue`, `LayoutAction`, `MockCamundaWorkflow`, `NotifyModel`, `CustomEditorUpdateListener`, `StatedBeanContainer`, `PublicDeviceDTO`, `request.CoreOptions`, `Comm`, `NbJSThemeOptions`, `GPUData`, `ui.Rectangle`, `ts.EnumDeclaration`, `HttpOperationResponse`, `ClientIntakeFormIded`, `Arity1`, `PromiseFulfilledResult`, `ParserInputWithCtx`, `RelatedClassInfo`, `ValidationResponse`, `lf.schema.Table`, `UploadableMap`, `requests.ListInstancesRequest`, `SourceType`, `EmbedProps`, `PdfSolidBrush`, `IRule`, `ParseFunction`, `WebGLTransformFeedback`, `LocationResult`, `TMap`, `ConstantSchema`, `UnwrappedArray`, `IPartialDeploymentTemplate`, `ComputeVariant`, `t.MemberExpression`, `IntPair`, `LineIds`, `DeleteUserProfileCommandInput`, `Mdast.Parent`, `FieldItem`, `RepositoryState`, `ExistsFilter`, `Crop`, `AsyncActionCreators`, `EthUnlockRecord`, `ScriptLike`, `GMSMapView`, `V1WorkflowOutputParameterModel`, `DataContextGetter`, `arc_result`, `ReportConfigurationModel`, `KeyLoader`, `TFEOpAttr`, `CmdParts`, `TwingOutputBuffer`, `EntityReference`, `MeetingSessionStatus`, `ToastPosition`, `Cubic`, `ObjectCallback`, `Security2CCMessageEncapsulation`, `Highlighter`, `ICommandMapping`, `KeywordPrefix`, `IUserService`, `MySet`, `SharingSession`, `DeleteProjectResponse`, `messages.Meta`, `IconMap`, `IEvents`, `PingPongObserver`, `Totals`, `PuzzleLoader`, `CaptionDescription`, `BackstackEntry`, `Debouncer`, `DidChangeLabelEvent`, `FeatureMap`, `MonoStyleViews`, `SBDraft2CommandOutputBindingModel`, `DbEvent`, `FeatureRegistry`, `Maximum`, `GunGraphConnector`, `IntervalCollection`, `TestStore`, `RegExpMatcher`, `DocumentService`, `ListAliasesCommandInput`, `ScenarioState`, `IVectorV`, `IProjectSetupData`, `InstallablePackage`, `requests.ListCpesRequest`, `RollupError`, `vscode.ShellExecutionOptions`, `EditableCell`, `TCollection`, `d.BuildTask`, `ViewWithBottomSheet`, `CdsNavigationItem`, `XPortalService`, `DAL.DEVICE_ID_BUTTON_B`, `JsonRpcProvider`, `Trade`, `AngularFire`, `RenderModel`, `GraphQLHOCOptions`, `DBInstance`, `FontWeightType`, `TransactionCtorFields`, `NodeAnnouncementMessage`, `UiActionsEnhancedSerializedEvent`, `AccountMongoRepository`, `DroppableProvided`, `ListTasksRequest`, `EditService`, `MenuPath`, `ListResolversRequest`, `NotificationTargetItem`, `ListHttpProbeResultsRequest`, `ReuseTabCached`, `MouseCoordinates`, `Mention`, `GetBlacklistReportsCommandInput`, `EdgeInsets`, `IBackendApi`, `VocabularyService`, `ReadableSignal`, `DaffSubdivisionFactory`, `DomCallback`, `TaskNow`, `RenderColumn`, `SemanticDiagnosticsBuilderProgram`, `YarnPackageManager`, `RouterRes`, `IndexService`, `SerializedEntity`, `SfdxFalconResult`, `ConnectionService`, `ChartAntVSpec`, `ElectronStore`, `CatDTO`, `StoreModel`, `ConfigItem`, `PluginInfo`, `CHR0`, `InvoicesService`, `ExtraControlProps`, `PackageJSON`, `DeviceInfo`, `OptimizationResult`, `ActivityAttendance`, `TransformContext`, `RawToken`, `SunBurstHierarchyNode`, `TransformPointFn`, `EntityAddOptions`, `UpdateClusterRequest`, `EnvConfig`, `RenderTextureInfo`, `ArticleOverview`, `UriResolver`, `ExprVis`, `MyTabItem`, `ApexTestGroupNode`, `TemplateHead`, `ListComponentsCommandInput`, `CommandEntityBuilder`, `FabricObject`, `GfxCullMode`, `ThreadChannel`, `VisibilityVertex`, `ApiConfiguration`, `PrintJsonWithErrorsArgs`, `Swagger.Schema`, `ClipboardJS`, `FormAppSetting`, `CtrTextureHolder`, `IDBCursorDirection`, `A6`, `requests.ListPackagesInstalledOnManagedInstanceRequest`, `InvitationDTO`, `AggsMap`, `TileReadBuffer`, `IdentityPermissions`, `KeyboardEventArgs`, `EnrichedAccount`, `ChannelMessageRemove`, `MediaSource`, `ITimelineItem`, `HTMLOListElement`, `IFluxAction`, `Node.Expression`, `PropEnhancerValueType`, `SolidityListener`, `ShaderDescriptor`, `ManagedEvent`, `RLANKeyframe`, `AnimationPromise`, `QueryProvidersRequest`, `AsyncDiffSet`, `EVMEventLog`, `IBaseProps`, `CategoryAxis`, `NamespacedWireDispatch`, `ViewBoxParams`, `TypedNavigator`, `PolyserveApplication`, `GitlabUserRepository`, `Rx.PartialObserver`, `ListableObject`, `Backend`, `WebGLFramebuffer`, `IKeyboardBindingProps`, `GX.KonstAlphaSel`, `PDFArray`, `FlatpickrFn`, `SubscriptionAccountInfo`, `OpenLinkProfiles`, `TestTimelineDataProvider`, `Identifier`, `CreateFleetCommandInput`, `GfxBindingLayoutDescriptor`, `ObjectExpression`, `SharedContentImp`, `HierarchicalEntity`, `LineResults`, `DeleteStackCommandInput`, `VirtualConfig`, `ToggleState`, `ProxyDao`, `DeeplinkPayPayload`, `UploadFileStatus`, `IActionInputs`, `CarouselButton`, `AnyChannel`, `TextFormatter`, `MockApiClient`, `ODataCallable`, `PieChart`, `UserResumeEntity`, `ValidationControllerFactory`, `ENDStatement`, `BotTagMasks`, `LoadAll`, `DeleteDomainResponse`, `ColorPickerProps`, `ITestContainerConfig`, `GoogleMeetSegmentationConfig`, `CollapseGroupProps`, `IEmitterBehavior`, `ConnectorReferenceHandler`, `IResolver`, `PrintTypeFlags`, `ExtendableMessageEvent`, `ChainsService`, `angular.ui.bootstrap.IModalServiceInstance`, `PddlWorkspace`, `EntityComparer`, `Topology`, `ProjectReflection`, `IComponentState`, `V3RouteWithValidQuote`, `SWRResponse`, `SpanKind`, `TargetSummary`, `EffortInfo`, `ArenaAttribute`, `ICommand`, `TextRenderer`, `StdSignature`, `FunctionDefinitionContext`, `PowerlevelCCReport`, `ThyFormDirective`, `ParityRegion`, `CdsRadio`, `CreateAliasCommandInput`, `OrderDoc`, `ITokenPayload`, `PriceAxisViewRendererData`, `sdk.ConnectionEventArgs`, `DebugProtocol.Request`, `OneofDescriptorProto`, `Element.JSON`, `ActionData`, `RouteMeta`, `LocalBlockExport`, `DOMString`, `VirtualItem`, `Capabilities`, `DeepLinker`, `FatalErrorsSetup`, `MatStepperIntl`, `ResizeStrategy`, `types.CSSProperties`, `VSvgNode`, `WorldState`, `NumberSystemName`, `EditorChangeLinkedList`, `DragSourceArguments`, `requests.ListRulesRequest`, `PointerCtor`, `PartialStoryFn`, `UpdateProfileCommandInput`, `jsdom.JSDOM`, `SocketContextData`, `IFirmware`, `CloudProvider`, `IMetadata`, `CaseClause`, `ICandidateFeedbackCreateInput`, `QRCode`, `ScaleContinuousType`, `BindingOrAssignmentElementTarget`, `ClusterContract`, `StringProperty`, `Type_AnyPointer_Unconstrained`, `GUILocation`, `IGenericTagMapper`, `ChatChannel`, `OfficeLocation`, `GenericFormProps`, `InitializationOptions`, `MappedTopicsMap`, `MultiAPIMerger`, `IAggConfig`, `WithContext`, `FunctionBuilder`, `ElementModels.IElementWrapper`, `DragDropManager`, `ast.ExpressionNode`, `StakingTransaction`, `NamespaceNode`, `FormulaDescriptor`, `TestBackend`, `Snowflake`, `IClusterHealthChunk`, `UniDriver`, `GridStackItemWidget`, `TimeBin`, `StringifiedType`, `ConfigHttpLoader`, `ICache`, `ParserArgs`, `Tagged`, `IExpressionEvaluationContext`, `QueryParamDef`, `PropertyAssignment`, `DocumentQuery`, `ElementLocation`, `IOpenFileItemsState`, `ReaderContext`, `NextApiResponse`, `LanguageClientConstructor`, `ReflectionGroup`, `TfsCore.TeamContext`, `RequestResponse`, `SiteConfiguration`, `CharMap4`, `RouterState`, `Graphics`, `RectangleObject`, `KeyboardKey`, `NullAction`, `ProvisioningParameter`, `GitClient`, `ErrorResponseData`, `Stub`, `CompilerConfig`, `ListRecommendationsRequest`, `ATNState`, `IAssetComponent`, `ReactNode`, `Animated.AnimatedInterpolation`, `IdentifierToken`, `Triangle3`, `FormatType`, `ContractCallReturnContext`, `ISimplestConfigFile`, `ExpectationRepository`, `ProviderCard`, `FormatState`, `DescribeWorkspaceCommandInput`, `RuleManager`, `VersionInterface`, `TeleportContext`, `UserTypeReference`, `CreateUserDto`, `ArmArrayResult`, `rpcConfig`, `d.JsonDocsUsage`, `IClass`, `WrapLocals`, `RemoveRoleFromDBClusterCommandInput`, `ControllerParameterMetadata`, `HsDimensionTimeService`, `ComboConfig`, `AudioOptions`, `ResultDate`, `MessageContext`, `Events.pointerup`, `GetCapabilitiesXmlLayer`, `ArrayMultimap`, `JobID`, `constructor`, `Highcharts.StockToolsNavigationBindings`, `PrivateLinkConnectionApprovalRequestResource`, `EthereumTransactionTypeExtended`, `ChatLogged`, `FileConfig`, `IGlTFParser`, `HouseCombatData`, `PlaywrightElementHandle`, `nls.LocalizeFunc`, `CountryService`, `B8`, `LocalForageObservableChange`, `PositionService`, `BigIntMoneyBase`, `MathBackendWebGL`, `HandlerResult`, `ActionHandlerWithMetaData`, `LocaleNode`, `KeySignature`, `SeedGenerator`, `ValueDB`, `SlashDot`, `YoonitCamera`, `ParquetSchema`, `TableDiff`, `TaskDoc`, `FilterCallback`, `ServiceType`, `DuiDialog`, `QueryBidResponse`, `BuddhistDate`, `Stylesheet`, `CallbackAction`, `RepeatVectorLayerArgs`, `EmitterWebhookEvent`, `BlockNumberRepository`, `LocaleSpec`, `Comonad1`, `PathOptions`, `Frontier`, `ActionBar`, `Controls`, `IsoBuffer`, `CurriedFunction1`, `TriggerInteractions`, `CompilerWorkerContext`, `TEX0Texture`, `IteratorCreatorFn`, `es.CallExpression`, `TestDataset`, `DecoratedError`, `AvatarSize`, `GoogleAuth`, `PlasmicASTNode`, `SrtpSsrcState`, `NoteCollectionState`, `IItem`, `ListRecommendationsResponse`, `Integration`, `DeleteOneOptions`, `MatcherCreator`, `ModState`, `ProjectClient`, `PackageInstallationResult`, `DescribeChannelMembershipCommandInput`, `ComponentEmitInfo`, `LibraryInfo`, `StatFrame`, `EditableCircle`, `Print`, `ImGuiIO`, `TaskTreeItem`, `CKEDITOR.eventInfo`, `middlewareSingle`, `ConnectedSpaceId`, `AES`, `IIconOptions`, `SinonFakeServer`, `iReduxState`, `ComponentRef`, `ArrayAccessValue`, `d.BuildLog`, `RailPart`, `ExtrusionFeatureParameters`, `TelegramBot.Message`, `XUL.menupopup`, `MpProduct`, `IRepositoryState`, `AlertState`, `EventStoreDescription`, `RivenMod`, `MockConfiguration`, `EventCategoriesMessage`, `IBBox`, `PaginationInput`, `GraphQLInputType`, `VoidFn`, `FastifyRequest`, `MWCListIndex`, `WidgetType`, `ClientRect`, `ConfigurableEnumValue`, `Exception`, `AV1RtpPayload`, `DocumentRegistryBucketKey`, `FlagValidatorReturnType`, `ImmutableFrameTree`, `TransferService`, `ContextItem`, `FormValidator`, `Float64Array`, `WebRTCConnection`, `PropsType`, `WholeHalfNone`, `Directory`, `JsonParserContext`, `Geocoder`, `Data`, `SnippetProvider`, `Modify`, `MapChart`, `TemplateStruct`, `TItem`, `TableConstructor`, `RawJSXToken`, `StatusVectorChunk`, `ISubscriber`, `AuthenticateFn`, `NumberRowModel`, `OperatorContextFunction`, `ts.MapLike`, `TypeAssertionMap`, `ExecutionResultDataDefault`, `PaginationOptions`, `DashboardSetup`, `https.RequestOptions`, `CoverLetterService`, `MediaMatcher`, `FsReaddirOptions`, `IDeferred`, `SimpleSwapAppState`, `DharmaMultiSigWalletContract`, `RollupSingleFileBuild`, `VisualizationsStart`, `ComponentModule`, `AnimationInstance`, `RedisClientOptions`, `OptionsHelper`, `TETuple`, `IConfirmService`, `quantumArray`, `UrlEntity`, `DocumentSymbolCollector`, `TransactionEntityDataService`, `MergeProps`, `DashPackage`, `Reaction`, `Conditions`, `protocol.FileRequest`, `EarningsTestService`, `TAccesorKeys`, `BlockBody`, `SharedRoleMapping`, `Prepared`, `GetMessagingSessionEndpointCommandInput`, `Chai.ChaiStatic`, `FairCalendarView`, `IListProps`, `FlowPostContextManagerLabel`, `UserReference`, `TFnRender`, `STORES`, `And`, `cytoscape.Core`, `FirebaseFirestore`, `ClusterData`, `PrometheusClient`, `EntityCache`, `QuestionAdornerComponentProps`, `SCServerSocket`, `IListViewCommandSetExecuteEventParameters`, `IEdgeRouter`, `OutputTargetDistCollection`, `IGetPatchDirResult`, `TableNS.CellProps`, `Exchange`, `ParseConfig`, `SettingTypes`, `SourcePosition`, `requests.ListDrgRouteRulesRequest`, `ColorT`, `tsdoc.DocComment`, `EntAsset`, `messages.Examples`, `ProjectionRule`, `C6`, `WidgetState`, `TeamCity`, `GoToFormProps`, `Favorite`, `MaybeAccount`, `EslintConfig`, `RepairTask`, `Application.RenderOptions`, `OctreeObject`, `RecordType`, `IBenefitsSearchResult`, `FilterQuery`, `SendTxnQueryResponse`, `WhereCondition`, `PackageTypeEnum`, `StridedSliceSparseSpec`, `OutRoomPacket`, `GraphBatchedTransferAppState`, `RSSItem`, `MarkdownContributions`, `RxFormBuilder`, `BLSPubkey`, `Transaction`, `LastFmArtistInfo`, `W5`, `EmailAddress`, `UseRefetchReducerAction`, `TriggerState`, `NumberMap`, `tag.ID`, `TFlags`, `LineMessageType`, `TransactionButtonInnerProps`, `SpeakerService`, `InputParamValue`, `ByteOrder`, `Stapp`, `PreferencesCategories`, `DeleteConfigurationSetCommandInput`, `Fetcher`, `CSymbol`, `UserInfo`, `Focusable`, `MergeRequestPayload`, `APIService`, `HydrateResults`, `ReporterRpcClient`, `SortOrder`, `StudentRepository`, `ModifyDBClusterCommandInput`, `StepListener`, `HTMLCollectionOf`, `UntagResourceOutput`, `SnapshotConnection`, `IConnectToGitHubWizardContext`, `Lines.Segment`, `IdentityProviderMetadata`, `WindowType`, `IKbnUrlStateStorage`, `Config.Argv`, `SVGIconProps`, `RelationMetadata`, `BooleanInt`, `ListDeploymentStrategiesCommandInput`, `S2L2ALayer`, `requests.ListIpv6sRequest`, `MatSnackBarConfig`, `ListGroupsResponse`, `BlockHandle`, `SyncData`, `IRandomReader`, `PDFCheckBox`, `Resource`, `BasicEnumerable`, `ScryptedRuntime`, `LoggerFactory`, `ProtonApiError`, `EdaPanel`, `DatasetOpts`, `ManifestInventoryItem`, `StateOperator`, `TEX0`, `Functions`, `SignedStateReceipt`, `ConsumerParticipant`, `CpeDeviceConfigAnswer`, `IExecutionFlattedDb`, `AccessDeniedException`, `x`, `LocalVideoStreamState`, `ReactTypes.DependencyList`, `DMMF.SchemaField`, `IValueFormatter`, `MapIterator`, `DomainBounds`, `CrochetForNode`, `LogAnalyticsSourceDataFilter`, `EnumItem`, `ButtonTool`, `PieDataSet`, `_IPBRMetallicRoughness`, `CommandFn`, `AdditionalPropsMember`, `Matched`, `ITiledLayer`, `MethodName`, `WebGLTensor`, `IAssetMetadata`, `MetaProperty`, `HTMLTableRowElement`, `AuditInfo`, `StartJobCommandInput`, `CreateChannelModeratorCommandInput`, `TypeMapper`, `BoxSlider`, `GetByIndex`, `OBJLoader`, `VideoCreateResult`, `ReadStorageObjectId`, `vscode.DebugConfiguration`, `JitsiPeer`, `FungibleConditionCode`, `ScaleQuantize`, `MonthlyForecast`, `DetailedReactHTMLElement`, `ProviderOption`, `HiFiCommunicator`, `CdkRowDef`, `JumpPosition`, `InheritedProperty`, `IDataFilterConfiguration`, `SmoothedPolyline`, `OnePoleFilter`, `RevocationStatus`, `ValidatorStore`, `IModels`, `GADNativeAd`, `UserPool`, `Struct`, `AllDocsResponse`, `MessageSecurityMode`, `GrantAccessData`, `AppModel`, `RegisteredRuleset`, `ir.Block`, `ListRealtimeContactAnalysisSegmentsCommandInput`, `GenericClientConfiguration`, `Work`, `HeadBucketCommandInput`, `StreamEvent`, `Cons`, `StoreEnhancer`, `MemoizedFn`, `ReuseCustomContextMenu`, `GenericRetrier`, `ApiDef`, `Timings`, `Glue`, `ptr`, `AggregateRoot`, `IPluginPageProps`, `IpRecord`, `ClientOpts`, `AccountNetwork`, `ParseArgument`, `IpGroup`, `DashboardService`, `ISearchFeature`, `DevicesService`, `CameraHelper`, `PermissionStatus`, `SegEntry`, `SignaturePad`, `EffectAction`, `CreateDataSetCommandInput`, `DataRows`, `IWaterfallSpanOrTransaction`, `Events.exittrigger`, `CommandOutput`, `ActionCreatorFactory`, `ThemePlugin`, `RolesService`, `Mappings`, `SimpleGridRecord`, `ViewBox`, `MenuValue`, `TinaSchema`, `LexicalToken`, `GfxReadback`, `ts.Printer`, `WidgetIdTypes`, `IPolicy`, `Joi.ValidationResult`, `MyElement`, `PanService`, `TimeState`, `PayloadAction`, `UseMutationResult`, `DispatchQueue`, `ISummaryRenderer`, `GetBinaryPathsByVersionInput`, `FormDataEvent`, `ValidateKeyboardDefinitionSchemaResult`, `JsonMap`, `RibbonEmitter`, `BeachballOptions`, `SetOption`, `IngredientForm`, `SettingContext`, `CoreTypes.VisibilityType`, `ArrayServiceGetKeysByTreeNodeOptions`, `PolicyRequest`, `Inline`, `AVRExternalInterrupt`, `RippleConfig`, `Sampler3DTerm`, `fhir.Location`, `IClientOptions`, `PerformanceTiming`, `AtomicToken`, `AccountStore`, `ConnectionLocator`, `Puppeteer.Page`, `SigningCosmWasmClient`, `MapData`, `_Exporter`, `EducationalMaterial`, `KeyboardScope`, `FactoryBuilderQueryContract`, `TreeNodeViewModel`, `HydrationContext`, `CodeEditor.IToken`, `files.FullPath`, `RPiComponent`, `IAngularMyDpOptions`, `IVector3`, `ICreateData`, `IApiParameter`, `RexFile`, `ReferenceType`, `ITranslateConfig`, `MessageEntity`, `PathValue`, `Lut`, `Capability`, `InjectorType`, `Face`, `Beatmap`, `CallHierarchyItem`, `T.Task`, `IVpc`, `MarketFiltersState`, `IKeysObject`, `MemberExpression`, `requests.ListExternalNonContainerDatabasesRequest`, `FunctionComponent`, `NameNode`, `Single`, `NavSegment`, `GanacheRawExtraTx`, `FirebaseFirestore.Firestore`, `EquipmentSharingPolicy`, `ExtensionConfig`, `events.EventEmitter`, `SelectionInfo`, `OperationDefinition`, `LangiumDocument`, `MockNexus`, `BitMatrix`, `GrowStrategyMock`, `CheckResult`, `GfxRenderTarget`, `CreateUserInput`, `KeyedDeep`, `GaussianNoise`, `CGRect`, `EitherAsyncHelpers`, `TruncateQueryBuilder`, `JSDoc`, `BitcoinishTxBuildContext`, `TreeNodeState`, `UserGroupList_UserGroup`, `GetUrlFn`, `ParamModel`, `IPointUnit`, `MetricsOptions`, `Refetch`, `TargetList`, `GenericMeasure`, `FloatTerm`, `MessagePriority`, `IStringFilter`, `CustomUIClass`, `EventItem`, `ILifecycle`, `MessageTag`, `IsBound`, `DBMethod`, `MutableMatrix33`, `IteratorWithOperators`, `FlatRow`, `IGuildMemberState`, `SatRec`, `PaymentTester`, `LeafCstNode`, `EmptyParametersGatherer`, `Hotkey`, `Auction`, `child_process.SpawnSyncReturns`, `FModel.DllFuncs`, `OwnPropsOfControl`, `MemoryNavigator`, `MDCDialogAdapter`, `SalesforceFormFields`, `UiService`, `RequestBodyParserOptions`, `ModelAndWeightsConfig`, `BespokeClient`, `Functor2`, `BroadcastOptions`, `PanelOptionsEditorBuilder`, `CreateRepositoryCommandInput`, `UserInfoOidc`, `Events.collisionend`, `digitalocean.Account`, `DAL.KEY_BACKSPACE`, `GetTranscriptCommandInput`, `IHeaderProps`, `MenuPopperProps`, `SafeStyle`, `MyNode`, `GeoContext`, `DeleteAnomalyDetectorCommandInput`, `DatabaseResultSet`, `Attrs`, `IdxTree`, `IHighlight`, `School`, `PreviewData`, `MultiEmitter`, `GraphicsShowOptions`, `ScriptTags`, `VisitorFunction`, `ParsedRule`, `Models.KeyValuePair`, `EmitNode`, `CreateSecurityConfigurationCommandInput`, `ProofNode`, `FormatResult`, `AzureSubscription`, `BalanceRequest`, `StateOptions`, `zmq.Dealer`, `RegisterDto`, `MerchantMenuOrderGoodsInfo`, `AttachmentMIMEType`, `IIteratorResult`, `FeatureConfig`, `FormValueType`, `ColumnBuilder`, `AuthInfo`, `INodeHealthStateChunk`, `AccountFacebook_VarsEntry`, `XroadConf`, `Functor1`, `PendingWrite`, `IExecuteResponsePromiseData`, `PlayerProp`, `requests.ListComputeCapacityReservationInstancesRequest`, `RoverStateReturn`, `StorageOptionsChangeData`, `EnvironmentManager`, `StrapiModel`, `BaseTheme`, `HyntaxToken`, `AreaLightInfo`, `MIDIAccess`, `Invitation`, `ISessionService`, `QuizServices`, `Cookies.Cookie`, `SiteMetadata`, `SharePublicKeyOutput`, `DNode`, `DataTypesInput.Struct1Struct`, `InspectPropertyReport`, `ContractPrincipal`, `DrawerContentComponentProps`, `MarkdownDocument`, `AwsEsdkKMSInterface`, `IDataTableColumn`, `FileWrapper`, `BlockArchiveLine`, `DataTransferItem`, `RecordColumn`, `ExpansionPanel`, `IUserSettings`, `Protocol.Network.RequestWillBeSentEvent`, `Ast`, `NumberKey`, `PlotCurveTypes`, `IAmazonServerGroupCommandResult`, `PlayerStat`, `ContractCallOverrides`, `GeoPolygon`, `Scan`, `Deck`, `ICommandContext`, `GetZoneRecordsResponse`, `OrderBookOrderDTO`, `Chainable`, `BookmarkItem`, `IAppSettings`, `QueryMessage`, `PairData`, `Datastore`, `LayoutOptions`, `TaskConfigurationScope`, `AttributeServiceOptions`, `TextElementStyle`, `IMoonData`, `DescribePipelineCommandInput`, `Gateway`, `FieldFormatsGetConfigFn`, `GraphQLTagTransformContext`, `Types.PostId`, `URLTokenizer`, `ArenaSelection`, `ScaleData`, `OnlineUserType`, `SettingGroup`, `ConfirmDialogDataModel`, `CallCompositePage`, `UpdateSiteCommandInput`, `ImportCacheRecord`, `FieldValidateConfig`, `LRUMap`, `Dex`, `LeagueStore`, `ReportingInternalSetup`, `NamespacedWireCommit`, `Analytics`, `ImageEnt`, `vscode.CustomDocument`, `RowId`, `RowRenderer`, `RestConfigurationMethodWithPath`, `requests.ListPluggableDatabasesRequest`, `BNString`, `DistributionData`, `GlobalInstructionType`, `OperateBucketParams`, `CanvasTextAlign`, `SBDraft2ExpressionModel`, `MapOptions`, `ListProjectsResponse`, `Http3PrioritisedElementNode`, `TransitionableCielchColor`, `Discriminated`, `ConsCell`, `Rectangle`, `MouseAction`, `BitcoinCashSignedTransaction`, `requests.ListAlarmsStatusRequest`, `GetOperationCommandInput`, `DeleteDatabaseCommandInput`, `AccessoryTypeExecuteResponse`, `SynthBindingName`, `CustomizePanelProps`, `Component`, `DocfyResult`, `ValidatorFn`, `WordInName`, `PredicateFn`, `Unsubscribe`, `OnSubscriptionDataOptions`, `RouteView`, `VuforiaSessionData`, `GatewaySession`, `IMatrixFunc`, `BaseScope`, `BTree`, `APIResponseCallback`, `ContainerItem`, `APIChannel`, `RayPlaneCollisionResult`, `DigitalCircuitDesigner`, `NodeWallet`, `GlobalSearchResult`, `OptionsType`, `AccessKeyRepository`, `IKeyRing`, `EntityCreate`, `IntegrationClass`, `BaseParams`, `ResizeHandle`, `PropSidebarItem`, `ISecurityGroup`, `Jimp`, `JhiEventManager`, `LCImpl`, `ModelFitArgs`, `IOverlayAnimationProps`, `SSRHelpers`, `ITokenProvider`, `SendCustomVerificationEmailCommandInput`, `CanvasContext`, `AppInfo`, `MonthData`, `ProjectListModel`, `ISequencedClient`, `Primitive`, `ControlFlowInfo`, `AddApplicationInputProcessingConfigurationCommandInput`, `TestMessagingService`, `SimpleAuthenticationDetailsProvider`, `ValidationData`, `CreateCategoryDto`, `ApiNotificationReceiver`, `ThemeIcon`, `OtokenInstance`, `utils.BigNumber`, `SecurityRating`, `Tagname`, `LifecycleFlags`, `ResolvedAxisOptions`, `RequestNode`, `SharedState`, `ResourceLink`, `ObjectSize`, `FirewallPolicy`, `ERC1155Mock`, `CategoryEntity`, `Venue`, `SocketChannelClient`, `FileUploadService`, `CheckPrivateLinkServiceVisibilityRequest`, `NameStyle`, `ChangeFlag`, `CFMLEngineName`, `WsService`, `IGameChara`, `WalletConnectProvider`, `FourSlash.TestState`, `Creature`, `fs.FileStorageClient`, `MultipleTypeDeclaration`, `SFOverrides`, `LogWidget`, `UnaryOperationNode`, `DataRecord`, `RecordItem`, `VProps`, `JPartition`, `ConvertedLoopState`, `ActionsInTestEnum`, `DeleteWorkRequestResponse`, `BridgeMessage`, `Types.NavigatorRoute`, `SelectionTree`, `FormPropertyFactory`, `GetShardIteratorCommandInput`, `MileStoneName`, `ActionTypeConfigType`, `OnRenderAvatarCallback`, `IAsyncEnumerable`, `ParsedDateData`, `HTMLVmMenuItemElement`, `RunData`, `ImagesContract`, `MockableFunctionCallCompiler`, `IChannelServices`, `UnicodeUtils.Direction`, `TProductCategory`, `Checker`, `HostClient`, `SessionKey`, `SynchrounousResult`, `IPodFile`, `ThemedStyledProps`, `TokenSet`, `TilePathParams`, `UIntArray`, `SVGStopElement`, `IApiExternalDocumentation`, `IComponentOptions`, `VisibilityVertexRectilinear`, `DeleteCustomVerificationEmailTemplateCommandInput`, `IBlobMetadataStore`, `MarkdownPostProcessorContext`, `IncomingHttpRequest`, `ToneAudioBuffers`, `Anim`, `BigIntConstructor`, `House`, `ChannelIdExists`, `HashMapEntry`, `SagaIteration`, `WithExtends`, `VerificationInitiateContext`, `BoxConstraints`, `React.Component`, `DialogLanguageModule`, `IndexPatternLayer`, `Stage`, `HoverResult`, `QueryTopicForHolder`, `AuthHelper`, `CoreService`, `TextElementGroupState`, `FocusMonitor`, `ListDedicatedIpPoolsCommandInput`, `APIResponseType`, `UiObject`, `GetDataSourceCommandInput`, `HandlerStack`, `PageG2`, `FILTERS.CUSTOM`, `ScreenReaderPartitionTableProps`, `SettingsPropsShared`, `NotebookPanel`, `PolicyService`, `QuerySuggestionGetFn`, `AutoImportResult`, `UIDialogRef`, `LinkedSearchProps`, `IntrospectionSchemaVersion`, `ConfigFlags`, `UnitStateMachine`, `OffscreenCanvas`, `ReplicatorQueries`, `OasDocument`, `TaskClient`, `WithEmptyEnum`, `ReadRequest`, `TaskInputs`, `UInt`, `SearchAllIamPoliciesRequest`, `UseGenerateGQtyOptions`, `DescribeSObjectResult`, `JSONSearchParams`, `Yendor.IPersister`, `ILanguageTemplate`, `Meta.Window`, `RawDatum`, `Watcher`, `d.ScreenshotConnector`, `ComponentLoader`, `Snippets`, `PythonPreviewManager`, `GrantInterface`, `IsAny`, `UpdateAvailableEvent`, `XmlEnumsCommandInput`, `ChannelStoredData`, `MockResource`, `DiezComponent`, `SyntaxErrorConstructor`, `BankAccount`, `cytoscape.NodeSingular`, `SizedBox`, `RuntimeBot`, `ImageResolution`, `DecipherCCM`, `SchematicTestRunner`, `Electron.Session`, `Controller`, `RefreshableView`, `Dialogic.InstanceEvent`, `IntrospectionOptions`, `RecordInput`, `MediatorService`, `DeepReadonly`, `TimeRangeLimit`, `ex.Input.KeyEvent`, `IContentType`, `Analyser`, `QRProvisioningInformation`, `DialogflowConversation`, `VertexDescriptor`, `RotationalSweep`, `RemoteTrackInfo`, `ParameterCondition`, `DataSourceOptions`, `IGitService`, `IConnectableBinding`, `IMemoryTable`, `PiPrimitiveProperty`, `NotificationCCReport`, `TaskIDPath`, `TypeOfExpression`, `DiskEncryptionSet`, `XPConnectService`, `O.Option`, `QueryEngineRequest`, `BootOptions`, `TerraformBaseCommandInitializer`, `SystemDomainApi`, `SnippetNode`, `Apollo.QueryHookOptions`, `GetFolderCommandInput`, `I18nMutateOpCodes`, `IGenericDeclaration`, `OfIterable`, `SpotifyWebApiJs`, `RSSSource`, `TUserAccountProvider`, `JoinBuilder`, `AuthenticationClient`, `OperationResult`, `AccessModifier`, `MigrateReset`, `TextElementBuilder`, `ImageAsset`, `CacheManagerContract`, `DescribeSessionsCommandInput`, `CompleteMultipartUploadCommandInput`, `DocumentClient.QueryInput`, `MigrationParams`, `ScrollSpiedElementGroup`, `RoastingMachine`, `StackContext`, `EditorOpenerOptions`, `PartialDeep`, `Ancestor`, `TrackedImportAs`, `PixelFormat`, `ChartDimensions`, `DateTimeModel`, `MidiValue`, `GeneratorProcess`, `QueueSendMessageResponse`, `SeriesIdentifier`, `ProcessLock`, `PrismaClientDMMF.Document`, `ClassProvider`, `PDFButton`, `FileSyntax`, `ISlickRange`, `Background`, `ProtocolConnection`, `FeatureVersion`, `CloudWatchLogs`, `ToastrManager`, `IndexLiteral`, `ChildWindowLocationProps`, `EMSSettings`, `PiValidatorDef`, `typescript.SourceFile`, `FileEvent`, `OperatorPrecedence`, `XYAxis`, `ManifestContext`, `NavigationType`, `DOn`, `State.FetchStatus`, `EntityIdentity`, `ValidatorSet`, `PagedRequestDto`, `Gadget`, `EventHandlerFn`, `ModalPage`, `PrecommitMessage`, `TestContext`, `PullRequest`, `ModeController`, `ClockHand`, `FsObj`, `CanvazNode`, `DomPortalOutlet`, `Problem`, `EntityOptions`, `AccessTokenScopeValidator`, `Scatterplot`, `Stopwatch`, `LinearlyReferencedFromToLocationProps`, `Exporter`, `ts.SyntaxKind`, `UIProps`, `ImportAliasData`, `IResolvedConfig`, `ISDK`, `ChatBaseSelectorProps`, `BrowserInfo`, `TexMatrixMode`, `DeclarationBlock`, `SecureNote`, `GrantType`, `MigrationOpenSearchClient`, `EulerRotation`, `DbSmartContract`, `CurrencyPair`, `ScanDirection`, `IndicesArray`, `Microgrammar`, `ProtocolError`, `ValidateResponse`, `CalibrationPanelProps`, `KeyboardNavigationHandler`, `MdcRadioGroup`, `DebugProtocol.EvaluateArguments`, `KeyModel`, `IAreaItemLevel`, `SfdxCommandlet`, `CachingLogViewer`, `IssueOptions`, `ITemplatizedLayout`, `MediaStreamTrack`, `VoiceFocusConfig`, `ExtendedArtifact`, `RpcRemoteProxyValue`, `AncestorDefs`, `LSA`, `CreateConnectionDTO`, `RouterReducerState`, `Decoded`, `CompilerBuildResults`, `HTMLParser`, `IReferenceType`, `RoomData`, `Fact`, `EncryptionConfiguration`, `I18NLocale`, `CollectionChangedEventArgs`, `AutoScaling`, `ProcedureRecord`, `DeleteProjectCommand`, `Omit`, `IWorker`, `DocumentInput`, `MealTicketRemoval`, `GridConfig`, `IMessageHandler`, `HttpRequestWithLabelsAndTimestampFormatCommandInput`, `IEditorMouseEvent`, `NamedItem`, `DashboardCellView`, `Cropper`, `MyMap`, `VmNetworkDetails`, `AnalysisResponse`, `TCssTemplate`, `DeleteBotCommandInput`, `ICorrelationTableEntry`, `ANC`, `DatatableVisualizationState`, `StandardContracts`, `VertexTypeStore`, `t`, `RedocNormalizedOptions`, `QueriesResults`, `TrackedMap`, `HarmonyAddress`, `FlowNarrowForPattern`, `NVMParser`, `StateBottomSheet`, `XHROptions`, `VideoProps`, `IResolvedIDs`, `DidDocumentBuilder`, `LexicalScope`, `Vin`, `ProsemirrorNode`, `TypeContent`, `Locator`, `BalmConfig`, `PerformAction`, `SearchProfilesCommandInput`, `PipeTransform`, `CreateClusterResponse`, `BatchPutMessageCommandInput`, `requests.ListDrgRouteDistributionStatementsRequest`, `GQLType`, `AthleteSnapshotModel`, `IssueCommentState`, `Cursor`, `CurrentRequest`, `BlockDeviceMapping`, `BtcUnlock`, `PythonVersion`, `BeInspireTreeNode`, `RoleResolvable`, `RemoveFromGlobalClusterCommandInput`, `ABIReturn`, `ProgressType`, `BrowserBehavior`, `ChannelInfo`, `ISelection`, `ITdDataTableSortChangeEvent`, `PartialC`, `Events.pointerdragmove`, `DeleteEnvironmentCommandInput`, `KernelMessage.IMessage`, `AlertsClient`, `MerchantGamePrizeEntity`, `WidgetControl`, `LRU.Options`, `ex.Actor`, `AssetsList`, `HeadingNode`, `AssetData`, `BoxUnit`, `Convert`, `ShaderId`, `GetPostsResponse`, `IngressSecurityRule`, `NonlocalNode`, `SavedObjectSaveOpts`, `InjectionError`, `Rebuilder`, `BlueprintContainer`, `AsyncThunks`, `TaggedLiteral`, `DatatableRow`, `ODataNavigationPropertyResource`, `DescribeTagsCommandOutput`, `types.TracerBase`, `WorkflowOutputParameterModel`, `IEquipmentSharingPolicy`, `ElementDescriptor`, `FeedItem`, `Hapi.Request`, `MinecraftLocation`, `SetShape`, `LexoRankBucket`, `TileImageSize`, `ChokidarEvents`, `GridState`, `InfoDialogService`, `BottomNavigationTabBase`, `RafCallback`, `DoorLockLoggingCCRecordGet`, `InstanceTargetWithMetadata`, `RemoteRequest`, `ISlideObject`, `Regl`, `ClientPlugin`, `CancellablePromiseLike`, `RComment`, `NumberW`, `SvelteDocumentSnapshot`, `EntityFactory`, `WalletResult`, `AnnotationWriter`, `AnalyzerService`, `TextLine`, `LimitToPipe`, `JSONType`, `SearchScope`, `TokenIdentifier`, `CategoricalAggregate`, `DragResult`, `ILiteralExpectation`, `InteractiveConfig`, `Schedule`, `ICloudTimerList`, `SFU`, `AsyncHook`, `DeleteDatasetCommandOutput`, `TrailImage`, `MIRBody`, `IObjectWithKey`, `TabHandler`, `WebCryptoDecryptionMaterial`, `PTG`, `TemplateElement`, `LongTermRetentionPolicy`, `BatchConfig`, `OnLoadParams`, `AlainSTConfig`, `IToastCache`, `IPanesState`, `TeamModel`, `ShallowStateItem`, `CSSProperty`, `BarSeriesStyle`, `ProjectContainer`, `TypeValue`, `Movie`, `JSDocMethodBodyCtx`, `CompletionProvider`, `PageObjectConstructor`, `PluginVersionResource`, `PeerTubeServer`, `RectangleEditOptions`, `MarkerElement`, `ExprNode`, `SerializableError`, `MockConfig`, `KudosTokenFactoryService`, `ImportMap`, `ContextShape`, `MaterialVariant`, `TLE.NumberValue`, `AccountsOperationStep`, `IVirtualRepeater`, `UseMetaState`, `GenericError`, `SimpleContext`, `AwsServiceFactory`, `PairingTypes.Proposal`, `AdaptElementOrNull`, `AnalysisRequest`, `TickOptions`, `IDateUtils`, `ResultTree`, `RNNCellForTest`, `MongooseFilterQuery`, `GenericStyle`, `IServiceWizardContext`, `TrackedCooldown`, `WebDriver2`, `TargetGroupAttachment`, `MyClassWithReturnExpression`, `FactoryDatabase`, `OptionalDefaults`, `GX.TevBias`, `LockFile`, `DialogItemValue`, `FragmentMap`, `SelectorList`, `MalSymbol`, `TopologyObjectId`, `IEmployeeJobPost`, `IPropertyGridEditor`, `FasterqLineModel`, `ConvLSTM2D`, `AtToken`, `PostContentDocumentRequest`, `NgrxJsonApiStore`, `LiveDatabase`, `XPCOM.nsIJSID`, `ReactiveVar`, `FlexItemStyleProps`, `ElectricRailMovingPoint`, `MonitorRule`, `ApiRequest`, `AnnotationPointType`, `AbstractGraph`, `def.Vec2`, `LucidRow`, `SceneModel`, `MilestoneDataPoint`, `RightResolvable`, `RuleType`, `WeightsManifestConfig`, `IosDependency`, `NzDebugConfig`, `JPAExTexBlock`, `ts.NodeFactory`, `k8sutils.KubeClient`, `providers.WebProvider`, `Field.PatchResult`, `TransactResult`, `RequestType2`, `CoreOptions`, `SingleSigSpendingCondition`, `ElementProperties`, `http.RequestOptions`, `SingletonList`, `X12Interchange`, `TSESTree.Statement`, `CacheManager`, `RxSlpStream`, `PivotItem`, `VersionPolicy`, `DriveNumber`, `VcalAttendeeProperty`, `Until`, `INestApplicationContext`, `BeaconBlockHeader`, `AuthData`, `TestResolverDTO`, `FabricGatewayConnectionManager`, `UserRegisterResource`, `OutPoint`, `IFluidCodeDetails`, `ApolloMutationElement`, `DaffOrderReducerState`, `PromiseExtended`, `SWRInfiniteConfiguration`, `ConnectionDTO`, `SelectBox`, `UserToken`, `AxisOrder`, `DejaTile`, `PropMap`, `TView`, `MenuConfig`, `TkeyStoreItemType`, `ToggleCurrentlyOpened`, `BlockFile`, `BaseFullNodeDeploymentConfig`, `PouchDB.Core.Document`, `OfflineContext`, `ContractTxQueryResult`, `Printer`, `LinkProps`, `PackageInfo`, `InferenceContext`, `CodeCommit`, `SKFrame`, `CSSService`, `Bookmark`, `PayloadBundle`, `Serie`, `TypeormRawSetting`, `IGrammar`, `RelationsOpts`, `ComponentsObject`, `ThyTreeSelectNode`, `StaticLayoutProps`, `IBidirectionalIterator`, `ILicense`, `CliCommand`, `StackCollection`, `EvCallData`, `GetObjectOutput`, `NumId`, `OidcSession`, `VideoState`, `JSDocTemplateTag`, `BarcodeInfo`, `K8sResource`, `UserPoolClient`, `inversify.Container`, `Grant`, `JSONRPCClient`, `STEP_RECORDS`, `NodeMessage`, `OutputTargetDistTypes`, `Pilotwings64FSFile`, `DeleteSecurityProfileCommandInput`, `ImpressionSender`, `RefObject`, `NDArrayMath`, `DeleteTagsRequest`, `CausalTree`, `SizeLimitChecker`, `PathStartCoordinates`, `MultisigTransaction`, `HttpRequestWithLabelsCommandInput`, `XMLDocument`, `DealStage`, `SdkAudioMetadataFrame`, `ISong`, `HandleOutput`, `TxnIdString`, `FaviconOptions`, `ForeignKeySpec`, `ListField`, `P2PInternalState`, `SponsorsResponseNode`, `Trader`, `IVirtualPosition`, `CapabilitiesSwitcher`, `KanbanBoard`, `HashFunction`, `RadixAccount`, `GLsizeiptr`, `FeatureGroup`, `Finder`, `ApplicationEntity`, `EquipmentSharing`, `EntitySubject`, `CodeModel`, `IMedal`, `TargetLocation`, `ChangeSetQuery`, `IRecurringExpenseDeleteInput`, `ITemplateDiff`, `AVPlaybackStatus`, `RenderTreeFrame`, `ObjectWithType`, `CamlQuery`, `IComponentDesc`, `FrameOverTime`, `BlobLeaseAdapter`, `CallMessage`, `UserRefVO`, `FloatArray`, `INodeCredentialDescription`, `BaselineFileContent`, `IApiRequestBody`, `NSApplicator`, `VdmMapping`, `DispatchType`, `requests.ListModelDeploymentShapesRequest`, `DeclineInvitationsCommandInput`, `ContextStore`, `AnimationData`, `ErrorWidget`, `TEUopType`, `SyncCommandWithOps`, `NginxDirective`, `d.CompilerCtx`, `ToolbarChildrenProps`, `Recorded`, `LeaguePriceDetails`, `DistanceFn`, `MockStoreAction`, `TaskCommand`, `HttpUrlGenerator`, `KleisliIO`, `DecoratedModelElement`, `SecretVerificationRequest`, `DisjunctionSearchQuery`, `TagsService`, `ResourceNotFoundException`, `Ray`, `ISceneData`, `ITranslationResult`, `T17`, `jest.SnapshotSerializerPlugin`, `ProjectService`, `DataConverter`, `FileChangeType`, `ChartBase`, `HTMLVisualMediaElement`, `GenerationNum`, `HttpClientOptions`, `MouseUpAction`, `ParameterContext`, `ArtifactStore`, `LastColumnPadCalculator`, `PartialBindingWithMeta`, `JsonDocsProp`, `FieldValidation`, `J3DModelInstanceSimple`, `ScannedReference`, `HasInfrastructure`, `ShaderAssetPub`, `TableServer`, `ValueSetterParams`, `SmartStartProvisioningEntry`, `ExternalRouteDeps`, `Neo4jConfig`, `AbstractCartProxy`, `KeyValueChanges`, `_ResourceConstantSansEnergy`, `ThemePrepared`, `RPGGame`, `requests.ListFileSystemsRequest`, `ResetPasswordAccountsRequestMessage`, `TagRenderingConfigJson`, `Bamboo`, `GLBuffer`, `KeyIndexMap`, `CreateHsmCommandInput`, `DownloadTarget`, `CircuitBreaker`, `SpeedtestResult`, `IBookmarks`, `StreamResetOutgoingParam`, `Side`, `App.windows.window.IOverlay`, `DebounceSettings`, `AuxResult`, `ClassIteratorFlags`, `PotentialPartnerActions`, `CreateProjectCommandInput`, `CoreExtInfo`, `ScopeState`, `PresentationTreeNodeLoaderProps`, `ItemDescription`, `VisTypeOptions`, `PanelPlacementMethod`, `ToolRunner`, `ColumnDescription`, `IWorkerModel`, `Fp2`, `BaseOptions`, `DOMError`, `InsertNodeOptions`, `HandlerProps`, `ManagedInstance`, `FormItemProps`, `HorizontalTable`, `IFieldType`, `IUser`, `NavigationTransition`, `ODataQueryOptions`, `KeylistUpdateMessage`, `TextDocumentIdentifier`, `VisTypeAlias`, `CoursesCounter`, `VirtualRepeat`, `Violation`, `LastfmTrack`, `ModifiersArray`, `TextArea`, `IQuestion`, `DependencyTracker`, `RecordedDirInfo`, `ts.BindingName`, `THandler`, `ESLMediaRuleList`, `RtcpReceiverInfo`, `RouteOpt`, `OrExpression`, `DomainInfoCache`, `MinionsController`, `Bzl`, `ActionContext`, `Conf`, `PipeCallback`, `ThyAbstractOverlayOptions`, `RestContext`, `HitSensorType`, `PropValidators`, `BoxColliderShape`, `TextFieldProps`, `GetUpdatedConfigParams`, `Path`, `CancellationTokenRegistration`, `RotationOrder`, `ActivatedRouteStub`, `Node_Annotation`, `ALBEvent`, `GetThreadResponseType`, `AbbreviationNode`, `MIRBasicBlock`, `RegisterData`, `ISecurityToken`, `SplashScreen`, `BackendType`, `ProductAnalyticalResult`, `firestore.GetOptions`, `UserTokenPolicy`, `GroundPlane`, `CharacterMaterial`, `NOTIFICATIONS_STATUS`, `ContractCallBuilder`, `QueryType`, `BlockchainLink`, `peerconnection.DataChannel`, `TestRequestResponse`, `visuals.Coord`, `GetClientFunction`, `ConfigSetName`, `CaseDesc`, `EncryptedSavedObjectsPluginSetup`, `IDeployState`, `FederatedAdapterOpts`, `Handle`, `Flag.Parser`, `SelectionNode`, `Streak`, `PReLULayerArgs`, `AdtLock`, `RecentCompletionInfo`, `PlayerController`, `IOProps`, `InternalCase`, `SQLiteDatabase`, `Toucan`, `Colony`, `three.Mesh`, `HTMLVmPlayerElement`, `SourceStream`, `ExportSummaryFn`, `IOutputs`, `DiagnosticReporter`, `TenantId`, `FlowElement`, `ComponentType`, `RunSegment`, `GitRepo`, `requests.ListDatabasesRequest`, `QueryFunction`, `JSZip`, `UnsignedTransaction`, `KC_PrismHit`, `BuiltLogic`, `Prefetch`, `DatabaseBundle`, `IAboutService`, `InjectedAccountWithMeta`, `RoutingIntent`, `ObjectBindingOrAssignmentPattern`, `PutReportDefinitionCommandInput`, `ListSession`, `AuthHeaderProcessor`, `TestSolo`, `EDateSort`, `V1CommandLineToolModel`, `Enemy`, `DirectiveTransform`, `ProgressEvent`, `JSDocFunctionType`, `GraphQLConfig`, `TupleNode`, `PaymentOptions`, `ts.Token`, `CursorModel`, `QueueEntry`, `QueryExecutor`, `MultiSliderProps`, `CausalRepoObject`, `UserOptions`, `ShEnv`, `HistoryEvent`, `IRECProductFilter`, `IBinaryData`, `IPackageRegistryEntry`, `MockGuild`, `PartyPresenceEvent`, `TemplateAnalysis`, `ActorLightInfo`, `Member`, `protos.common.SignaturePolicy.NOutOf`, `IInboxMessage`, `Signature`, `SignDocWrapper`, `TenancyEntityOptions`, `SIOPRequestCall`, `CommonVersionsConfiguration`, `EvaluatedNode`, `ObjectFactory`, `KeyCompoundSelector`, `OctokitType`, `RemoteNodeSet`, `Reflector`, `VariantObject`, `CompressedPatch`, `GenericNack`, `PaletteDefinition`, `CliApiObject`, `SpriteStyle`, `Tournament.TournamentConfigsBase`, `TestERC20`, `CookieEchoChunk`, `CardRenderSymbol`, `QueryTreeNode`, `IDownloadFile`, `IAccountsState`, `Error`, `Feedback`, `IndexedTechnique`, `ModelShape`, `SecurityGroupRulePorts`, `TDest`, `MeetingSessionConfiguration`, `AParentInterface`, `Extensions`, `GQLQuery`, `OverlayRef`, `System_String`, `IField`, `Doc`, `Dimensions`, `NestedStructuresCommandInput`, `PointerAbstraction`, `ScriptType`, `UpdateIPSetCommandInput`, `Promisify`, `ModelArtifactsInfo`, `MapObjectAdapterParams`, `DiscoverInputSchemaCommandInput`, `SheetContainer`, `CannonColliderShape`, `Mnemonic`, `OnConflictBuilder`, `Credentials`, `TextMeasure`, `MapComponent`, `CloudDevice`, `Balance`, `DownloadRequest`, `CombatPlayerComponent`, `DebugEditorModel`, `StatelessComponent`, `MicroframeworkLoader`, `CommitIdentity`, `IInfectionOptions`, `HydrateAnchorElement`, `TQuery`, `AnimationArgs`, `TEnumValue`, `DebugProtocol.PauseArguments`, `InterpolationFunction`, `PedComponent`, `THREE.Vector2`, `LintOptions`, `DescribeGroupCommandInput`, `DirectiveDefinitionNode`, `NodePhase`, `UserSettingsService`, `BlockedHit`, `IRootAction`, `EnvId`, `Signed`, `PictureGroup`, `DeleteRegistryCommandInput`, `AngularHttpError`, `SymbolMap`, `VmixConfiguration`, `MutationPayload`, `ChatType`, `BezierPoint`, `CustomerVm`, `MarkOperation`, `SdkStreamDescriptor`, `IDataFilterValueInternal`, `FMAT_RenderInfo`, `DestinationOptions`, `PermissionMetadata`, `RARCDir`, `NamingStrategy`, `TestFixture`, `FeedDict`, `AudioConfig`, `ArgumentDefinition`, `Anime`, `CountOptions`, `SerializedAction`, `BootstrappedSingleSpaAngularOptions`, `CallappConfig`, `SnippetsProvider`, `TrackingService`, `BoxrecBasic`, `CreateAssetCommandInput`, `PadplusRoomPayload`, `DispatchedPayload`, `IFormGroup`, `IDeliveryClientConfig`, `OscillatorType`, `Root`, `TimeoutOptions`, `IntersectionObserverEntry`, `StreamInterface`, `OptionLike`, `Character`, `Document`, `FrameNode`, `ConflictingNamesToUnusedNames`, `StackingContext`, `ResponseStream`, `TreeExtNode`, `JoinType`, `ChannelTypeEnum`, `RouteQuote`, `ListJobShapesRequest`, `CurriedFunction3`, `SystemInfo`, `SessionState`, `DCons`, `CheckConflictsParams`, `HttpClientService`, `USSTree`, `Texture`, `THREE.Intersection`, `ICachedResourceMetadata`, `EmptyIterable`, `RegistryService`, `DetachedSequenceId`, `VKeyedCollection`, `TitleTagService`, `MomentumOptimizer`, `ReplayDataMediator`, `BrowserType`, `FlatIndex`, `RTCCertificate`, `TimerHandler`, `BaseCoin`, `RegisterServerOptions`, `IndexRangeScanStep`, `RedundancyConfig`, `SecurityProviders`, `NSMutableArray`, `ModuleReference`, `ApiHttpService`, `CalendarState`, `IDataPerList`, `MessageImage`, `TextObject`, `Gui.VPanel`, `Maybe`, `MathjsBigNumber`, `GeoPoint`, `ParamAssignmentInfo`, `IMode`, `VdmProperty`, `ModuleOptionsWithValidateTrue`, `ToJsonProperties`, `Dynamics`, `AbbreviationInfo`, `RichTextComponents`, `NavigableSet`, `MatrixClient`, `JRPCRequest`, `IDanmaTrackInfo`, `ExpressionAstFunction`, `CheckpointWithHex`, `SetType`, `AsyncActionProcessingOptions`, `GLRenderer`, `ApiGatewayLambdaEvent`, `ContainerBinding`, `INodeStatus`, `MutationResult`, `ChatServerConnection`, `NavigationContainerRef`, `UniqueID`, `IDBDatabase`, `TsmOptions`, `d.OutputTargetHydrate`, `SwUpdate`, `AxiosHttpClient`, `float64`, `Community`, `VerificationContext`, `RX.Types.SyntheticEvent`, `SortValue`, `ItemShape`, `ProjectIdentifier`, `StartTagToken`, `HTMLCollection`, `CanaryMetricConfig`, `IUserAchievement`, `RecordRow`, `HoverFeedbackAction`, `CommonFile`, 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`ConcreteSourceProvider`, `PortProvider`, `ConfirmDialogService`, `DistanceQueryInterface`, `NumberParams`, `Mdast.Root`, `ResponseReaction`, `ExportRecord`, `SearchExpression`, `HowToPay`, `instantiation.IConstructorSignature5`, `Templateable`, `DSpaceSerializer`, `Propagation`, `UIBrewStorage`, `NumberConstructor`, `SuspenseListRegistryItem`, `Node_Const`, `ScopedProps`, `EncryptedData`, `GfxRenderInst`, `DebugBreakpoint`, `InventoryInteractionService`, `HorizontalPlacement`, `SubscriptionEntry`, `CorporationCard`, `Fraction`, `DtlsClient`, `ElevationProvider`, `ImageStretchType`, `MemoryDebe`, `FunctionConstructor`, `HierarchyFacts`, `ElTableStoreStates`, `server.DataLimit`, `GlobalReplicationConfig`, `InnerClientState`, `ISuggestion`, `y`, `IKibanaMigrator`, `TransactionView`, `JobCommand`, `StepFunction`, `ListFirewallPoliciesCommandInput`, `TimelineItem`, `WebGLExtensionEnum`, `TestFn`, `DejaSelectComponent`, `TestDeployRetrieve`, `LookupSorter`, `ChannelList`, `GauzyCloudService`, `ExpressionRegexBuilder`, `IFluidDataStoreContext`, `SelectorMap`, `SetDefaultPolicyVersionCommandInput`, `ReleaseChannel`, `ApiClientRequest`, `IWebhookData`, `MatMenuItem`, `GenerativeToken`, `Submitter`, `WorkspaceSummary`, `EC2Client`, `Kernel.IKernelConnection`, `FocusKeyManager`, `RootHex`, `React.HTMLProps`, `DebugProtocol.StepInArguments`, `ForwardingSchema`, `SafeSelector`, `SceneGraphNode`, `ScratchOrg`, `MongoClientOptions`, `https.ServerOptions`, `AbiEntry`, `ValueMetadataAny`, `AuthorizationNotFoundFault`, `FilterDescriptor`, `SignedMultiSigTokenTransferOptions`, `HandlerParamOptions`, `UserTokenAccountMap`, `Compression`, `ModOutput`, `LogsConfiguration`, `pe`, `BuildPipelineParams`, `TypeAST`, `ResourceKeyList`, `webpack.loader.LoaderContext`, `ZimCreator`, `NotFoundError`, `requests.ListImagesRequest`, `EnergyAmounts`, `search.SearchState`, `VisualizationsPlugin`, `CharacterClassElement`, `CommandBase`, `DeviceSize`, `ColorFilter`, `UpdateFolderCommandInput`, `ts.JSDocTag`, `ISortOption`, `EventToAsyncUnHandler`, `SuggestionWithDetails`, `IClaimData`, `ShValue`, `DisableOrganizationAdminAccountCommandInput`, `InlineResolveOptions`, `MetadataPackageVersion`, `WeakEvent`, `ParsedSchema`, `URLSearchParamsInit`, `Trap`, `OctoServerConnectionDetails`, `VisSavedObject`, `ArticleType`, `SendMessageData`, `ServiceDefinitionPaths`, `PackageListItem`, `DomainDeliverabilityTrackingOption`, `Progress`, `ListInvitationsCommandInput`, `WhereBuilder`, `CreateAccountsValidationResult`, `SpeechSynthesisEvent`, `TestLogger`, `IsolatedAction`, `ColumnDifference`, `PluginSettings`, `TreeviewNode`, `jest.MatcherUtils`, `CSSOutput`, `Regions`, `PullRequestState`, `XMLHttpRequestResponseType`, `PointS`, `TransferArgs`, `ColumnSubscription`, `CheckPrivilegesOptions`, `CombinedDataTransformer`, `firestore.DocumentSnapshot`, `StackParams`, `Json.Token`, `IGetUserInvitationOptions`, `MockCSSRule`, `ProseNodeMap`, `t.JSXElement`, `ExpansionModule`, `GlimmerComponent`, `EditHistoryCommit`, `UnsupportedSyntax`, `StandardMaterial`, `HttpOptions`, `DescribeOrganizationConfigurationCommandInput`, `GrpcEventEmitter`, `AuthAction`, `EventObject`, `PersistentCharacter`, `CreateSnapshotCommandInput`, `BigLRUMap`, `RootState`, `ExplorerState`, `TimeTicksInfoObject`, `AwaitNode`, `___JSE_XLSX___Node`, `SanityTestData`, `OnScroll`, `MenuService`, `ContentActionRef`, `BaseSettings`, `LazyLight`, `SchematicContext`, `EqualityComparer`, `CreateOptions`, `PluginInsertActionPayload`, `PaymentDataRequest`, `IDiff`, `AnimationTransitionMetadata`, `Actors.Actor`, `AsyncCommandWithOps`, `PipelineVersion`, `ZoneNode`, `INativeTagMap`, `ISQLScriptSegment`, `InsertBuilder`, `DaffStateError`, `BoundsOffsets`, `TestElementDrivesElement`, `FlexStyleProps`, `ACCategory`, `Oas3Rule`, `ContextAwareLogger`, `RemoteStoreRoom`, `DescribeAddonCommandInput`, `Sidekick`, `TToken`, `CollectionViewLayout`, `SequentialArgs`, `ContextTransformer`, `TestChannelArgs`, `UITraitCollection`, `ProxyConfig`, `TFLiteDataType`, `Stereotype`, `ObsoleteOptions`, `CreateDomainNameCommandInput`, `GoConditionalMove`, `vscode.Hover`, `CookieSettingsProps`, `PDFState`, `ExecutionPureTransitions`, `OrderStruct`, `TSQueryOptions`, `QueryResultRowTypeSummary`, `NodeURL.URL`, `SearchState`, `DataTableService`, `ShardingInstance`, `AaiMessage`, `DetailedStackParameter`, `TransactionEvent`, `NuxtConfig`, `PieVisualizationState`, `ServiceCollection`, `Statements`, `PluginConstructor`, `TSigner`, `CreateUserService`, `GoogleUser`, `PadchatContactPayload`, `DiscoveredClass`, `immutable.Set`, `VariablePart`, `CallHandler`, `ReducerWithInitialState`, `VideoStreamRenderer`, `Linters`, `ContentProvider`, `JStretch`, `IHookCallbackContext`, `RebootBrokerCommandInput`, `TitleTagData`, `GroupAction`, `AnimatorDuration`, `ProgramOptionsList`, `ParserFnWithCtx`, `AnimationProps`, `EasingFunction`, `UsageInfoHoverInfo`, `TypingIndicatorStylesProps`, 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`Commutator`, `CheckedObserver`, `Team`, `Provide`, `PuppeteerScreenshotOptions`, `OperatingSystem.Windows`, `StyleHelpers.QuoteInput`, `UserBuilder`, `NavigationTree`, `ChartConfiguration`, `DrawIOUMLDiagram`, `BlockchainGatewayExplorerProvider`, `d.ComponentConstructorWatchers`, `UserStatsState`, `TransactionFunction`, `ReactDataGridFilter`, `OverlayConfig`, `XPCOM.nsXPCComponents_Interfaces`, `AttributionsToResources`, `MessageType`, `IMongoResource`, `StoreConfig`, `IListFunctionOptions`, `NodeParameterValue`, `PersonState`, `project.Project`, `RouteHandler`, `IDs`, `OrderByNode`, `dKy_tevstr_c`, `MentionInputorElement`, `IChannelManager`, `compare`, `SettingDictionary`, `IColumnIndices`, `CSharpFieldType`, `Random`, `GetMetaDataFunction`, `RosettaOperation`, `TinderLike.Props`, `ObjectASTNode`, `ApiViewerTab`, `GraphQLSchemaNormalizedConfig`, `PreferenceInspection`, `BooleanValidator`, `ASStatement`, `AlertWrapperProps`, `PureTransitions`, `FooterProps`, `SpectatorHost`, `AtomTweeningNumberElement`, `IdentityProviderConfig`, `IonContent`, `ClipPrimitive`, `requests.ListManagedInstanceGroupsRequest`, `PlaneType`, `PAT0_TexData`, `FileCache`, `EngineMiddleware`, `FocusOrigin`, `void`, `BlokContainer`, `InternalPropertyObserver`, `LanguageOptions`, `Recommendation`, `PartitionFilter`, `CreateEmailIdentityCommandInput`, `InsightObject`, `Pong`, `MapMarker`, `GlobalState`, `SubPredArg`, `QueryFn`, `GraphQLFieldResolver`, `VisualizeAppProps`, `LoadMetricInformation`, `NavigatorRoute`, `NotebookEvents`, `SubnetAlreadyInUse`, `DiscordMockContext`, `DropHandler`, `RuleOptions`, `SolutionStackProps`, `FlashArguments`, `MinAdjacencyListArray`, `_NotificationConfig`, `IDocumentMessage`, `EnergyMap`, `ILanguageSyntax`, `GravityType`, `ExtraFieldDetail`, `ContainerAdapterClient`, `SMA`, `MDCProgressView`, `StubXhr`, `Var`, `PlaintextMessage`, `HandleResult`, `PrepareEnvVariablesProps`, `GCPAuthOptions`, `CodeGeneratorContext`, `ConnDataType`, `UpptimeConfig`, `CallExpression`, `ControllerMetadata`, `CursorModelConfig`, `X509CertificateSupplier`, `ComposeSubscriber`, `ValidationRule`, `DocumentSnapshotCallback`, `MyAppProps`, `CloseReason`, `promise.Promise`, `AppNotificationManager`, `ToneBufferSource`, `TransitionOptions`, `ProgressAtDayModel`, `LevelActionTypes`, `StateSelectors`, `IDeployContext`, `AlignSelf`, `EntityDeserializer`, `PromiseRejectionEvent`, `QueryProviderAuditorRequest`, `NetworkData`, `Assets`, `QualifiedId`, `BoxProps`, `FrameBuffer`, `Shortcut`, `AngleSweep`, `ResourceTypes`, `SearchQueryBuilder`, `Styler`, `FooService`, `NodeWithId`, `TxType`, `NetworkProvider`, `V1APIService`, `Fn4`, `ModalsState`, `Events.pointerleave`, `WorkRequestResource`, `TransitionInstruction`, `PackageManagerType`, `DeleteModelCommandInput`, `TimelineHeaderWrapper`, `EcommerceItem`, `FindSelector`, `Necktie`, `NameOrCtorDef`, `ICoverageFile`, `IRemindersGetByContactState`, `RatePretty`, `React.ClipboardEvent`, `CategoryRendererItem`, `GitStatus`, `ExtensionItem`, `AureliaProgram`, `TestKeyring`, `SupportedService`, `TypeSignature`, `GetInstanceCommandInput`, `CallbackFunc`, `ChartSeries`, `WebrtcProvider`, `ERC721TokenDetailed`, `TradingPair`, `CentralSceneCCNotification`, `InstanceBlockDeviceMapping`, `RemoveEventListener`, `DataArray`, `JoinCandidateBuilder`, `StablePlace`, `IReportEmbedConfiguration`, `Proppy`, `Dirigibles`, `ByteSize`, `DebugProtocol.VariablesArguments`, `IBirthCompositionBody`, `ISharedFunction`, `PreventCheck`, `ConnectionInvitationMessage`, `ConfigService`, `ImmutableListing`, `AnyCoinCode`, `ProppyFactory`, `EthereumProvider`, `StackFrame`, `ConfigureOptions`, `BlockPath`, `AClass`, `cheerio.Root`, `MatOpN`, `GeneralState`, `TElementNode`, `CollectorOptions`, `WebGLActiveInfo`, `MakefileConfiguration`, `PickDeepObj`, `vscode.ConfigurationScope`, `InterfaceSymbol`, `GetDeliverabilityTestReportCommandInput`, `RlpSerializable`, `VisualizePluginStartDependencies`, `requests.CreateCertificateRequest`, `GfxProgram`, `IMilestone`, `TransferBatch`, `KeywordType`, `AnyRecord`, `TrainingZone`, `SidenavContextType`, `DataStore`, `GetGroupRequest`, `EarlyReturnType`, `redis.RedisClient`, `mb.IRecording`, `PropertyCategoryLabelFilterer`, `Duplex`, `LogStatement`, `DictionaryPlugin`, `RemoteFile`, `ConnectionWorkflow`, `PiScopeDef`, `DataSourceType`, `ChartJSService`, `SerializedPlayer`, `TransformedPoint`, `ImageHandler`, `XhrCompleteContext`, `MIMEType`, `LocationLink`, `WsConnection`, `Separate`, `CommandHandler`, `IGatewayRoom`, `TabStripItem`, `ProductTypeService`, `TreeElement`, `PianoNote`, `ISiteScript`, `IIterator`, `Agenda`, `IConnected`, `StkTruToken`, `GreetingWithErrorsCommandInput`, `MyOtherObject`, `FcUuidAuth`, `DropIndexNode`, `CandidateCriterionsRating`, `ts.InterfaceType`, `GeometryStreamProps`, `sdk.SpeechSynthesizer`, `IRectangle`, `M`, `DataContext`, `HTMLOptGroupElement`, `ComputedPropertyName`, `IConnector`, `ApplyChangeSetOptions`, `Auth0UserProfile`, `EventState`, `Box3Like`, `SinonSpy`, `TokenModel`, `ExpressionRendererEvent`, `FieldNameList`, `TestControllerPoint`, `RepositoryFile`, `MethodNode`, `TextMatchOptions`, `IOrderCreationArgs`, `AppWithCounterAction`, `AST.Regex`, `Strapi`, `FourSlashFile`, `ExploreState`, `BIP85Child`, `ListSchemaVersionsCommandInput`, `ArtifactSizes`, `MeshLambertMaterial`, `BigNum`, `PathResolverResult`, `Types.RouteCallback`, `LoginInfo`, `TransferValidatorStakeV1`, `Select`, `ColumnSeriesOptions`, `ChannelWrapper`, `ParseEvent`, `QueryBarTopRowProps`, `JSONSchemaType`, `KeyPairKeyObjectResult`, `NzI18nService`, `IDBPDatabase`, `MessageWriter`, `WsDialogService`, `RouteRecord`, `LocalStorageKeys`, `ElectronService`, `ListInputsCommandInput`, `FieldOptions`, `IndexedAccessType`, `StyleInfo`, `ExpRes`, `MessageResolvable`, `Curry`, `IStore`, `Prop`, `ProblemFileType`, `Equals`, `requests.ListWafBlockedRequestsRequest`, `Services.UIHelper`, `TypedBinOp`, `ClientCapabilities`, `IterableReadable`, `HexString`, `ApiProps`, `SExpressionRepl`, `EdgeCollider`, `Picture`, `Reject`, `ParentFiber`, `ENR`, `i64`, `IMapSettings`, `InputThemeConfig`, `AssemblyOption`, `Fn`, `MentionSuggestionsProps`, `ReactWrapper`, `XorShift`, `Rule.RuleContext`, `DalBoard`, `SendManyOptions`, `PageState`, `GitRemote`, `RawDraftContentState`, `InjectedMetadataSetup`, `egret.MovieClip`, `SbbIconOptions`, `ServiceUnavailableException`, `NodeWorkerMain`, `SocialError`, `CheckoutPaymentPage`, `ParentNode`, `Resume`, `FunctionFlags`, `Send`, `TextureProvider`, `RequesterBlockMap`, `GfxImplP_GL`, `LocalAccount`, `IMouseZone`, `HandlerMap`, `AssetKey`, `TemplateScope`, `Booking`, `ITdDataTableColumn`, `TestComponentProps`, `XAxisProps`, `OrganizationRecurringExpenseService`, `Parameter`, `SettingsStateType`, `STStyle`, `Primitives.Value`, `DBDriverResource`, `SchemaObjCxt`, `ICompiledFunctionCall`, `IPluginContext`, `MOCK_TYPE`, `RegExpCompat`, 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`PointerInfo`, `ProviderSettings`, `PingMessage`, `HTMLRewriter`, `SimpleRNNCellLayerArgs`, `GDQBreakBidManyOptionElement`, `RecordsGraph`, `TypeInferences`, `protos.google.iam.v1.ISetIamPolicyRequest`, `SearchPattern`, `RendererProps`, `ApiService`, `AuthContextData`, `DSVParsedArray`, `DescribeDBClusterSnapshotsCommandInput`, `HTMLScTooltipRowElement`, `TestConfigData`, `DidConfig`, `ContractKit`, `IModLoaderAPI`, `ILookUpArray`, `ParsedTypeDetailed`, `TxSummary`, `NewPackagePolicy`, `ContentLayoutProps`, `AngularExternalTemplate`, `IObjectInspector`, `ExpressionExecOptions`, `DoubleLinkKVStore`, `ts.ESMap`, `StyleResource`, `GroupBySpec`, `TargetElement`, `ActionSheetOptions`, `IterableProtocol`, `TestBadgeComponent`, `NpmPackageManager`, `V1Container`, `TypedNode`, `HasTaskState`, `UserConfig`, `CollectBBox`, `Decomposers`, `ItemSocket`, `IndyProof`, `ChannelPickerItemState`, `ProviderLibrary`, `MDCTabBarAdapter`, `Plugin_2`, `MessageTypeMapEntry`, `ModuleRpcServer.ServiceHandlerFor`, `ContainerRegistryEvent`, `TxGeneratingFunctionOptions`, `ConfigAccount`, `DeleteEventSubscriptionCommandInput`, `Inherits`, `UnicodeRangeTable`, `BasicGraphPattern`, `ResourceComputationType`, `SubmissionStatus`, `PureEffect`, `XPCOM.nsIComponentRegistrar`, `WebPhoneUserAgent`, `KeyframeNodeOwner`, `TriggerEvent`, `ValidateDeviceOwnershipQuery`, `ScrollIntoViewOptions`, `requests.ListPublishersRequest`, `SchemaValidator`, `UnresolvedLogs`, `HTMLWalkState`, `MinMaxSurroundAttestation`, `NodeJS.ReadableStream`, `DelonLocaleService`, `SubjectService`, `TSeed`, `NodeSelector`, `NewOrganizationDTO`, `RuleFixer`, `SyncServer`, `DAL.DEVICE_ID_BUTTON_RESET`, `Accessibility.PointComposition`, `IActorRdfDereferenceOutput`, `BroadcastTx`, `InterventionTipsStatuses.StatusIds`, `ArrayServiceTreeToArrOptions`, `Test2`, `QBFilterQuery`, `MeshLODLevel`, `BaseApplication`, `FinalEventData`, `AppEntry`, `FetchResolveOptions`, `ItemModel`, `ThumbnailModel`, 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`RowViewModel`, `View`, `MessageSerializer`, `FindingCriteria`, `CommonContext`, `Models.DiagnosticsSettings`, `Comparison`, `ScmResourceGroup`, `SubContext`, `ts2json.DocEntry`, `HsEndpoint`, `GlyphInfo`, `GetInvitationsCountCommandInput`, `Vorgangsposition`, `JRes`, `ConnectorType`, `LayoutType`, `Handlebars.HelperOptions`, `TimeFilterServiceDependencies`, `BaseNavTree`, `VimMode`, `DebugAction`, `StreamSelection`, `SpacesManager`, `HttpChannelWrapper`, `ExpressionFunctionClog`, `EmaSubscription`, `HttpLink`, `requests.ListJobRunsRequest`, `TileCoords3D`, `Ulong_numberContext`, `MagicRPCError`, `Transformable`, `FactoryProvider`, `PredicateNode`, `IButtonClickEvent`, `PushRPC`, `Augur`, `IPlatform`, `CssFile`, `KeyPairOptions`, `V1ClusterRole`, `PackageJsonInfo`, `KeyboardKeyWrapper`, `Build`, `requests.ListSecretsRequest`, `DataPublicPlugin`, `SignedTransaction`, `IdOrNull`, `FlattenedXmlMapWithXmlNamespaceCommandInput`, `DescribeAppCommandInput`, `SVGRectElement`, `requests.ListLocalPeeringGatewaysRequest`, `SubMiddlewareApi`, `OurOptions`, `FunctionDesc`, `GPUSampler`, `ReadonlyVec`, `MonitorState`, `ILineInfo`, `GetPolicyVersionCommandInput`, `LogicAppInfo`, `TransmartRelationConstraint`, `requests.ListNotebookSessionsRequest`, `DataModels.Correlations.ProcessInstance`, `AjaxAppenderConfiguration`, `SshSession`, `GitQuickPickItem`, `DataViewColumn`, `LineSelection`, `ErrorMessageTracker`, `DesktopCapturerSource`, `StoreActions`, `MockMessageClump`, `Constraint`, `AggregationCursor`, `ShellWindow`, `LITestService`, `UpdateEntrypoint`, `PDFPage`, `PubScript`, `DbAbstractionLayer`, `CollectionTypes`, `BaseAsset`, `MenuTree`, `requests.ListNodePoolsRequest`, `ITestRunnerOptions`, `MixinTable`, `LocaleData`, `InstancedBufferGeometry`, `GuardFunction`, `Listr`, `ImageEdits`, `ChunkList`, `FlexDirection`, `RollupBlock`, `requests.ListSteeringPoliciesRequest`, `GeneralName`, `TexGen`, `angu.Context`, `ClassDescriptor`, `AnyIterable`, `FlexboxLayout`, `IJSONSegment`, `GameDataStateRecord`, `ActionReducer`, `TNATxn`, `ComponentWithUse`, `MonitoringStats`, `d.BuildResultsComponentGraph`, `PropertyExt`, `DeprecationsFactory`, `Collector`, `TreemapNode`, `DataExtremesObject`, `PointOctant`, `SimpleRNNLayerArgs`, `AsyncPriorityQueue`, `TScope`, `RequestType`, `DaffOrderFactory`, `IScreenshot`, `AppMenu`, `ISourceOptions`, `React.Ref`, `NSNotification`, `PartyJoinRequest`, `BundleManager`, `CompilerError`, `JapaneseDate`, `JPAResourceData`, `enet.NetData`, `ReplyRequest`, `BinaryTargetsEnvValue`, `STDeclaration`, `MatchingLogic`, `SegmentGroup`, `LengthType`, `ProcessEnv`, `social.UserData`, `PrismaPromise`, `TLE.TleParseResult`, `ProjectOptions`, `TickerFuncItem`, `MediaSlot`, `_.Dictionary`, `ListIdentitiesCommandInput`, `VKFParamMap`, `HookTypes`, `StyleSheetList`, `EditorPackage`, `ClrDatagridStateInterface`, `RoutableTileWay`, `DockerContainerProps`, `TypeFeatures`, `SendCommandResult`, `DashboardPanelState`, `PopupModel`, 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`Events.postdraw`, `DocCollection`, `RouteDeps`, `IterationUI`, `CarouselItem`, `ChannelService`, `UpdateParticipantRequest`, `WType`, `RemoteAction`, `ArrayOption`, `MainModule`, `CipherCCM`, `TweenInput`, `StorageOptions`, `CreateUserCommandOutput`, `TemplateUnparser`, `SpriteSpin.Data`, `StateBlock`, `google.maps.MarkerOptions`, `ViewPortManager`, `BifrostProtocol`, `GraphStats`, `Vec`, `IRequestOptions`, `StylableModuleSchema`, `ClrFlowBarStep`, `CSharpMethod`, `ColumnsProps`, `BaseUnit`, `CollectionValue`, `RuleChild`, `VisibleTextLocator`, `L1L2Args`, `IInventoryItem`, `RequestType0`, `ProviderData`, `InviteActions`, `AbiItem`, `MatrixProvider`, `GetChildNodes`, `AiPrivateEndpointSummary`, `PluginKey`, `TextComponent`, `HTMLLineElement`, `HookFunction`, `SuiDropdownMenuItem`, `ConvLSTM2DCellArgs`, `StreamAddOutgoingParam`, `FuseConfigService`, `CircuitGroupCircuit`, `ZipsonWriter`, `Types.PresetFnArgs`, `PathTargetLink`, `XTableColumn`, `HtmlTagObject`, `CSVInput`, `CoreDeploy`, `NextApiReq`, `BoundAction`, `Folder`, `dia.Cell`, `MigrationMap`, `OutputMessage`, `AgentOptions`, `Koa`, `IntelliCenterConfigRequest`, `Stmt`, `ValueObject`, `CivilContextValue`, `PriceData`, `TestMochaAdapter`, `Touch`, `Highcharts.Options`, `ContractCall`, `CollectionViewer`, `B2`, `ParameterName`, `ILyric`, `NonExecutableStepCall`, `CreateAppRequest`, `AutoFeeLevels`, `SearchEnhancements`, `AuguryEvent`, `DaffGetCategoryResponse`, `ts.ImportClause`, `LContext`, `ITheme`, `RiskLevel`, `AddressBookConfig`, `KeyframeIconType`, `ResourceManager`, `TEvents`, `StructureContainer`, `FilterObject`, `DataAssetSummary`, `UpdateNetworkProfileCommandInput`, `PrivateEndpointDetails`, `DynamicTextStyle`, `CircleShape`, `TaskDto`, `NestedHooks`, `Fu`, `DescribeSnapshotsCommandInput`, `LogEntry`, `CustomCode`, `RefactorAction`, `CLIElement`, `TabStateReturn`, `DraggableData`, `Blok`, `EnumDeclaration`, `AnnotationsMap`, `VMenuData`, `InstanceDetails`, `BaseRecordConstructor`, `CompletionPrefix`, `IssuesCreateCommentParams`, `d.ComponentCompilerProperty`, `ShortcutsTypes`, `DebuggingMode`, `TableSchema`, `SeederCollection`, `PartyMatchmakerAdd`, `LogicalQueryPlan`, `MapViewApp`, `ManualClock`, `requests.ListBootVolumesRequest`, `BlocksModel`, `TaskObserversUnknown`, `TransformCssToEsmOutput`, `TEmbeddableInput`, `OperationType`, `OhbugClient`, `Models.QuotingParameters`, `BarProps`, `Feature`, `TreeSelectItem`, `TokenPayload`, `INodeInfo`, `SketchLayer`, `VChild`, `ViewportScrollPosition`, `requests.ListStreamPoolsRequest`, `IAward`, `TaskTypes`, `IterableX`, `DeleteEmailTemplateCommandInput`, `ResolveInfo`, `LanguageData`, `MutableVector2`, `StaticComponent`, `ISystemActions`, `BlobService`, `YallOptions`, `DictionaryService`, `FunctionCall`, `PerfectScrollbarConfigInterface`, `WebhookActionConnector`, `BottomSheetNavigationState`, `pxtc.ApisInfo`, `TransactionAuthFieldContents`, `ISampler`, `PackageDetails`, `BaseEvent`, `ToolbarUsage`, `LayoutBase`, `BaseAtom`, `ex.Input.PointerEvent`, `DocumentExtra`, `MediaTrackConstraints`, `TableColumn`, `TimePrecision`, `TemplatePieces`, `QueryDocumentSnapshot`, `MsgDepositDeployment`, `CentersService`, `IdentityProviderSelectionPage`, `ICellEditorParams`, `DomSource`, `SourceMaps`, `ArgValue`, `ContextInterface`, `TestClient`, `PlayerListPlayer`, `RotationallySymmetricShape`, `StoredConfiguration`, `CmsConfig`, `requests.DeleteWorkRequestRequest`, `ILoggerService`, `MDCTabAdapter`, `HapiServer`, `RenameParams`, `ISvgMapIconConsumerProps`, `IFormProps`, `StateVisNode`, `ReuseContextCloseEvent`, `AnimationFactory`, `MatHint`, `ResManager`, `ParseExpressionTextResults`, `CharCategoryMap`, `ActiveLabel`, `VisualizationsStartDeps`, `GunGraph`, `VariableValue`, `ExpectedDiagnostics`, `GX.DiffuseFunction`, `requests.ListVmClusterUpdatesRequest`, `NamedType`, `gPartial`, `SelectionConstructorArgs`, `AnimationKeyframeHermite`, `ClassDefinition`, `IObjectType`, `TimeZone`, `DeleteFlowCommandInput`, `MapDispatchToPropsFunction`, `Outbound`, `OptionMessage`, `React.ReactNode`, `HsdsCollection`, `android.net.Uri`, `DoStatement`, `NoticeItem`, `DisplayObjectWithCulling`, `CreateFolderCommandInput`, `GeneratedKey`, `WcCustomAction`, `ASTNode`, `usize`, `SelectOptionValue`, `VisOptionsProps`, `HeroSearchService`, `InteractiveProps`, `GtConfigField`, `DescribeValidDBInstanceModificationsCommandInput`, `TextRange`, `ProtractorBrowser`, `ArrayContent`, `E2EPage`, `RendererMock`, `QuestionMatrixDynamicModel`, `DeployProviders`, `btTransform`, `RoomMember`, `RouteTable`, `RuleData`, `d3.HierarchyPointNode`, `FD_Entity`, `ScaleByFactor`, `Profile`, `RadioButton`, `ActionTypeExecutorOptions`, `PlanetApplicationRefFaker`, `IAtDirectiveData`, `NodeStat`, `requests.ListDrgRouteDistributionsRequest`, `SeriesPoint`, `MessageDocument`, `WalkState`, `AssignmentDeclarationKind`, `AccountIdRequestMessage`, `ButtonHTMLProps`, `OrganizationTeamEmployee`, `CharWhere`, `StandardTokenMock`, `PageService`, `AttributifyOptions`, `LoginUser`, `TComAndDir`, `BrowserSession`, `AssignAction`, `LayoutStateModel`, `CommandCreatorResult`, `SMap`, `ActivityInfoModel`, `IKernel`, `SwaggerOptions`, `MissionSetupObjectSpawn`, `StopMeetingTranscriptionCommandInput`, `serviceRequests.GetWorkRequestRequest`, `NumberListRange`, `android.graphics.drawable.BitmapDrawable`, `TSTypeReference`, `TBSelection`, `d.TranspileModuleResults`, `HTMLHeadingElement`, `IncomingHttpResponse`, `BEMData`, `RadioItem`, `FlipperLib`, `ApiReturn`, `PDFObjectStream`, `INewProps`, `EndpointConfiguration`, `BottomNavigation`, `CancellationReason`, `ErrorMessage`, `Leg`, `PayloadType`, `Happening`, `MetaStaticLoader`, `OpenSearchUtilsPlugin`, `NuxtContext`, `GX.IndTexFormat`, `TActions`, `AnalysisCache`, `Helpers`, `ThExpr`, `ConnectFailedListener`, `GettersFor`, `OwnedUpgradeabilityProxyInstance`, `Collectable`, `TextField`, `CreateBundleDTO`, `FontAwesomeIconStandalone`, `FireLoopRef`, `CameraComponent`, `DAL.DEVICE_ID_MULTIBUTTON_ATTACH`, `FontMetricsObject`, `PromiseExecutor`, `LocalForage`, `WebController`, `Coll`, `ContainerInfo`, `HostedZone`, `Entitlement`, `IMetricContext`, `semver.SemVer`, `ClipEdge`, `ListConfigurationRevisionsCommandInput`, `SearchInWorkspaceResultLineNode`, `GetIamPolicyRequest`, `InternalParser`, `SigningWallet`, `ICountry`, `RawVueFileName`, `MenuPositionX`, `ProblemTagEntity`, `ActionMetadataArgs`, `AbstractAssets`, `ServerAccessKey`, `ValueQuery`, `MutableTreeModelNode`, `PatcherServer`, `RollupWatcherEvent`, `HttpPipelineLogLevel`, `DeclarationName`, `ResolveRequest`, `GalleryImageVersion`, `DebugGeometry`, `Keyframe`, `ContractAPI`, `LinearOptions`, `ThemeNeutralColors`, `IImageBuilder`, `AccountV10`, `ListTagsForResourceCommand`, `CLValue`, `PinchGestureEventData`, `UnionBuilder`, `AggregateCommit`, `WalkStats`, `BTI`, `NodeJS.Dict`, `StateChannelsJsonRpcMessage`, `IObserver`, `InteractiveController`, `IContentSearchFilter`, `SVGDefsElement`, `IFluidHandleContext`, `TopAggregateParamEditorProps`, `t_08f7c2ac`, `LoaderFactory`, `RecommendationSummary`, `ListenerFn`, `VNodeElement`, `InnerJoin`, `OptionalResources`, `MessageInstance`, `PaymentMethodCreateParams.BillingDetails`, `PathFn`, `CreateModelCommandInput`, `GoldenLayout.ItemConfig`, `TrackedSet`, `ICaptainDefinition`, `SingletonDeployment`, `JobDatabase`, `WrappedDocument`, `ProbabilitySemiringMapping`, `AzureBlobStorage`, `grpc.Metadata`, `DbSystemEndpoint`, `User1524199022084`, `JSMs.Services`, `BooleanType`, `OutputFile`, `ConverseContext`, `InvoiceItem`, `SelectorGroup`, `DescribeDomainsCommandInput`, `CdkHeaderRowDef`, `PendingRequest`, `ExtensiblePayload`, `FolderData`, `Gamepad`, `Iter`, `StyledComponentClass`, `IChangeRequestManagementItem`, `DirectionsType`, `MethodDeclaration`, `Dialogic.MaybeItem`, `RouterHistory`, `NameValue`, `ScreenInfo`, `CreateProcedureWithInputOutputParser`, `LambdaIntegration`, `LineNode`, `MXDartClass`, `CallReceiverMock`, `IOmnisharpTextEditor`, `SrvRecord`, `InputNode`, `TestView`, `ElectronEvent`, `IAssetState`, `ArcTransactionProposalResult`, `IEventType`, `TracksState`, `APIConfigurationParameters`, `IterableOrArrayLike`, `UploadFile`, `FaunaCollectionOptions`, `FirmwareWriterProgressListener`, `CFDocsDefinitionInfo`, `IThemeRegistration`, `R.Chain`, `ITransaction`, `NSDictionary`, `WorkerResponse`, `StackOutput`, `Exprs`, `Ui`, `Apollo.LazyQueryHookOptions`, `ConditionResolver`, `GetStateReturn`, `BasicJewishDate`, `FetchOptions`, `ISetting`, `DidChangeWatchedFilesParams`, `MaybeFuture`, `ProviderLike`, `PerimeterEdge`, `MessageFormatterOptions`, `Subscriber`, `TestingModule`, `DiagnosticWithLocation`, `RendererEvent`, `ItemPositionCacheEntry`, `SystemVerilogIndexer`, `AuthenticationPolicy`, `ITokens`, `Kwargs`, `ColumnScope`, `MissingTranslationHandlerParams`, `DAOMigrationParams`, `DeletePackageCommandInput`, `LayouterService`, `ast.MacroCallNode`, `LogSummary`, `polymer.Element`, `FormRenderer`, `SampleUtterances`, `UnitRuntimeContext`, `AlertUtils`, `Params$Create`, `EdmxFunction`, `yargs.Argv`, `PrerenderHydrateOptions`, `CommandBuilder`, `TextElement`, `d.TransformCssToEsmOutput`, `ClientRequestFailedEventArgs`, `PaginateOptions`, `Synth`, `angular.IHttpService`, `ProxyPropertyKey`, `OmniOscillator`, `TGetStaticProps`, `MDL0_MaterialEntry`, `PotentialLemma`, `NodeArray`, `CoinTransferMap`, `EmbeddableRendererProps`, `WebpackTestBundle`, `WorkflowDto`, `PublicCryptoKey`, `JCorner`, `SimpleStore`, `RawResponseCallback`, `BastionShareableLinkListRequest`, `IShikiTheme`, `UploadedFile`, `UI5Aggregation`, `SceneActivationCCSet`, `BaseSyntheticEvent`, `OsuBuffer`, `_SelectExplanation`, `TabbableHTMLProps`, `ListSubscriptionsResponse`, `CollisionEndEvent`, `WarframeData`, `UIBrewHelper`, `O.Compulsory`, `NPCActor`, `IDejaGridColumn`, `TextSegment`, `DenomHelper`, `ClockRotate`, `VariableMap`, `GitScmProvider`, `TreeIterator`, `RuntimeShape`, `SavedObjectsExportError`, `Endorser`, `Records`, `SignalOptions`, `DeletePublicAccessBlockCommandInput`, `BgState`, `NgxPermissionsService`, `Atom.Point`, `DecodeError`, `IAddGroupUsersResult`, `TypeData`, `BaseCollider`, `ParsedCssDocument`, `AccountOperation`, `requests.ListOnPremConnectorsRequest`, `CellInterface`, `CanvasItem`, `ISet`, `MessageEmbeddedImage`, `OptionalWNodeFactory`, `CloudService`, `ReadRepository`, `i`, `UpdateHostClassService`, `TestDriver`, `PreviewVer`, `SignatureHelpItem`, `IMergeTreeOp`, `GoToOptions`, `KibanaResponseFactory`, `SimpleRNNCell`, `apid.Rule`, `NgxDropzoneService`, `WsTitleService`, `StorageDriver`, `QuaternionKeyframe`, `Comparable`, `L.LatLngExpression`, `IProfileMetaData`, `Pooling2DLayerArgs`, `GetIntegrationCommandInput`, `OverridePreferenceName`, `RepositionScrollStrategy`, `Timer`, `INotificationOptions`, `ChartsPluginSetup`, `ScenarioResult`, `ShardFailureOpenModalButtonProps`, `ForgotPasswordEntity`, `UiCounterMetricType`, `FramePin`, `ContextContainer`, `KubectlContext`, `React.DependencyList`, `ViewportOptions`, `IMatchOptions`, `CheckboxGroupProps`, `SessionLogoutRequest`, `DeploymentParameters`, `VoiceFocusDeviceOptions`, `PendingMaintenanceAction`, `ThemeServiceStart`, `TimeInfo`, `LintReport`, `SearchParamAsset`, `ServiceError`, `PaperProfile`, `Linkman`, `GaussianNoiseArgs`, `CssSelector`, `Lookup`, `CumsumAttrs`, `ArmObj`, `TUserBaseEntity`, `InternalHttpServiceStart`, `DaemonSet`, `DocumentAccessList`, `HmrStyleUpdate`, `UpdateSource`, `MsgPauseGroup`, `QCNode`, `TBuilder`, `AbiStateUpdate`, `ForInStatement`, `AlfredConfigWithUnresolvedTasks`, `IntervalCollectionIterator`, `firebase.firestore.DocumentReference`, `ResolvedCoreOptions`, `CommandLineToolModel`, `ApexDebugStackFrameInfo`, `RowArray`, `PartialObserver`, `DataPublicPluginEnhancements`, `WExpression`, `CogJob`, `ILoaderPlugin`, `PendingFileType`, `GBDeployer`, `Kernel.IFuture`, `RangeInterface`, `CheerioAPI`, `UpdateSubscriptionsRequest`, `WasmTensor`, `OriginationOp`, `INEO`, `Updater`, `ReLULayerArgs`, `Clef`, `vscode.Task`, `So`, `PrivateEndpointConnectionsDeleteOptionalParams`, `TransmartExportJob`, `JsonDocsStyle`, `TabsService`, `MIRResolvedTypeKey`, `LockerService`, `NAVTableField`, `EventAction`, `ModifyDBClusterEndpointCommandInput`, `admin.app.App`, `DeploymentDocument`, `InsertQuery`, `SharedString`, `DotDotDotToken`, `MyAccountPage`, `Demand`, `Testability`, `ItemBuffer`, `Rx.AjaxRequest`, `YamlCodeActions`, `VAStepWord`, `IVFSMount`, `DeploymentCenterStateManager`, `CodeLensBuffer`, `DeserializedType`, `FocusEventInit`, `i18n.TagPlaceholder`, `Spreadsheet`, `ListCertificatesCommandInput`, `Indicator`, `ts.CustomTransformers`, `RenderErrorHandlerFnType`, `ColorDataObj`, `IGroup`, `FlowNode`, `PageBlock`, `AveragePooling2D`, `ResponsiveMode`, `QuantityFormatter`, `InputStream`, `PipetteOffsetCalibration`, `FunctionCallArgumentCollectionStub`, `requests.ListMountTargetsRequest`, `UserUI`, `TagList`, `V1PersistentVolumeClaim`, `PlasmicContext`, `Seek`, `BaseClientOptions`, `Requestor`, `CreateRulesSchema`, `DeleteRoomResponse`, `CheckboxChangeEvent`, `PhraseFilter`, `LineInfo`, `TableRowProps`, `AuthenticationHelper`, `ResolverBuilder`, `IColumns`, `Processor`, `IPointData`, `QuestionFormatter`, `WebTreeMapNode`, `Redis.ClusterOptions`, `ResponsiveFacade`, `ClassTypeResult`, `HttpEventType`, `ZRImage`, `DomRecorder`, `MnemonicVariationsX86`, `IDynamicGrammarGroup`, `AnimationTriggerMetadata`, `HDKey`, `PDFOperatorArg`, `MerchantOrderGoodsEntity`, `OutcomeShortHand`, `m.Component`, `IncomingStateType`, `AndroidMessagingStyle`, `UsePaginatedQueryData`, `Events.entertrigger`, `LegendProps`, `IZosFilesOptions`, `DeleteApplicationCommand`, `tsc.TypeChecker`, `CredentialRequestOptions`, `CardRenderEffect`, `PluginsService`, `PropSchema`, `SavedObjectsUpdateResponse`, `SidebarLinkProps`, `SingleOrBatchRequest`, `OrderState`, `LedgerState`, `ReactIntl.InjectedIntl`, `SeekOutput`, `SignatureFlags`, `OpenApiSchema`, `ZipFile`, `InsertOneWriteOpResult`, `DeploymentGroupConfig`, `ServiceWorkerState`, `AnimationBase`, `LambdaNode`, `EffectScope`, `ChromiumBrowserContext`, `HitEvent`, `Camera_t`, `ConfigurationItem`, `Vue.CreateElement`, `FsUtil`, `ShouldShow`, `RequiredParserServices`, `DeleteFriendsRequest`, `SearchKey`, `ChangedEvent`, `TabBarProps`, `STDataSourceOptions`, `ObjectInstance`, `ClickOptions`, `KeyedReplacementMap`, `HelperService`, `RepositoriesStatisticsState`, `ConversationTimeline`, `GetStorageSuccessCallbackResult`, `SAPNode`, `AuthKey`, `PhysicsStatistics`, `VirtualMachine`, `IUserRepo`, `SheetObject`, `ToTypeNode.Context`, `Traversable3`, `TraceIdentifier`, `translateMapType`, `UITapGestureRecognizer`, `SwitchLayerAction`, `IEditorAction`, `Kernel.IKernel`, `PhysXPhysicsMaterial`, `DataToExport`, `Publications`, `SendCommandRequest`, `SavedObjectsImportResponse`, `RelativeTime`, `IThriftRequest`, `GXShapeHelperGfx`, `KeymapItemEditableProps`, `BaseItemState`, `ValidEndpointType`, `Clip`, `Stone`, `IErrorState`, `CompoundSelector`, `KeybindingScope`, `RenderCamera`, `KeyBindings`, `JQueryXHR`, `Exponent`, `OptionEditorComponent`, `hardforkOptions`, `NewLineFile`, `Azure.TableBatch`, `TAccount`, `d.ComponentCompilerTypeReferences`, `GenericTreeItem`, `OptionsDevice`, `ParallelPlot`, `UnarynotaddsubContext`, `DropDownOption`, `ImperativeBase`, `HexDocument`, `BFT`, `NullAndEmptyHeadersClientCommandInput`, `FilterList`, `PDFPageLeaf`, `EarlyStopping`, `Timeslot`, `DispatcherLocals`, `XQuery`, `EmbeddableActionStorage`, `ToolbarItemProps`, `Axis3D`, `pb.Callback`, `DAL.DEVICE_ID_SCHEDULER`, `MatcherHintOptions`, `Ledger`, `Space2DSW`, `MTDTexture`, `Voting`, `IRoutes`, `HandlerInboundMessage`, `InstrumentedStorageTokenFetcher`, `ThunkActionT`, `C`, `MzInjectionService`, `JSType`, `DrawType`, `DebtPareto`, `SubmodelImage`, `ExcaliburGraphicsContextWebGL`, `DiagnosticRule`, `DecodedSourceMap`, `HsDialogContainerService`, `OptimizerConfig`, `MdcSnackbar`, `MDL0ModelInstance`, `GetMyProfileCommand`, `S1Node`, `CourseName`, `CreateAssetDTO`, `GetStudioCommandInput`, `MemoryPartition`, `ImportSavedObjectsOptions`, `MediaQueryData`, `VirtualInfo`, `ethers.Signer`, `ApplicationCommandOptionChoice`, `Debe`, `ActionBase`, `DataModels.Correlations.Correlation`, `UpdateActionDef`, `Indy.LedgerRequest`, `OrganizationContactService`, `RouteFactory`, `UpSetSelection`, `CallNode`, `LocaleProviderService`, `_IDb`, `setting`, `ButtonManager`, `CompactProtocol`, `MessageChannel`, `ENUM.AfflictionType`, `SymbolTracker`, `ReaderStateParserLike`, `ReadBuffer`, `NzSafeAny`, `DependencyWheelPoint`, `TargetTypesMap`, `SenderFunction`, `QueryStringInputProps`, `RedspotContext`, `AllInputs`, `requests.ListCostTrackingTagsRequest`, `PluginModel`, `MerchantIdentity`, `ImmutableNotebook`, `IqResponseStanza`, `SpecialPropertyAssignmentKind`, `TriggerType.GITHUB`, `ResetDBParameterGroupCommandInput`, `OverlayProps`, `ImageCache`, `InMemoryDriver`, `ApisInfo`, `BenefitMeasurement`, `requests.ListIamWorkRequestLogsRequest`, `ConnectedComponent`, `GfxMegaStateDescriptor`, `SubmissionEntity`, `IDiagramState`, `RegisterDeprecationsConfig`, `CommandName`, `StartDBClusterCommandInput`, `TextureParameterEnum`, `AdapterUser`, `RedisClient`, `Error_ContextEntry`, `PostRoles`, `OperationVariant`, `GetPolicyCommandInput`, `GridElement`, `HTTPBuffer`, `SdkProvider`, `RGBStrings`, `MeshVertice`, `SalesInvoiceModel`, `requests.ListErrataRequest`, `PlaneAngle`, `apid.ReserveId`, `DeployedCodePackageCollection`, `ServerHost`, `Twitter`, `ExampleDefinition`, `IChannelFactory`, `IntrospectionInputTypeRef`, `Booru`, `FieldFormatsRegistry`, `ExtraComment`, `DescribeComponentCommandInput`, `ImplDeployment`, `BIP32Path`, `order`, `ClientsService`, `IItemScore`, `AnalyticUnit`, `Angulartics2Mixpanel`, `vscode.WorkspaceEdit`, `JellyfishWallet`, `Matrix44`, `DkrTexture`, `Cropping2DLayerArgs`, `IntersectionObserverInit`, `StreamDeckWeb`, `IAssignmentUnitModel`, `TPackageJson`, `Electron.MenuItemConstructorOptions`, `Controller$`, `IpcMessageEvent`, `DayProps`, `IModuleStore`, `CAShapeLayer`, `BlockIndex`, `MeasureFormatter`, `ListWorkRequestLogsRequest`, `TSTNode`, `TradeFetchAnalyzeResult`, `IBabylonFileNode`, `TranslationService`, `LeaveGroupRequest`, `GridAxis`, `TimesheetService`, `ConfigurationTarget`, `IQueuedMessage`, `ActiveComponent`, `com.mapbox.pb.Tile.ILayer`, `OidcRegisteredService`, `GatewayToConceptRequest`, `TickItem`, `ContentManager`, `TTableOperand`, `Animation`, `WebFontMeta`, `CompilerSystemCreateDirectoryOptions`, `SelectionChangeEventArgs`, `Koa.Context`, `PositionWithCaret`, `LuaType`, `BrowseService`, `SendTxBody`, `NavigationContext`, `X`, `IShadingContext`, `DataModels.TokenHistory.TokenHistoryGroup`, `RippleCreateTransactionOptions`, `Appearance`, `KeyList`, `LabelSet`, `KeycloakAdminClient`, `E2EProcessEnv`, `Bond`, `GraphQLFieldConfigArgumentMap`, `EntityValidator`, `BazelWorkspaceInfo`, `SavedDashboardPanel730ToLatest`, `Animated.SharedValue`, `MatButtonToggle`, `IVSCServerManagerEventsHandler`, `ProposalResponse`, `ICfnSubExpression`, `IDataSource`, `ColumnFilters`, `Receiver`, `DefaultRequestSigner`, `DataNode`, `DotnetInsightsGcDocument`, `Vector4_`, `ExpressRoutePort`, `InitiatingWindowProps`, `MatchmakerMatched_MatchmakerUser_StringPropertiesEntry`, `IValidatedEvent`, `IJavaProjectWizardContext`, `Bsp`, `TileData`, `FixedPointX64`, `ReaderTask`, `UsernamePassword`, `ContinuousDomain`, `PIXI.DisplayObject`, `C9`, `TaskStatus`, `ESLSelectItem`, `ThyDropPosition`, `DeviceRegistryService`, `ZWaveErrorCodes`, `t.NodePath`, `CacheInfo`, `ToggleDeselectSeriesAction`, `ChaincodeStub`, `Object`, `Price`, `KintoRequest`, `ListInstancesRequest`, `requests.ListVolumeBackupsRequest`, `DeployStepID`, `ISetActionTypes`, `IItemBase`, `RenameEntityEvent`, `DataTypeDefinition`, `TSTypeElement`, `core.CommonInputFieldConfig`, `PQLS.Analysis`, `SerializedTemplateInfo`, `t.Statement`, `ValueDescriptor`, `InitiateLayerUploadCommandInput`, `TestCursorQuery`, `DeepPartial`, `TrustedSc`, `ObjWrapper`, `FakeData`, `FrameworkInfo`, `LineComment`, `NullLiteralExpr`, `Matrix3x2`, `t.Visitor`, `ISmartContract`, `ConnectionMode`, `SingleProof`, `MatchedContext`, `Calc`, `IdentifyEventType`, `Documentable`, `LayerType`, `SavedQueryAttributes`, `AuditConfig`, `_ISchema`, `tf.io.WeightsManifestConfig`, `ts.TypeLiteralNode`, `vue.ComponentOptions`, `DescribeParameterGroupsCommandInput`, `ApplicationRef`, `requests.ListDataGuardAssociationsRequest`, `TSConfig`, `PhotoService`, `JsonPatchOperationsState`, `FSWatcher`, `TLPointerInfo`, `PackageTarget`, `IFieldsAndMethods`, `AnimationFrame`, `BuildVideoGetQueryOptions`, `TokenBalance`, `ProductVariantSettingService`, `BreadcrumbsListProps`, `BigQueryRetrievalResult`, `CommentTag`, `AggregateRewriteData`, `CachedQuery`, `trm.ToolRunner`, `StickerOptions`, `RelationshipType`, `TAccumulate`, `GetGroupCommandInput`, `ReactiveInteraction`, `CurrencySymbolWidthType`, `IServiceManager`, `Flair`, `RnM2Accessor`, `RemoteEvent`, `PixelImage`, `MetricState`, `DataChannel`, `IOdspTokenManagerCacheKey`, `TablePaginationConfig`, `Bunjil`, `EaseItem`, `EncryptedDataKey`, `SolutionSet`, `K.FlowTypeKind`, `CssPropertyOptions`, `app.LoggerService`, `FixedPointNumber`, `Docker`, `EbsMetricChange`, `InstallStatus`, `TransactionType`, `Model.Option`, `LineSegment3d`, `KeyPairTronPaymentsConfig`, `IndexSpecification`, `EdgeMaterialParameters`, `FloatSym`, `DraftBlockType`, `CreateAlbumeDto`, `SerializedRenderResult`, `StreamReturn`, `argparse.ArgumentParser`, `ListrRendererValue`, `QueryGraph`, `WorldBoundingBox`, `TradeStrategy`, `IDiffObject`, `SelectEffect`, `EmbeddableOptions`, `AveragePooling3D`, `OrganizationService`, `ContentMatcher`, `CellOptionType`, `AppHookService`, `AnyArenaNode`, `SIDE`, `EngineArgs.EvaluateDataLossInput`, `LexerActionExecutor`, `FlexParentProps`, `LeftHandSideExpression`, `Capture`, `MDCSwitchAdapter`, `requests.ListApmDomainsRequest`, `ASSymbol`, `WCLFight`, `MutationTree`, `MDCCheckboxAdapter`, `DeleteTableCommandInput`, `CreateOneInputType`, `DebugProtocol.ContinueResponse`, `PostProcessor`, `TAbstractControl`, `BasicSeriesSpec`, `Usage`, `WithSubGeneric`, `BehaviorHook`, `MappedCode`, `OnLoadArgs`, `AzureAccount`, `IObjectHash`, `ProofCommandResponse`, `StackGroup`, `FormPayload`, `ColumnSetting`, `Prioritized`, `IMessageItem`, `FiltersState`, `SyncExpectationResult`, `InitMessage`, `HttpsCallableResult`, `Double`, `UserLecture`, `TradeSearchRequest`, `MockedResponse`, `DefItem`, `jdspec.ServiceSpec`, `ControlPanelConfig`, `StateInfo`, `RTCDataChannel`, `TStore`, `HairProps`, `TransformFactory`, `COURSE_TYPE`, `G`, `IHookStateSetAction`, `IZoweTreeNode`, `Candidate`, `ICommandArgs`, `TagResourceCommandOutput`, `DynamicColorProperty`, `GeniePlugin`, `ParsedBlock`, `GithubIssueItem`, `BlockNumberState`, `BenefitService`, `StaticConnectionType`, `BinaryTreeNode`, `AskQuestionsParams`, `UnionOfConvexClipPlaneSets`, `FileSystemStats`, `IterationDirection`, `ErrorInfo`, `ISectionProps`, `DecryptResultPmcrypto`, `TupleType`, `ChannelSummary`, `StoryFile`, `IVarSize`, `InstanceStatus`, `BasicCCSet`, `RepositoryIssue`, `IAuthResponse`, `ESTestIndexTool`, `GenericLogger`, `SystemFixture`, `OrganizationsService`, `IExtent`, `Importance`, `DebugProtocol.ScopesArguments`, `DiagramEngine`, `IPathResultItem`, `Base58CheckResult`, `BINModelSectorData`, `ClassBuffer`, `Showtime`, `Carrier`, `DraftDecoratorType`, `IListItemAttrs`, `GeoLatLng`, `RequestTracingConfig`, `IdentifierInput`, `ForeignAttributeSelector`, `BasicUnit`, `WebContext`, `IChallengeProps`, `CommentGraphicsItem`, `SignatureHelpResults`, `MdDialogRef`, `InfoWindow`, `AddressInformation`, `ReminderFormatConfig`, `handlerFunc`, `ResourceTimelineGridWrapper`, `RtpTrack`, `FixResult`, `PCode`, `TimeRequestOptionsSourcesTargets`, `SimpleAttribute`, `ICreateVsamOptions`, `ReportService`, `GfxDevice`, `SideBarItem`, `BlockingResponse`, `FileSource`, `TwComponent`, `UsageCounter`, `OverlayPortal`, `cdk.CustomResource`, `VirtualMachineRunCommand`, `META`, `MarkerSnap`, `TransactionOverrides`, `Toplevel`, `MaybeElementRef`, `IPythonVenvWizardContext`, `AuthenticationConfiguration`, `RegionTagLocation`, `EntityAction`, `ChildRule`, `CertificateSubjectAlternativeName`, `CanvasTextBaseline`, `MockSegmentStore`, `TypeMoq.IMock`, `CredentialStore`, `MenuContextProps`, `WorkflowType`, `HTMLDivElement`, `NodeTree`, `SuspenseContextType`, `RoutesManifest`, `QR`, `CoinPretty`, `HashedFolderAndFileType`, `AnyType`, `LoginSuccessPayload`, `ModifyPoint`, `FauxClassGenerator`, `ParsedTemplate`, `Transforms`, `Enum`, `ListIntegrationInstancesRequest`, `P7`, `LanguageType`, `SortingService`, `Jest26CacheKeyOptions`, `ResponsiveInfo`, `InstallTypingHost`, `ThemeReducer`, `ZoneDefinitionModel`, `MessageReaction`, `PathData`, `TrueSkill`, `APIPost`, `CheckFn`, `requests.ListReplicationPoliciesRequest`, `BrowserFiles`, `I18N`, `HexMesh`, `ISearchResult`, `ConfigurationModel`, `IAllBondData`, `CumSumProgram`, `requests.ListBootVolumeReplicasRequest`, `IGetToken`, `DOMEventName`, `RecordProxy`, `CliArgs`, `HighlightService`, `CoreEnvironment`, `BScroll`, `Uint32List`, `DecimalFormatOptions`, `ModalWrapperProps`, `UserForm`, `ActivationFunction`, `StructuredAssignment`, `ContactMock`, `ChartErrorEvent`, `KnownAction`, `ServerConfig`, `MediaModel`, `ReactTestRendererTree`, `RangeResult`, `PositionOffset`, `ICategoricalFilter`, `AuthzService`, `ResponseGenerator`, `ResourceUnavailableException`, `DaffCategoryFilterToggleRequest`, `SecurityHealth`, `AxisOptions`, `StateT`, `ContextMenuInteraction`, `ListResourceTypesRequest`, `HsShareUrlService`, `Err`, `SinonMatcher`, `ICfnBinding`, `Types.GenerateOptions`, `PLAYER`, `GameplayClock`, `IHealthStateChunk`, `JointTreeNode`, `ShortcutID`, `TQuestionFull`, `Node.MethodParams`, `ErrorContext`, `QuirrelClient`, `AssignNode`, `Color.RGBA`, `Dexie.Table`, `NVM3Object`, `ReserveInstance`, `TrimmerTheme`, `I`, `IRoute`, `ProductContentPipe`, `CandidateStore`, `RemoteHotspot`, `TableServiceClient`, `LogAnalyticsParserField`, `JsxElement`, `ProxyOptions`, `AnonymousType`, `requests.ListCloudExadataInfrastructuresRequest`, `RenderTreeDiff`, `TensorArray`, `TypeTable`, `ActionRuntimeContext`, `CardScript`, `UpdateUserDto`, `TestSetupBuilder`, `GetRouteCommandInput`, `SdkPingPongFrame`, `TableAccessFullStep`, `StopExecution`, `AssetItem`, `DependencyIdentifier`, `SyncTable`, `DOMMatrix`, `PositionObjOrNot`, `IRecordedApiModel`, `Eula`, `PopoverController`, `ChromeApi`, `FileReflection`, `TimelineStep`, `OptionsState`, `WorkspaceFolderConfig`, `BotFrameworkAdapter`, `Intl.DateTimeFormatOptions`, `CalendarDay`, `EnvironmentInfo`, `RecoilValueReadOnly`, `ToComponent`, `GeneratorPaths`, `BoneAnimator`, `XTreeNode`, `ContextService`, `SCN0`, `NestedStagePanelsManager`, `BooleanInput`, `RequestWithUser`, `AnimatedSettings`, `S5PL2Layer`, `SavedObjectLoader`, `Storable`, `SimpleManipulator`, `ViewRef`, `Space`, `Kinds`, `SerialFormat`, `NodeEncryptionMaterial`, `MergeOptions`, `IDataSet`, `FontCatalogConfig`, `PagesService`, `RecordingSegment`, `CameraRigControls`, `vscode.DiagnosticSeverity`, `ConvertState`, `GetDomainRecordsResponse`, `WeatherService`, `IFontManager`, `JasmineTestEnv`, `TextDocumentSettings`, `BigNumber.BigNumber`, `MatchExp`, `ShapeBase`, `ListSourcesRequest`, `WebAppConfigStack`, `AssetBalance`, `ICommandBarProps`, `NormalizedCacheObject`, `SortingOrder`, `TreemapSeries.NodeObject`, `DevServer`, `TargetDatabaseTypes`, `TextureCubeFace`, `PatternStringProperty`, `PasswordGenerationService`, `CameraStrategy`, `Pow`, `BoundCurves`, `Prompt`, `Selective`, `PickerDelegate`, `ChartDef`, `ScullyContentService`, `DependencyPair`, `Function`, `Shift.Expression`, `IOpenSearchDashboardsSearchResponse`, `DescribeFleetsCommandInput`, `ActionProcessor`, `NumberValue`, `LineGraphicsOptions`, `WebSocket.MessageEvent`, `NextHandler`, `IAdapter`, `ReactiveChartStateProps`, `StrictValidator`, `ValidatePurchaseAppleRequest`, `DeleteDatasetCommandInput`, `ChipCollection`, `UnixTimestamp`, `PSTTableItem`, `VerdaccioConfig`, `ExecutionItem`, `OpenApiPersistedSchema`, `ts.PrefixUnaryExpression`, `RequiredValidator`, `Purchase`, `CompiledQuery`, `BaseRouteName`, `IDefinition`, `AlainSFConfig`, `PublisherSummary`, `ChartData`, `IStopwatch`, `SRT0_TexData`, `instance`, `MockProxy`, `PositionData`, `OnPostAuthResult`, `LogoActionTypes`, `PackageDependency`, `Publisher`, `PlatformNode`, `ParseSpan`, `ByteArray`, `AsyncBarrier`, `MmpService`, `_`, `Aes128Key`, `LogStructuredData`, `DataPointPosition`, `StaticMeshAsset`, `JsonRpcResult`, `IInterceptorOptions`, `_1.Operator.fλ`, `ReadOnlyAtom`, `ScreenDimension`, `IHandlerParameters`, `SignedStateVarsWithHash`, `model.Model`, `TPositionPair`, `Flatten`, `ReportingConfig`, `AudioOutputFormatImpl`, `ComponentSymbolTable`, `LeaguePriceSource`, `CircularAxisData`, `SupportedBodyLanguage`, `EntityConfig`, `PythonShell`, `CirclinePredicate`, `FilterRequest`, `UploadData`, `AlphaDropoutArgs`, `LoginToken`, `DocumentCollection`, `PreprocessorSync`, `IExchangeInfo`, `MakiObject`, `BackendValues`, `DAL.KEY_TAB`, `SlideProps`, `i.Node`, `OnProgressCallbackFunction`, `StringValidator`, `ITokenResponse`, `HashMap`, `IGBInstance`, `EidasRequest`, `CommentModel`, `PackInfo`, `HeaderProps`, `GlobalAveragePooling1D`, `IPhysicsMaterial`, `OverlappingPathAnalyzer`, `RelaxedPolylinePoint`, `ComplexSelector`, `TxHelper`, `CoreURI`, `VMLDOMElement`, `requests.ListJobShapesRequest`, `StacksKeys`, `PopperProps`, `ActiveModifiers`, `StateDto`, `SimpleStatementContext`, `UndoManager`, `OptionalEntry`, `TypeDisplayOptions`, `OpcuaForm`, `SFCDiffWatcher`, `ManagedListType`, `StorageEngine`, `FormDialogService`, `ParticipantItemStrings`, `V1WorkflowStepInputModel`, `MessageLogger`, `BodyComplexClient`, `ReferencesNode`, `EC_Public_JsonWebKey`, `messages.Ci`, `DnsRecord`, `BadgeButtonWidget`, `ListChannelsResponse`, `CombatStats`, `ServiceProviderAdapterMongoService`, `ScaleGamma`, `TimeIntervalTriggeringPolicyConfig`, `DefaultPass`, `IColorValueMap`, `IceState`, `IValidationSchema`, `MgtFlyout`, `IBasePickerSuggestionsProps`, `BN.Value`, `ReportStoreService`, `NavLocation`, `Highcharts.ClusterAndNoiseObject`, `ServerEntry`, `CreateTagsRequest`, `megalogDoc`, `anyNode`, `StateNamespace`, `AccessLevel`, `anchor.Wallet`, `NzConfigService`, `markdownit`, `BaseException`, `LangiumSharedServices`, `Emission`, `AccessTokenData`, `IAggregateConfiguration`, `HttpFetchOptions`, `SerializedSourceAnalysis`, `ListDatasetsCommandInput`, `ProxyGroup`, `LabelEncoder`, `PlotlyLib`, `PayloadTooLargeError`, `SpecQueryModelGroup`, `XColorsTheme`, `ATN`, `StructureCollection`, `SVGProps`, `MessageImages`, `core.ETHVerifyMessage`, `AtomicAssetsNamespace`, `StackStatus`, `TypeOptions`, `IInviteGroupUsersResult`, `AllureStep`, `CertificateProfileType`, `MockTemplateElement`, `PluginRevertActionPayload`, `android.view.ViewGroup`, `Topic`, `TabWatcher`, `SemicolonClassElement`, `NgbDate`, `AllSeries`, `ServerService`, `FileElement`, `DaffCartCoupon`, `SubTrie`, `CreateOrganizationCommandInput`, `LayoutProps`, `PickerInput`, `UIViewControllerTransitionCoordinator`, `ClassNameMap`, `NodeGraphicsItem`, `ConnectionProvider`, `ComponentChild`, `NativePlatformResponse`, `NgGridItemEvent`, `EdmxProperty`, `ActionReducerMapBuilder`, `VisitFn`, `NSFileManager`, `DebugVariable`, `UpdateContent`, `A4`, `CollectorFilter`, `ChildBid`, `PathNodeData`, `WhitelistInstance`, `IHttpGetResult`, `InsertWriteOpResult`, `DataMaskCategory`, `IEditorController`, `PatternCaptureNode`, `WorkspaceHeader`, `DataClient`, `IKsyTypes`, `TaskConfigurationModel`, `ProcessRequirementModel`, `HappeningsValidationOutcome`, `ObservableArrayProxy`, `BuildRequestOptions`, `GlobalEventModel`, `StorageLocation`, `IFB3Block`, `AppearanceService`, `AvailabilitySlot`, `TsSelectionListComponent`, `XActionContext`, `RuntimeConfig`, `TsLinter`, `StreamModule`, `StateInline`, `GridRenderCellParams`, `Round`, `requests.ListJobsRequest`, `Play`, `ReturnTypeInferenceContext`, `GraphQLConnectionDefinitions`, `FactoryFn`, `ServiceRequest`, `Func`, `IQueryCondition`, `DeleteScheduleCommandInput`, `PrefixLogger`, `hubCommon.IRevertableTaskResult`, `StackCardInterpolatedStyle`, `Nameable`, `ServiceRoom`, `CSSObjectWithLabel`, `AppExecution`, `IStop`, `FileRelativeUrl`, `ModelFactory`, `SafeUrl`, `FieldTransformConfig`, `ElementX`, `TickLabelBounds`, `ColumnPreset`, `IDockerImage`, `SerializableResponse`, `Asserts`, `EventRecord`, `XData`, `ExtraPost`, `SMTLet`, `IProgressReporter`, `DateTableContext`, `ComponentCompilerLegacyConnect`, `ListPipelineExecutionsCommandInput`, `Cascade`, `IRoom`, `ProxyAgent`, `ServiceIdRequestDetails`, `Allocation`, `SqlTuningTaskSqlDetail`, `CRUDEngine`, `DocumentGeneratorItem`, `AngularPackageLoggerMessage`, `LoggingMetaData`, `IrisIcon`, `CreatePackageCommandInput`, `MockedLogger`, `ExtraOptions`, `LambdaService`, `IDragCursorInfos`, `CandidatePair`, `RoomPosition`, `LogicNode`, `WorkspaceRepo`, `TransactionExplanation`, `ICardProps`, `VersionData`, `ISavedVis`, `TestCaseSetup`, `TurtleBuilder`, `ProsemirrorAttributes`, `JLCComp_t`, `DejaColorFab`, `ClassSession`, `SyntheticPerformanceMetrics`, `DocumentRecord`, `HeadersInit`, `PointEditOptions`, `SharedService`, `Listable`, `ExportKind`, `ExportsAnalyzerResult`, `ResponderModel`, `TempoEvent`, `CreatorBase`, `RxnArrow`, `Multiply`, `MockSetup`, `FormatFunc`, `ThyTooltipConfig`, `ArmResourceDescriptor`, `GoodGhostingInfo`, `NetworkAddress`, `ReportingAPIClient`, `NodeInterface`, `PermissionType`, `CommentReply`, `AppLeaveHandler`, `GroupedPriorityList`, `Amplitude`, `vscode.DocumentSymbol`, `RowValidatorCallback`, `NgWalkerConfig`, `DkrObject`, `ConnectionErrorCode`, `SpeechTranslationConfigImpl`, `WebSiteManagementModels.AppServicePlan`, `TimeChangeEvent`, `ListrTaskWrapper`, `requests.ListDbSystemPatchesRequest`, `EmitTextWriter`, `EditableRow`, `DocumentViewResponse`, `HttpAdapter`, `apid.ThumbnailId`, `ShipData`, `BoxSliderOptions`, `TabType`, `MetadataInfo`, `Highcharts.QuadTreeNode`, `ElasticLoadBalancingV2MetricChange`, `NgModuleRef`, `AggsCommonStart`, `UntypedBspSet`, `PhysicalQueryPlanNode`, `AddUserCommand`, `FunctionConfig`, `Transition`, `ReduxCompatibleReducer`, `FieldDefinitionNode`, `AESEncryptionParams`, `TombFinance`, `Html5QrcodeSupportedFormats`, `SdkIndexFrame`, `e`, `OrchestrationVariable`, `HTMLIonMenuElement`, `CreateDeploymentResponse`, `BaseApi`, `FreezeObject`, `AliasDeclaration`, `CreateAppCommandInput`, `RoleHTMLProps`, `PortRecordType`, `EnrichedDeprecationInfo`, `TestObject`, `CommonNode`, `MDCButton`, `Tremolo`, `AtomicMarketContext`, `Id64Set`, `OidcCtx`, `VariableUse`, `IModel`, `DiagnosticCategory`, `DescribeChannelModeratedByAppInstanceUserCommandInput`, `EventFacade`, `CounterProps`, `SymbolFlags`, `PartialSequenceLength`, `AdvancedSettings`, `GitlabUser`, `UIToast`, `DebtTransaction`, `DateRangeBucketAggDependencies`, `DirectChannel`, `DensityBuilder`, `E2EPageInternal`, `TraceNode`, `StoreModule`, `PublicationDocument`, `ColumnRefContext`, `AdEventListener`, `BeanWrapper`, `NextFunction`, `JWTVerifyResult`, `ITrackItem`, `MatcherState`, `SlashParams`, `ContentItem`, `TInterval`, `GnosisExecTx`, `SolidLineMaterial`, `Inode`, `IdTokenResult`, `IArtifact`, `TriggerApexTests`, `ResDicEntry`, `CtrFail`, `ApexExecutionOverlayAction`, `SearchQueryProps`, `VisualizeEditorVisInstance`, `SurveyPropertyEditorBase`, `alt.Vector3`, `YamlParser`, `CodeActionContext`, `ObjectProvider`, `DBContext`, `ValueService`, `EventManager`, `RequesterType`, `PanelHeaderProps`, `G6Node`, `LemonTableColumn`, `SwaggerJson`, `CoapMethodName`, `ChartwerkTimeSerie`, `WaitingThreadInfo`, `BezierCoffs`, `NotExpression`, `vscode.CodeAction`, `AdjacencyGraph`, `Ability`, `SchemaRefContext`, `MapboxGeoJSONFeature`, `FixtureLoader`, `Tokenizer`, `RouterReq`, `AudioDescription`, `UpdateDashboardCommandInput`, `WebDriver`, `ItemService`, `INotificationTemplate`, `CurrencyFormatOptions`, `VersionedTextDocumentIdentifier`, `AzHttpClient`, `PlacementContext`, `Hash256String`, `It`, `RestManager`, `ExpressionValueSearchContext`, `IHeader`, `CreateAccountParams`, `ListChangeSetsCommandInput`, `DtlsRandom`, `BackupPolicy`, `CkbBurn`, `PageNode`, `TabComponentProps`, `Course`, `TreeNodeLocation`, `IExternalStorageManager`, `Adapter`, `DeleteResourcePolicyRequest`, `DetectorBuilder`, `zowe.IDownloadOptions`, `alt.IVector3`, `MapOf`, `LifecycleSettings`, `QuerySet`, `BaseListParams`, `ImageResult`, `EntityLike`, `PagerCell`, `SlpRefType`, `StaticRegion`, `SchemaAttributeType`, `FeatureUrl`, `Labor`, `Sponsor`, `DeleteProjectRequest`, `HyperlinkProps`, `UpdateStudioCommandInput`, `LegacyDrawing.Sprite`, `Stitches.ScaleValue`, `ComponentBed`, `OpCode`, `PreviewDataApp`, `ODataActionResource`, `InventoryFilter`, `MatchSpecific`, `IHttpFetchError`, `CompositePropertyDataFilterer`, `Shift.Node`, `ReviewerStatisticsState`, `d.FsReadOptions`, `requests.ListAlarmsRequest`, `DMMF.ModelAction`, `EditOptions`, `requests.ListVirtualCircuitsRequest`, `Spread`, `CreateProfileDto`, `ListAutoScalingConfigurationsRequest`, `IControllerAttribute`, `CreateDatasetCommandOutput`, `BitcoinjsNetwork`, `InputListProps`, `Elevation`, `ListCertificatesResponse`, `ModalComponent`, `BinaryNode`, `UseQueryReturn`, `TileMatrixSet`, `XRInputSource`, `MultiCommandCCCommandEncapsulation`, `ConnectionContracts.ConnectParams`, `AugmentedAssignmentNode`, `IClassify`, `InMemorySpanExporter`, `PostRequest`, `ListObjectsV2CommandInput`, `DataClassBehaviors`, `Lang`, `QueueItem`, `VcsRepository`, `EnhancedEmbeddableContext`, `NotificationData`, `XPCOM.nsIDOMWindow`, `ThunkAction`, `EditorStore`, `OptimizeCssInput`, `ProviderInfo`, `TableCell`, `FnArg`, `PageContent`, `Serializable.GraphSnapshot`, `ListDatasetsCommandOutput`, `WatcherFolderMap`, `TJSONObject`, `ProofreadRuleMatch`, `FunctionAppStack`, `OpIterator`, `d.PrintLine`, `OAuthRequest`, `ProductCategoryService`, `Trash`, `InternalContext`, `ICircuitGroup`, `ProjectDataManager`, `MaterialEntry`, `NamedImportsOrExports`, `OnExistingFileConflict`, `Test.TestLogType`, `GfxrPass`, `ApolloError`, `SvelteComponent`, `TaskBase`, `MoveTree`, `ethers.providers.Provider`, `DaffCategoryReducerState`, `Datepicker`, `SpatialStandupRoom`, `ComponentAst`, `Serverless`, `SM`, `DownloadTask`, `DetailedPeerCertificate`, `DevToolsExtensionContext`, `LowLevelResponse`, `ProofAttributeInfo`, `KeyResult`, `ComponentsState`, `UserDataPropertyAPI`, `QueueMap`, `UInt16`, `OsmConnection`, `HookResult`, `ThermostatFanModeCCReport`, `PlatformTypes`, `DeployedServicePackage`, `JobQueue`, `ActionTypes`, `XcodeProject`, `WebsocketData`, `CalibrationResponseAction`, `VisualizeEmbeddableFactoryDeps`, `Generate`, `EditDoc`, `ShapeConfig`, `Chance`, `TinyPg`, `ScannedBehavior`, `TweetEditorState`, `Blockchain`, `MappedTypeDescription`, `WatchDecorator`, `GuaribasUser`, `BroadcastService`, `DeploymentEnvironment`, `InstructionData`, `IMutableQuaternion`, `StatusUpdate`, `DiscordooError`, `ParticipantContents`, `JDesign`, `SymlinkCache`, `EthereumPaymentsUtilsConfig`, `OperationParameter`, `core.IRawOperationMessage`, `NextServer`, `IRenderer`, `GalleryProps`, `BooleanCV`, `GlobalCoordinates`, `Verifier`, `IBaseImageryMapConstructor`, `CollectionData`, `HsAddDataService`, `SavedObjectsBulkUpdateObject`, `MediaStreamConstraints`, `DatePipe`, `TIn`, `NavigationContainerRefWithCurrent`, `IntersectionTypeNode`, `ViewNode`, `Stripe`, `IWriteAbleSetCombination`, `BlockCache`, `OptionsStruct`, `MyCompanyRowConfig`, `ComparisonResult`, `AbstractRegisteredService`, `moneyMarket.oracle.PricesResponse`, `HTMLIonItemElement`, `IMutableCategorizedPropertyItem`, `Folded`, `NamespaceImport`, `DefaultContext`, `Cypress.PluginConfigOptions`, `SolutionBuilderHost`, `InputTimeRange`, `CancelExportTaskCommandInput`, `DialogDelegate`, `PlayerOptions`, `ParseTree`, `IProcFSEntry`, `Coverage`, `WorkingDirectoryStatus`, `InferredProject`, `StoneTypeArray`, `WorkItemTypeField`, `FsFiles`, `GroupName`, `GfxWrapMode`, `ObjectLiteralElement`, `IElement`, `TiledMap`, `ObjectTracker`, `common.RegionProvider`, `LoggableTarget`, `DriveFile`, `requests.ListDedicatedVmHostShapesRequest`, `HostInstanceMap`, `ProxyIntegrationTester`, `GetEndpointCommandInput`, `ReindexActions`, `CollectionMetadata`, `SyntaxTree`, `DocInstance`, `LineUpJSType`, `ListDataViewsCommandInput`, `TabsListProps`, `IPromiseRetry`, `CollectionEvent`, `CellTile`, `SampleAt`, `IEmployeeJobsStatisticsResponse`, `WalletConnect`, `FnN3`, `API`, `INodeTypeDescription`, `TranslateAnswerConfig`, `VisiterOption`, `TxEventContext`, `TestAnalyzer`, `IBeacon`, `ProjectUser`, `BuildHelpers`, `ManualServerConfig`, `IStartTsoParms`, `DNSPacket`, `GatewayShardsInfo`, `ResourcePermission`, `BasePlacement`, `ReconnectionOptions`, `FieldConfigData`, `ExploreStateModel`, `Services.Plugins`, `KV`, `SourceMapSource`, `Canonizer`, `TEntity`, `NmberArray16`, `StoreMap`, `JSON5Config`, `DAL.KEY_6`, `ColorScaleInfo`, `Command.Command`, `MediaFormat`, `SVGAttributes3D`, `ArrayDiff`, `PostData`, `TProductFilter`, `MultilevelSwitchCCStartLevelChange`, `SimpleFunction`, `AbbreviationAttribute`, `CreateServiceRequest`, `IntervalJobOptions`, `CSVOutput`, `WithMetadata`, `CipherContext`, `TokenLocation`, `EphemeralTaskLifecycle`, `CallContext`, `MonoRepo`, `StackDataValues`, `PiEditProjectionItem`, `TokenList`, `ClassInfo`, `QueueStorageContext`, `TestingAggregate`, `MetaLogger`, `ANGLE_instanced_arrays`, `RadixParticle`, `BaseProtocolLabware`, `PackageConfig`, `LightGallery`, `ImageType.StyleAttributes`, `OrderTemplatesOverviewPage`, `Radian`, `IAnswer`, `ValueTypes`, `EntityConfiguration`, `TemplateService`, `DeleteAccountsRequestMessage`, `Effects.SpriteEffect`, `VirtualDocument`, `FsFile`, `SVGNodeAttribute`, `DereferencedSchema`, `NonRelativeModuleNameResolutionCache`, `StreakItem`, `ViberTypes.MessageOptions`, `Water`, `ASTVisit`, `JobLifecycleState`, `Types.KafkaConsumerMessageInterface`, `SupCore.Data.EntryNode`, `ts.StringLiteral`, `AT`, `NgOpenApiGen`, `GlobalService`, `LookupResult`, `TransitionCheckState`, `ImportNamespace.Interface2`, `UndoState`, `SignalData`, `IconSvg`, `CardName`, `ListSchemasCommandInput`, `apid.DropLogFileId`, `StatusCodeCallback`, `ListComprehensionIterNode`, `Registrar`, `ObjectNodeParams`, `PatternClassNode`, `JobSummary`, `doctrine.Type`, `requests.ListNetworkSecurityGroupsRequest`, `ModelManager`, `AriaProps`, `IPluginSettings`, `immutable.Map`, `IVirtualDeviceValidatorResult`, `KintoResponse`, `PatternMatch`, `AttrValue`, `IAtom`, `DataSourceConfig`, `PoseNetOutputStride`, `ExtendedError`, `CountBadgeProps`, `ImportKeyPairCommandInput`, `Rate`, `GeoUnitsForLevel`, `ALSyntaxWriter`, `Joint`, `HostRuleHeader`, `ChaincodeResponse`, `IMinimatch`, `NonPayableTx`, `MutableGeoUnitCollection`, `Questions`, `OpenSearchResponse`, `FirstValue`, `AssembledObject`, `DefinitionLocation`, `Conv2D`, `IOrganizationSet`, `Type.TPowerQueryType`, `CardInGame`, `drawerModule.RadSideDrawer`, `ContentPage`, `ThirdPartyCapDescriptor`, `Event_2`, `SimpleTypeMemberNamed`, `SignatureHash`, `SavedObjectWithMetadata`, `ParsedStringPattern`, `SuggestChangeHandler`, `APIError`, `SortKeyParams`, `ButtonStyleProps`, `PaymentV2`, `EmailOptions`, `TypePackage`, `GaxiosError`, `IntelChannel`, `ManagementAgentPluginGroupBy`, `DangerDSLType`, `android.graphics.Bitmap`, `requests.ListDbSystemPatchHistoryEntriesRequest`, `NavLinkWrapper`, `Terminal`, `scriptfiles.ASModule`, `LoadingLastEvent`, `UpdateModelCommandInput`, `QuantumElement`, `PositionSide`, `TransformSchemaOptions`, `DateService`, `SlashCommandContext`, `StreamClient`, `GlobalToModuleMapping`, `CSharpProperty`, `NetworkVirtualAppliance`, `IUserFilterDefinition`, `TweenFunc`, `ListContentsCommandInput`, `PackageJsonDependency`, `BitBucketCloudAPI`, `SelectPopoverOption`, `SpyObj`, `ListChildComponentProps`, `LetterStyle`, `RGBColorType`, `AnyXModule`, `Wnd`, `JIntersection`, `FactoryUDFunction`, `WrappedLiteralValue`, `FileLock`, `DebouncedState`, `EnumType`, `ExecutionDriver`, `SrcDecoder`, `TableDistinctValue`, `KeywordDefinition`, `LookupInResult`, `Survey`, `ValidatedBatchConfig`, `ISceneLoaderAsyncResult`, `StackProperties`, `Types.EditableTitleState`, `HLTVPage`, `HistoryItem`, `AirPacker`, `HighlightItem`, `SIZE`, `EmbeddableFactory`, `DeleteFn`, `GfxBindingLayoutSamplerDescriptor`, `PSTFile`, `VisualizationsSetup`, `IProgress`, `DetailedOrganizationalUnit`, `PropFunctionSignature`, `vscode.CodeActionContext`, `ProposalData`, `Messages`, `BotCursorType`, `AudioTrack`, `Pump`, `pxtc.SymbolInfo`, `LinuxParameters`, `ITableSchema`, `DictMap`, `ComponentTemplateListItem`, `PluginHostProps`, `HammerInput`, `WatchCallback`, `AvatarProps`, `ZoomTransform`, `ICalculatePagingOutputs`, `Github`, `Secret`, `RNNLayerArgs`, `LocalProps`, `NumberLiteralExpr`, `GenericRequestHandler`, `AppResult`, `TasksActionTypes`, `ResponderExecutionStates`, `CustomResource`, `DocItem`, `Item`, `Object3D`, `RxSocketioSubjectConfig`, `UIHelper`, `EditTransformFlyoutState`, `ThyClickPositioner`, `PluginRemoteLoadZipOptions`, `HostItem`, `tr.actions.Args`, `IStackTokens`, `PreciseNumber`, `ParseLocation`, `ListCore`, `ValueGetterParams`, `ThyListOptionComponent`, `MapEnv`, `ParamSchema`, `BinaryBody`, `DescribeMaintenanceWindowExecutionTasksCommandInput`, `Stringer`, `CandidatesService`, `CommitSequence`, `Ora`, `CustomPluginOptions`, `ImportedModuleDescriptor`, `TGen`, `IRequestQueryParams`, `BatchChain`, `IRendererOptions`, `GitHubItemSubjectType`, `ITemplateItem`, `AlertSummary`, `ForwardingState`, `KeysState`, `RealTestServer`, `TextWrapper`, `interop.Reference`, `ScreenCollisions`, `DAO`, `GetPointFieldFn`, `requests.ListSubnetsRequest`, `IStreamInfo`, `GoogleFont`, `Animated.Adaptable`, `ResourceDoc`, `TrackedPromise`, `StoryGetter`, `CentralTemplateProvider`, `NativePointer`, `CompiledPath`, `IMdcTextFieldElement`, `EmitResolver`, `AsyncCache`, `OrganizationAccountConfig`, `VertexAttributeEnum`, `ThyAutocompleteConfig`, `NodesVersionCompatibility`, `ExplorationInfoParameter`, `MindMapModel`, `SummaryPart`, `BarGroupValue`, `GitRepository`, `PropertyGroup`, `DataRequest`, `CustomRender`, `GetDocumentCommandInput`, `IMatrixEvent`, `ParsedCronItem`, `PartialList`, `ToolsSymbolInformationRequest`, `Exception_Type`, `IGetTasksStatistics`, `CmsModelFieldValidation`, `NgForm`, `LocationFeature`, `CodeMirror.EditorConfiguration`, `StrategyOptions`, `UncommittedChangesStrategy`, `AbstractModelApplication`, `WebSocket.Server`, `TableModel`, `DerivationPath`, `BuildSupport`, `S3.PutObjectRequest`, `ListResolverEndpointsRequest`, `CsvParserStream`, `MappedDataRow`, `JassPlayer`, `IActionContext`, `ComponentSlotStyle`, `vec2`, `VisualizePlugin`, `NcTab`, `XTransferNode`, `ILiquidationCandidate`, `ITaskRepository`, `CreateProjectCommand`, `worker.IWorkerContext`, `GraphContract`, `DropDownProps`, `ElementFound`, `forge.pkcs12.Pkcs12Pfx`, `Persona`, `Meta`, `ImportType`, `SearchCondition`, `CoerceFunc`, `EntityUID`, `CanvasElementModel`, `TestResults`, `IdentifierDecorator`, `StudioState`, `ScreenService`, `TResolvedResponse`, `AddUpdatesEvent`, `ControlActivity`, `DownloadResponse`, `InstallVirtualAppParams`, `WebampWindow`, `BlocksInfo`, `ListGroupsCommandInput`, `HistoryEntry`, `IDownload`, `InvalidateOptions`, `Rendered`, `RolesFunc`, `AbiInput`, `NgControl`, `Endomorphism`, `BaseMaterial`, `TypescriptEditorPane`, `IPersonalizationSurveyAnswers`, `RegExpLiteral`, `MediaRequest`, `MonsterArenaStats`, `NumberExpression`, `Connections`, `DatabasePoolConnection`, `LibraryStoreItem`, `EventToPrevent`, `URL_`, `AstModuleExportInfo`, `Nth`, `HttpHeader`, `ReportingStore`, `RetryData`, `GetConfigurationSetEventDestinationsCommandInput`, `SplineRouter`, `WebService`, `QTransition`, `ChaCha20Poly1305`, `PeerConfig`, `SyncValidation`, `TensorBuffer3D`, `MaybeAsync`, `FunctionService`, `AppsCommands`, `NumberInputProps`, `CountState`, `AutoRestGenerateResult`, `PlotLineOrBand`, `JSONResponse`, `DateTimeParts`, `TxBuilder`, `LibrariesBuilder`, `DBSchema`, `PathDescription`, `OverlayEventDetail`, `ProjectLanguage`, `X12SerializationOptions`, `ValueClickActionContext`, `IPeacockElementAdjustments`, `CheckboxProps`, `BuildWatchEmitter`, `DayModifiers`, `ISavedObjectTypeRegistry`, `PrimAction`, `Question`, `SagaEnv`, `DataToGPUOptions`, `PositioningPlacement`, `StorageEntry`, `StoreOrStoreId`, `GfxRenderCache`, `SymbolDisplayPartKind`, `ForegroundContexts`, `DifferentHandlerParam`, `S3Action`, `BitcoinUnsignedTransaction`, `ControllerSessionScope`, `ClientEngineType.Library`, `Scripts`, `StagePanelDef`, `TransactionInstruction`, `SuccessfulResponse`, `ParserTreeValue`, `ExpoConfigFacebook`, `OPCUAClient`, `ISwaggerizedRouter`, `TMessage`, `SetupDeps`, `JsonExpr`, `Sentence`, `ListPackagesCommandInput`, `ast.FunNode`, `PsbtTxInput`, `PortalCommunicator`, `DatasetLocation`, `Contents.IModel`, `ExpressionFunctionVarSet`, `LocalForageWithObservablePrivateProps`, `ChildField`, `FormComponent`, `IUpSetDump`, `StagePanelType`, `UseSelectProps`, `BlobStorageContext`, `MockObject`, `VpnSite`, `requests.ListSuppressionsRequest`, `WebAppCreateStack`, `UserResolvable`, `CollectedData`, `TestElementRefersToElements`, `IncrementalElement`, `IOption`, `ApmBase`, `ReactiveCommand`, `MerchantOrderEntity`, `WeaveResult`, `JhiDataUtils`, `KeyAttribute`, `LayoutVisualizationGroup`, `RTCRtpReceiveParameters`, `CollectionCompilerMeta`, `Filesystem.ReadJsonAsync`, `PageOptions`, `SiteListItem`, `ActivityState`, `AuthorizationContext`, `crypto.Hash`, `ReadableOptions`, `IComboBoxOption`, `Swatch`, `ListValue`, `IMenuProps`, `EdgeCalculatorDirections`, `Keypair`, `StylusState`, `GeometryProvider`, `PartitionHash`, `InventoryPlug`, `ContextView`, `CopyButtonProps`, `GSConfiguration`, `knex.Raw`, `ClipVector`, `GrowableXYArray`, `FileSystemCallback`, `StaticTheme`, `NestedRecord`, `pulumi.CustomResourceOptions`, `Strategy`, `LogAnalyticsMetaFunctionArgument`, `IProseMirrorNode`, `PresetInfo`, `ExtractRouteParams`, `CesiumEvent`, `RawModule`, `requests.CancelWorkRequestRequest`, `FileMatcherPatterns`, `DefinitionInfo`, `Parser.Tree`, `SimpleASTSeq`, `WrappedCodeBlock`, `INotificationDocument`, `MapperOptions`, `FileUri`, `Report`, `StackRootNavContext`, `ArticleFormat`, `ScryptedDeviceType`, `Initialization`, `Authenticator`, `MergeTree.Marker`, `EntityCollectionRecord`, `GRU`, `NgSelectComponent`, `EmulatorContext`, `AnyOf`, `IExportOptions`, `NodeStructure`, `CreateNoticeDto`, `StyleConfig`, `interfaces.Request`, `RegionTag`, `HeadersJson`, `TimeOffsetInterval`, `WindowWrapper`, `EditorGroup`, `TemplateTransformerData`, `TTheme`, `ThrowAsyncIterable`, `EnumStringHelper`, `FormatTraits`, `IWebhookRequest`, `CapabilitiesResponseWrapper`, `EngineDefaults`, `ParticipantsAddedEvent`, `Res`, `TEName`, `MsgCreateLease`, `AlignmentFactory`, `ContainerFlags`, `BigQueryRequest`, `DebugSessionOptions`, `DynamicAttrs`, `AgentConfig`, `ElementEventCallback`, `RequestProvider`, `IntrospectionInputObjectType`, `MappingTreeItem`, `MeshFragData`, `IteratorContainer`, `EnhancedGitHubIssueOrPullRequest`, `ScopedLogger`, `CardRenderItem`, `BuildContext`, `GroupOrOption`, `CharRangeSection`, `OpenSearchDashboardsServices`, `SearchIssuesAndPullRequestsResponseItemsItem`, `Type_Enum`, `ControllerStateAndHelpers`, `SpeechConfigImpl`, `MemberDef`, `CodeMirror.EditorChange`, `StorageValuesV7`, `ICalendarEventBase`, `DataCollection`, `Cmp`, `SQLFragment`, `MonikerData`, `SaveType`, `IbkrEvents`, `MobileService`, `GetRowHeightFn`, `NugetPackageTableFields`, `PartitionSpec`, `MatBottomSheetContainer`, `CheerioFile`, `ContractRegister`, `Backoff`, `InHostPacket`, `SwiftProperty`, `BaseModel`, `MediaModule`, `ValueFn`, `ValidatorData`, `PlotSpec`, `requests.ListClusterNetworkInstancesRequest`, `commonServices`, `BaseLogger`, `SimpleRect`, `ISelectorMap`, `nsIDOMNode`, `CommandInfo`, `PixelRendr`, `TwistyPropDebugger`, `GetEmailIdentityCommandInput`, `strtok3.ITokenizer`, `RemirrorJSON`, `TestOperation`, `Departement`, `CodeGenerator.Params`, `IExcerptTokenRange`, `SelectorParser.Node`, `AxiosRequestConfig`, `azureTable.Table`, `Highcharts.AnnotationEventObject`, `CoverageOptions`, `JackettFormattedResult`, `PlatformLocation`, `RouteExecutionFromInput`, `ResultAccumulator`, `PropType`, `PoiInfo`, `Handlers`, `MDCRippleAdapter`, `DeserializationOption`, `NavNodeManagerService`, `ControlPanelSectionConfig`, `IGlobalState`, `TreemapSeries.NodeValuesObject`, `CommittedFileChange`, `ElementCoreContext`, `FileAnnotationType`, `TimeBuckets`, `SelectablePath`, `OES_vertex_array_object`, `RequestMethod`, `NetworkOptions`, `SerializedCard`, `GitStashReference`, `HemisphericLight`, `LexoDecimal`, `AuthenticateCustomRequest`, `LogicalKeyboardKey`, `VLC`, `PossiblyAsyncHierarchyIterable`, `ReadonlyPartialJSONObject`, `GX.Register`, `FaceInfo`, `DefaultEmitOptions`, `ISignature`, `PointObject`, `UpdateQueryNode`, `AggParamsState`, `DataStoreTxEventData`, `Highcharts.AnnotationChart`, `RequestContext`, `RawResponse`, `CrawlerRunOptions`, `PartyData`, `TalentMaterial`, `SipgateIOClient`, `IBaseRequest`, `EcsMetricChange`, `ElementAttrs`, `FileSearchCriteria`, `TransactionAsset`, `BufferStatusResult`, `TextmateSnippet`, `SpawnPromise`, `WithReservedWord`, `ISpriteMeta`, `Weekday`, `PickerComponent`, `ImportObject`, `BtnProps`, `EntityEvictEvent`, `ResponseModel`, `ILendingPool`, `Call_SendResultsTo`, `ISurveyObjectEditorOptions`, `ConfigObject`, `ObjectLike`, `DataClassEntry`, `AdShowOptions`, `Associative`, `RiskElementModel`, `GadgetInstanceService`, `defaultFontWeights`, `ExtHostCommentThread`, `WeekDayIndex`, `Gaxios`, `DescribeJobExecutionCommandInput`, `IGameEditorContext`, `DecoratorObject`, `MagitBranch`, `CurrencyAmount`, `EmployeesService`, `IMinemeldStatusNode`, `ReactApollo.OperationOption`, `History`, `SteeringPolicyPriorityAnswerData`, `mdast.Root`, `NowFile`, `kms.KmsManagementClient`, `ContainerModule`, `TestConsumer`, `ImportSpecifier`, `StatedBeanMeta`, `DunderAllInfo`, `ExtractScript`, `HighlightedType`, `Utility`, `Talk`, `Forest`, `ParsedSystem`, `DamageTypeData`, `Policy`, `android.bluetooth.BluetoothGatt`, `RoomPartialState`, `FileStore`, `CalibrationLabware`, `FunctionKey`, `DomainDeprecationDetails`, `NamedNodeMap`, `Namer`, `ExportDataType`, `SearchResultPage`, `JQueryPromise`, `TContent`, `SwitchContainerProps`, `DColorButton`, `CustomerData`, `PullToRefresh`, `MockDynamicContent`, `WeakStorage`, `AreaSeriesStyle`, `JSX.TargetedMouseEvent`, `SingleSelectionSet`, `CartProduct`, `PlayerStateService`, `DecompilerEnv`, `p5ex.CleanableSpriteArray`, `MicrosoftSqlServersResources`, `NodeBase`, `LineCounter`, `PartOfSpeech`, `IPostMessage`, `IVueAuthOptions`, `BindingEditorContextInfo`, `UserListQueryDto`, `VirtualDeviceScript`, `TranslaterPoint`, `ConflictState`, `AnnotationConstructor`, `ECompareValueType`, `IRowDetails`, `IGistMeta`, `AppSettingsService`, `Solution`, `IStorageWrapper`, `DOMRect`, `SpeedKmH`, `TokensService`, `AuthorizationRequest`, `EmotionCanvasTheme`, `DatabaseConfig`, `DataProxy`, `ActualT`, `TransactionState`, `MatButton`, `Uploader`, `PlayerActions`, `RunOutput`, `QueryArgs`, `WebGLTexture`, `LooseValidator`, `ESLintExtendedProgram`, `m.VnodeDOM`, `LifecyclePeer`, `UIPickerView`, `NuclearMeta`, `TraceEvent`, `CoverageFragment`, `ColorStyleProps`, `PasswordBasedPreset`, `CalcIdxType`, `AdadeltaOptimizer`, `ProfileOrganizationResponse`, `Trace`, `ConnectionFormService`, `WhereOptions`, `IChildNodesMap`, `ReactionType`, `BrokenConeSide`, `TestInvokeAuthorizerCommandInput`, `GraphqlConfig`, `NamedObjectDef`, `FFMpegInput`, `StrapiAttribute`, `DefaultResourceOptions`, `ConfigEnv`, `RollupTransition`, `DeleteConnectionCommandInput`, `KeyToDiffChangeMap`, `StorageProxy`, `TestingEntity`, `TenantService`, `RunEveryFn`, `Rtcp`, `TaskConfiguration`, `CornerFamily`, `JsonPatchOperationPathCombiner`, `MealForm`, `CompilerBuffer`, `ProvisionByoipCidrCommandInput`, `ts.MethodDeclaration`, `HttpTerminator`, `ResolveProvider`, `Actual`, `IBasicSession`, `N`, `AutoArchiveSettingsDelegate`, `BaseConvertService`, `ParseContext`, `IWorkflowDataProxyAdditionalKeys`, `RelayerRequestSignatureValidator`, `AndroidInput`, `DashboardTableData`, `OperationElement`, `ITransactionOption`, `SimulationOptions`, `IgAppModule`, `BorderStyle`, `GeoContainmentAlertParams`, `UriComponents`, `Evaluator`, `TNSDOMMatrix`, `RouterInfo`, `PatternOutput`, `ConnectorDeclaration`, `Role`, `JobExecutionSummary`, `SubscriptionsClientOptions`, `HttpMethods`, `VimValue`, `Accept`, `ImportResult`, `NglInternalDate`, `AnyParameterTypeDescriptor`, `IAssociationParams`, `CompilerEventDirAdd`, `EntityCacheQuerySet`, `AboutService`, `OnOptions`, `MigrationSummary`, `SavedVisInstance`, `ScenarioCheckResult`, `Fold`, `DataAction`, `DefinitionRowForInsert`, `requests.ListSecurityListsRequest`, `NotSkeleton`, `DynamoToPromise`, `AsObject`, `reflect.Assembly`, `WebCryptoPartialPbkdf2`, `Return`, `FileIncludeReason`, `AndroidActivityResultEventData`, `StubbedInstanceWithSinonAccessor`, `DiffView`, `TreeNode`, `GradientColor`, `NodeLink`, `AWS.AWSError`, `LightGroup`, `Firestore`, `DaffCountryFactory`, `IDragData`, `CallControlOptions`, `PrintOptions`, `DictionaryQueryEntry`, `WorkspaceField`, `PeerSetup`, `ProtoServer`, `MediaKey`, `PutEventsCommandInput`, `ActiveEnvironment`, `THREE.Matrix4`, `StepOptions`, `Thumbnail`, `BufferTokenizer`, `ExpressionAttributeNames`, `ContentBuilder`, `ExtraCommandLineOptions`, `SavedObjectsCollectMultiNamespaceReferencesOptions`, `FillLabelConfig`, `PaneWidget`, `PartialQueryLang`, `Pizza`, `ListFilesResult`, `TsConfig`, `XYPoint`, `SelectBase`, `None`, `PiEditProjectionLine`, `SubEntityData`, `WorkspaceType`, `DMMF.Datamodel`, `FileStructureType`, `TerminalApiRequest`, `LoggerOptions`, `IActionCodeSettings`, `ResizerKeyDownEvent`, `SegmentType`, `OpUnitType`, `FullCertificationRequestDTO`, `FeeExtensionsConfig`, `PluginRegistration`, `V1Node`, `UhkModule`, `KeyEventLike`, `StoreDestinationArray`, `TokenDetailsWithCoingeckoId`, `ListImagesCommandInput`, `IAaveGovernanceV2`, `CreateAskDTO`, `AreaField`, `StoryArgs`, `Relations`, `ForgotPasswordAccountsRequestMessage`, `InputValue`, `LocatedError`, `Boundaries`, `MessageRenderer`, `RnM2`, `DependencyType`, `OP_PUSHDATA`, `ITriggerResultObject`, `CANNON.Body`, `DocgeniLibrary`, `ParseSchemaTypeInfo`, `ExpressResponse`, `ResInfo`, `TsRadioOption`, `DisputableVotingData`, `CompletionBatch`, `OasPathItem`, `WrappableType`, `ActionSpec`, `GetRepositoryPolicyCommandInput`, `PatternInfo`, `Utils.ITimeProvider`, `IdDTO`, `GeneratedIdentifier`, `vscode.MessageOptions`, `ConvexClipPlaneSet`, `array`, `EnrichedLendingObligation`, `SecureStorage`, `NoteItemDummy`, `AppStatus`, `SingleSegmentArena`, `BenefitMeasurementIndicator`, `StacksTestnet`, `Specie`, `RadarChart`, `DefaultComponent`, `ARMRomItem`, `CallSettings`, `ApplicationShell`, `EventListenerHandle`, `FeeMarketEIP1559Transaction`, `IPopoverProps`, `ThemeColor`, `EncryptContentOptions`, `AppointmentMoment`, `WorkspaceServiceInstance`, `angular.ui.IStateService`, `google.maps.DirectionsResult`, `NotebookCellOutputItem`, `firebase.firestore.Firestore`, `AppActions`, `Flag`, `CommitID`, `InjectableType`, `CullMode`, `StreamPresenceEvent`, `AccountApple_VarsEntry`, `FastifyReply`, `QueueInfo`, `PlaybackParticipant`, `FlexPluginArguments`, `ReadonlyPartialJSONValue`, `RemoteRepositoryRepository`, `TxnJsonObject`, `NetworkErrorType`, `TestReference`, `IndexPatternsContract`, `App.contentSide.ICommunicationToBackground`, `StyleDefinition`, `YDomainRange`, `MediaTrackCapabilities`, `MetricDataQuery`, `Switchpoint`, `CoreWeaponMode`, `IMeshPrimitive`, `IInsert`, `BatchNormalization`, `TestCase`, `ListFindingsCommandInput`, `DefaultMap`, `ButteryFile`, `WorkspaceSymbolCallback`, `request.Test`, `Text`, `BzlConfiguration`, `ReducerManager`, `UIFunctionBinding`, `DecoratorArg`, `ExtensionNodeAttrs`, `UpdateConfigurationCommandInput`, `DiagramMakerNode`, `Vuex.Store`, `nameidata`, `ApiContract`, `EntryControlCCConfigurationReport`, `ErrorDataKind`, `ProposalIdOption`, `CustomStyle`, `MovementItem`, `IEmployeeCreateInput`, `HttpResponseObject`, `TSTopLevelDeclare`, `ControlledComponentWrapperProps`, `PacketType`, `AudioConfigImpl`, `MessageCode`, `XmlEmptyBlobsCommandInput`, `IManagementApiClient`, `QueryLeaseRequest`, `PluginInsertAction`, `BabelPresetChain`, `StackSummary`, `IConfigFile`, `WebGPUBackend`, `GfxPrimitiveTopology`, `ICurrentUserState`, `ILocation`, `tf.Scalar`, `UVFile`, `TwistAction`, `ComponentTest`, `IOsdUrlStateStorage`, `MUser`, `ParsedIcons`, `ReplicationConfigurationReplicatedDisk`, `PluginOptions`, `ItemsService`, `WorkflowItemDataService`, `CountQueryBuilder`, `Time`, `TestCommand`, `DeleteServerCommandInput`, `ForwardingSpec`, `IActorContext`, `LambdaMetricChange`, `CssProperty`, `CookieJar`, `InviteMembersCommandInput`, `PasswordHistoryData`, `Dino`, `TextElementState`, `BuildInfo`, `ListFiltersCommandInput`, `BasicGraph`, `ServiceRoute`, `UIStorage`, `Initiator`, `http.ClientRequest`, `ISubnet`, `InternalServiceException`, `ISPRequest`, `GX.TexCoordID`, `DFA`, `StatementBodyContext`, `d.PropOptions`, `Curry2`, `NodeRequire`, `ShallowRef`, `WorkflowNode`, `PackageMetadata`, `LoopTemplate`, `Benchee.Options`, `Grid`, `IQuestionnaire`, `IFluidDataStoreChannel`, `Clause`, `MatchmakerAdd_NumericPropertiesEntry`, `StatCalculated`, `SwPush`, `UIWindow`, `SearchInWorkspaceOptions`, `Sprite3D`, `HID`, `WorkUnit`, `RouterUrlState`, `Bill`, `fse.Stats`, `KernelMessage.IExecuteRequest`, `IPossibleParameterFile`, `AssociationCCAPI`, `CustomEventInit`, `PointAndCrossingsList`, `ListWebACLsCommandInput`, `CSSScalar`, `RootTestSuite`, `GfxTextureP_WebGPU`, `SphereCollisionShape`, `IRenderMimeRegistry`, `ProxyTarget`, `AttributeInput`, `IBindingSetting`, `ObservableObjectAdministration`, `MIRFieldDecl`, `Attach`, `SnapshotFragment`, `AutoScalingGroup`, `AstIdGetter`, `OperationNode`, `JWTSignOptions`, `UnionTypeProvider`, `AuthClient`, `t.TSType`, `PropOptions`, `RoomState`, `TraversalStrategy`, `Coding`, `ExpNum`, `IMessageParser`, `JSNode`, `NodeTransform`, `IndexableNativeElement`, `ProposedPosition`, `ReprOptions`, `StreamedData`, `SelectorAstNode`, `AuthMachineContext`, `IHttpRequest`, `DataTypeContext`, `MutationFunctionOptions`, `TransitionConfig`, `ZRenderType`, `ExecuteResultLine`, `ToastInput`, `Net.Socket`, `IssuePublicationIdentifier`, `Producer`, `ServiceDependency`, `MessageCreateOptions`, `OpenSearchConfig`, `LoginProps`, `PbEditorElement`, `EditId`, `Job`, `GanttItem`, `displayCtrl.ICtrl`, `RichText`, `ConcreteTestSettings`, `PluginItem`, `MerkleTreeInclusionProof`, `VoidExpression`, `NearestIntersection`, `MatchingDirection`, `Broadcaster`, `IPrintableApplication`, `DeepLinkConfig`, `Tracer`, `SortKey`, `SwitchProps`, `FileSystemAccess`, `ast.NodeType`, `TagsListItem`, `OpenAPI.Parameter`, `Hand`, `ExtractorChecker`, `MockControllerAdapter`, `MovementState`, `Delivery`, `ESMap`, `PointerUpdateTrigger`, `GeometryRenderer`, `Fig.Subcommand`, `Inbound`, `SimpleTreeDataProviderHierarchy`, `Applicative3`, `SFSchema`, `CollectionWithId`, `LoginRequest`, `TextureData`, `TxsTopicData`, `DateRangeValues`, `TranslatableService`, `VertexPlaceholder`, `FunnelStep`, `ComponentRegistrant`, `GroupFrame`, `PagingMeta`, `OnPostAuthToolkit`, `GeometryStateStyle`, `INodeInputSlot`, `CdtEdge`, `Emoji`, `ConeTwistConstraint`, `RelationField`, `MarkerNode`, `SwipeGestureEventData`, `MatchScreenshotOptions`, `DescribeAssetCommandInput`, `ImageProps`, `ItemProps`, `MatchDSL`, `ProcessOutput`, `MarkdownEngineConfig`, `Bonus`, `StorageItem`, `IGraphQlSchemaContext`, `ImageSourceType`, `MetaRewritePolicy`, `ICollectionOptions`, `StyledLinkProps`, `ControllerMethods`, `TestClientLogger`, `FlexibleConnectedPositionStrategy`, `ServiceItem`, `d.EventOptions`, `BreadcrumbLinkProps`, `EditablePolyline`, `SenderDocument`, `Contribution`, `AppRoot`, `IPropertyOption`, `CoordinateExtent`, `IAccountDetails`, `CollisionKeeperCategory`, `PackageModuleRef`, `DaffCategoryFilterRangeNumericRequest`, `CombinedPredicate`, `Translate`, `ClientWrapper`, `ResourceList`, `SrtpContext`, `SpecificEventListener`, `CsvWriter`, `ConfigOption`, `ProjectItemImpl`, `ThemeInfo`, `Locations`, `CppBytes`, `IBehavior`, `logging.Log`, `CommerceLayerClient`, `TodosState`, `ListenerRemoveCallback`, `TImportOptions`, `IComponentEvent`, `CustomFontEmbedder`, `FieldQueryBase`, `DaffCategoryFilterRangeNumericPairFactory`, `OptionPureElement`, `EidasResponseAttributes`, `MlLicense`, `WebResponse`, `WindowProps`, `CommentController`, `EmusakEmulatorConfig`, `FeeStructure`, `ts.NumericLiteral`, `EdmxReturnType`, `EitherNodeParams`, `DroppableStateSnapshot`, `MockCallAgent`, `EthereumPaymentsUtils`, `Traversal`, `d3Geo.GeoProjection`, `ICodeBuilder`, `StylableFile`, `MockSerialPort`, `HippodromeEditOptions`, `ExecutionContextContainer`, `DaffExternallyResolvableUrl`, `PartyClose`, `UploadLayerPartCommandInput`, `FormattingOptions`, `UpdateFunctionCommandInput`, `TorusPipe`, `MediasoupPeer`, `BackupService`, `InputComponents`, `Epsg`, `SymbolAndExponent`, `ProDOSVolume`, `PolyIDAndShares`, `PullBlock`, `PluginResult`, `AutonomousDatabaseKeyHistoryEntry`, `DiscoverStartPlugins`, `UserTask`, `DashboardViewportProps`, `EnumMember`, `mixedInstance`, `ListPoliciesRequest`, `HighRollerAction`, `SubscriptionList`, `EmptyAction`, `LinkState`, `MCommentOwnerVideo`, `ProjectRepository`, `DrawOptions`, `BuildableTree`, `PersistentState`, `Nodelist`, `BodyTempState`, `HttpRequestWithGreedyLabelInPathCommandInput`, `ExtractorData`, `ItemField`, `CreateDatasetRequest`, `PolygonBoxObject`, `EmitEvent`, `TestDatum`, `PReLU`, `AccountBalance`, `GetMembersCommandInput`, `requests.ListCloudVmClusterUpdatesRequest`, `ProviderConfiguration`, `KBarState`, `vType`, `Groups`, `RRI`, `ResponsiveValue`, `Pairing`, `IMod`, `CalendarWrapper`, `RateLimitArguments`, `SlashingProtection`, `NodeDisplay`, `MpUIConfig`, `boolean`, `FunctionStats`, `DimensionGroup3D`, `Redlock`, `RenderBuff`, `PitchName`, `HTMLOptionElement`, `SyncNotifyModel`, `Ng2StateDeclaration`, `TransactionPool`, `UserError`, `YEvent`, `PageProps`, `MockElement`, `HashLockTransferAppState`, `OrientedBounds`, `AnyData`, `BidirectionalLayerArgs`, `MomentValidator`, `ObjectTypeKind`, `IResources`, `MDCMultilineTextField`, `IDataMessage`, `PinLike`, `RuleTypeModel`, `ServerResponseService`, `ISeedPhraseFormat`, `RuleSpec`, `IExecutionResult`, `DataBeforeRequestOptions`, `CollectorSet`, `NativeDeleteOptions`, `TempDirectory`, `CreateAttendeeCommandInput`, `Edges`, `TabModel`, `DescribeEndpointCommandInput`, `ProjectToApiAnalysis`, `SchemaQuery`, `DiscussionDocument`, `PaginationCallback`, `Pipeline`, `SceneControllerConfigurationCCReport`, `DataTypeFactory`, `VnodeDOM`, `CipherRequest`, `SceneColorTheme`, `SeriesTypePlotOptions`, `TestDecorator`, `UIModeType`, `ScopedLogging`, `PartialEmotionCanvasTheme`, `ActivationIdentifier`, `BlockPointer`, `BodyPartDefinition`, `ViewConfig`, `QueryBidsRequest`, `GfxRenderPipelineP_GL`, `GeometryObject`, `ISavedSearch`, `tfc.NamedTensorMap`, `RecordOfType`, `ExceptNode`, `MatGridTile`, `TimeUnit`, `WsBreadcrumbsService`, `VscodeSetting`, `CodeEditor.IPosition`, `RouteResponse`, `DaffCartPaymentMethod`, `OauthRequest`, `FSEntry`, `StepExtended`, `BastionHost`, `IUserData`, `RouteService`, `SalesInvoice`, `RefSet`, `Station`, `ClientPayload`, `ItemKeyboardNavigator`, `AstNodeWithLanguage`, `MActor`, `IAuth`, `ITestCase`, `WpResourceConfig`, `CogStacJob`, `BufferLike`, `VariationInfo`, `ObOrPromiseResult`, `WebSiteManagementModels.User`, `MockRequestInfo`, `Hapi.Server`, `GetQueryResultsCommandInput`, `CredentialsService`, `EndpointWithHostLabelOperationCommandInput`, `ImportAsNode`, `AuthenticateSteamRequest`, `DedicatedHost`, `ResolvedModuleWithFailedLookupLocations`, `HTMLPropsWithRefCallback`, `RouterConfiguration`, `OperationError`, `ConnectionResult`, `ParsedInterval`, `SavedObjectOpenSearchDashboardsServices`, `css.Node`, `Colors`, `messages.Location`, `RawResult`, `Oazapfts.RequestOpts`, `ImageHandlerEvent`, `AbiOutput`, `ResolveStylesOptions`, `RulesObject`, `CreateRepositoryResponse`, `PN`, `ChannelContract`, `Tracing`, `ServerMessage`, `DenoExtensionContext`, `LinkedHashSet`, `AlertInput`, `IAudioStreamNode`, `RNG`, `DragTarget`, `MicrosoftStorSimpleManagersResources`, `ResponseCallback`, `PrimaryKey`, `PatternMappingKeyEntryNode`, `RefreshTokenService`, `NgActionBar`, `BuildifierFileType`, `SlotOp`, `requests.ListMetastoresRequest`, `ArrayValues`, `TrackBuilder`, `PaginationDTO`, `SystemService`, `DID`, `IClassicmenuRuleSpec`, `MDSPostgresClient`, `ConnectArgs`, `ListUsersResponse`, `ConvLSTM2DCell`, `VaryMap`, `MdcCheckbox`, `RouteMethod`, `NpmInfo`, `TraceConstraint`, `SettingsDataUpdate`, `NotifyMessageDetailsType`, `KonvaEventObject`, `BlockchainTreeItem`, `android.graphics.drawable.Drawable`, `BinaryBitmap`, `FieldJSON`, `DeleteDomainCommand`, `ScalarTypeSpec`, `InfoActor`, `ExtraArgs`, `FileSystemUpdater`, `ESRuleConfig`, `UmiPluginNProgressConfig`, `Found`, `VcalVeventComponent`, `TestingFacade`, `AnimeListStatusFields`, `FullCalendar.ViewObject`, `kuberesources.ResourceKind`, `LookupItem`, `SubnetGroup`, `SentryScopeAdapter`, `PermuteLayerArgs`, `DeploymentConfig`, `DataMessage`, `NoteSnippetEditorConfig`, `BindingState`, `BaseClient`, `FileSystemEntries`, `PutConfigurationSetTrackingOptionsCommandInput`, `ThemeTool`, `SubscribeActions`, `TypeOrTypeArray`, `BasicCalculator`, `ImportStatements`, `ImageryMapExtent`, `CardManager`, `EventListenerCallback`, `FileHolder`, `ISequencedDocumentAugmentedMessage`, `PluginOrPackage`, `SerializedVis`, `UniqueOptions`, `IAttachMessage`, `convict.Schema`, `TimeQueryData`, `ListChannelModeratorsCommandInput`, `AuthenticationTemplate`, `StatefulChatClientArgs`, `VtexHttpClient`, `Http3FrameParser`, `CountryState`, `NzConfigKey`, `EntryObj`, `InnerAudioContext`, `SslConfig`, `IPlayerState`, `SCNMaterial`, `LobbyMember`, `ServiceProto`, `BackupShortTermRetentionPolicy`, `Sizes`, `requests.ListRoutingPoliciesRequest`, `Fzf`, `RemoveTagsFromResourceMessage`, `ListItemProps`, `Visitor`, `DataGridRow`, `CardProps`, `ListModelDeploymentShapesRequest`, `OmvFeatureFilterDescriptionBuilder.FeatureOption`, `SourceComponent`, `PublicEndpointDetails`, `AbsolutePosition`, `CheckPrivilegesResponse`, `LinterOffense`, `AutoforwardConfig`, `JoinTree`, `CHAINS`, `IRouter`, `CircularList`, `FnModules`, `IControl`, `ContactPayload`, `OpticsDomain`, `CustomWindow`, `ChangeDatabaseParameterDetails`, `RecordEdge`, `ModalType`, `PersistConfig`, `ResponderType`, `ExtractOptions`, `CsmSlotEntity`, `SMTFunctionUninterpreted`, `GeneralEventListener`, `ConchQuaternion`, `IssuanceAttestationsModel`, `CloudAccounts`, `FileListProps`, `PutBucketTaggingCommandInput`, `Vpc`, `IZoweJobTreeNode`, `EmployeeRecurringExpenseService`, `WaveformRegion`, `VerticalTextAlignment`, `Ident`, `DaffCategoryPageMetadata`, `PrimitiveField`, `PgType`, `RunnerGroup`, `ProofStatus`, `WechatTypes.SendMessageOptions`, `DeleteKeyPairCommandInput`, `Assembler`, `SPClientTemplates.RenderContext`, `Formatter`, `IndexProps`, `SentryEvent`, `StreamZip`, `TimeLog`, `SqlFile`, `Notifications`, `RunnerInfo`, `MongoMemoryServer`, `ConditionalTransactionCommitmentJSON`, `IMainMenu`, `RTCRtpCodecParameters`, `glob.Options`, `BSPFile`, `Iprops`, `HandlerResourceData`, `monaco.editor.IMarkerData`, `CliConfig`, `IKeyValuePair`, `FirmwareWriterPhaseListener`, `Glossary`, `SocketUser`, `IOpenSearchDashboardsSearchRequest`, `FetchFn`, `RootCID`, `WordGroup`, `ASTParserTree`, `TokenStreamRewriter`, `DeferredAction`, `ResourceDayGridWrapper`, `CreateCollectionOptions`, `PlanetApplicationService`, `TeamsActionConnector`, `PubKeyEncoding`, `NodeBuilderContext`, `ModuleKind`, `DataViewCategoryColumn`, `InstantRun`, `AEADCipher`, `NgxsDataStoragePlugin`, `EthereumAddress`, `ConditionalType`, `TrackDetails`, `CreateCustomVerificationEmailTemplateCommandInput`, `EmployeeLevelService`, `MovieService`, `PlannerConfigurationScope`, `T3`, `Weapon`, `WriteTournamentRecordRequest_TournamentRecordWrite`, `Login`, `MediaElementAudioSourceNode`, `CMDL`, `MagickGeometry`, `ResourceDifference`, `GDevice`, `ExploreBundleResult`, `ClassMember`, `InteractionModel`, `ThunkCreator`, `Json2Ts`, `DebouncedFunc`, `HandleProps`, `ts.BlockLike`, `RequestUser`, `UseSubscriptionReturn`, `CueSet`, `ProviderState`, `ComponentRegistry`, `JsxOpeningFragment`, `MockContext`, `WyvernAsset`, `InlineResolved`, `ng.ILogService`, `StationModel`, `DaffConfigurableProductVariant`, `DataViewHierarchyNode`, `AnimationDesc`, `RefedMixin`, `PerspectiveGetResult`, `PersistencyBlockModel`, `Cidr32Block`, `ServerException`, `BackgroundBlurOptions`, `IMatrixProducer`, `Events.pointerdragend`, `SetOverlap`, `TraceServiceSummary`, `ExecOutput`, `IVisualizerVertex`, `ResponseHandler`, `Accidental`, `RetryStrategy`, `AndroidSplashResourceConfig`, `ShrinkStrategyMock`, `CategoryCollection`, `Mailbox`, `FindUsersResult`, `FuncArg`, `CityRouteProps`, `HookEffects`, `PaginationModelItem`, `InitialAlert`, `StructureValue`, `BaseContext`, `ConfigurationModule`, `StacksOperationOutput`, `tcl.Tag`, `ModuleResolver`, `BroadlinkAPI`, `AppStateStatus`, `Vout`, `SlashingProtectionAttestation`, `ICodeGenerationStackOutput`, `RegistryConfig`, `ElementInfo`, `GeoJSONGeometry`, `LinuxDistribution`, `Caching`, `pxtc.BlocksInfo`, `CompiledProxyRule`, `VoyagerSubscriptionContextProvider`, `BinaryOp`, `ir.Type`, `ModuleRpcCommon.EncodedContext`, `JobIdOption`, `SceneContext`, `NodeJSKernelBackend`, `StatefulChatClient`, `ModelPredictConfig`, `DeletePolicyCommandInput`, `Entries`, `CppParseTree`, `TFSavedModel`, `GfxTextureDescriptor`, `YCommandInput`, `IStatusWarning`, `ClusterExplorerResourceNode`, `d.CompilerWorkerContext`, `ComponentWithProps`, `StyledCharacterStrategy`, `AssignOptions`, `ethereum.PartialTransaction`, `WritableData`, `IMdcSelectElement`, `EventSource`, `RailRider`, `DataTypeConfig`, `IFrameAttachment`, `PlannerPage`, `CommandRunner`, `VariableData`, `DocumentFragment`, `BlogState`, `Champion`, `TextContentBuilder`, `RouteArgs`, `KVStorageBackend`, `RunnerOptions`, `SupClient.ProjectClient`, `FetchTicketsActions`, `ReleaseActionProps`, `ParserOptionsArgs`, `Lobby`, `IPermissionReturnType`, `TestKmsKeyring`, `AirnodeRrp`, `ExpressionParams`, `CognitoMetricChange`, `ExecutionProbe`, `protos.google.iam.v1.ITestIamPermissionsRequest`, `ProductEntity`, `T.ComponentMap`, `InputResolution`, `ScreenshotBuildResults`, `DecodedSignaturePart`, `XScaleType`, `d.ErrorHandler`, `ConnectedUser`, `TwingCompiler`, `InfiniteLine`, `requests.ListTagsRequest`, `OrderGraph`, `TestAccountProvider`, `FieldValuePair`, `BodyImplementation`, `LanguageModes`, `ParameterListContext`, `DatabaseConfiguration`, `UX`, `AnyArena`, `TAggConfig`, `d.RollupConfig`, `PersonaIdentifier`, `HashType`, `Presence`, `IDataSourceDictionary`, `SerializedMessage`, `LabelService`, `Datatable`, `AngularPackageLoggerMessageType`, `CommandLineOptionOfCustomType`, `ListImagesRequest`, `ModelRenderContext`, `DeclinationDictionary`, `NativeInsertUpdateManyOptions`, `ZoneDelegate`, `d.JsonDocs`, `IResultSelection`, `SpawnClose`, `BindingItem`, `Logs`, `chrome.tabs.Tab`, `XRViewport`, `CompositeStrings`, `WriteFunc`, `THREE.Path`, `GlobPattern`, `ForeignKey`, `OpusRtpPayload`, `d.JsonDocsDependencyGraph`, `T.Model`, `ChatState`, `GetDevicePositionHistoryCommandInput`, `MessageQueue`, `Plane3dByOriginAndUnitNormal`, `TestSystemContractsType`, `ListEvents`, `IResource`, `O1`, `ResponseValue`, `TransferCommitment`, `SignIn`, `HasPos`, `BoolShape`, `InnerPlugin`, `PlaneGeometry`, `Embeddable`, `RequestConfigT`, `PermissionService`, `KickGroupUsersRequest`, `Renderers`, `PersistedEvent`, `MarkerOptions`, `ForAllSuchThatInput`, `IKactusFile`, `ContextInternal`, `RepositoryManager`, `pulumi.Input`, `PreferenceChangeEvent`, `WeaveNode`, `PointProps`, `JobExecutionState`, `MagicExtensionWarning`, `TimeSlotService`, `requests.ListGiVersionsRequest`, `ThemeType`, `NotificationOptions`, `NFT721V1`, `CastEvent`, `SkiplistNode`, `TransactionMetadata`, `Rigidbody3D`, `IOsdUrlControls`, `FunctionReturnTypeCallback`, `ISearchGeneric`, `ifm.IRequestInfo`, `PeerType`, `datePickerModule.DatePicker`, `TileCorners`, `Domain`, `HintID`, `Cmd`, `UpdateAliasCommandInput`, `IdentityData`, `DebugPluginConfiguration`, `ServerSideVerificationOptions`, `Uint64Array`, `NodePolyfillsOptions`, `PageEditContextInterface`, `SVError`, `QueryParameters`, `GeoShape`, `ChatServer`, `BoundExistsFn`, `GlitzServer`, `FirstDataRenderedEvent`, `XBus`, `WorldCountry`, `ExpressRouteCircuitConnection`, `HTMLLinkElement`, `IGovernancePowerDelegationToken`, `ObjectCsvStringifier`, `KeyboardState`, `CoreImagesContract`, `FakeCommand`, `CSSOpts`, `Globber`, `PropertyName`, `VehicleState`, `EditorPlugin`, `ResolvedElement`, `ErrorWithMetadata`, `SVGForeignObjectElement`, `PropertyType`, `browsing.FilesView`, `ThemeUIStyleObject`, `PathComponent`, `PluginPass`, `DQCCacheData`, `MetricSeriesFragment`, `HookRegistry`, `AFileParser`, `GetAuthorizerCommandInput`, `ComponentList`, `CodeCell`, `CdsAlert`, `GenericOperationDefinition`, `SignedStopLimitOrder`, `IReadOnlyFunctionParameterCollection`, `SizeProps`, `ActionDefinitionByType`, `BcryptAdapter`, `Sym`, `S2`, `FirewallPolicyRuleCollectionGroup`, `TransferDirection`, `PartialRequired`, `LocalRegistry`, `TestUnitsProvider`, `WithString`, `InflectorRule`, `TranslateParams`, `MockService`, `UploadObservable`, `AxisSpace`, `AddConfigDeprecation`, `FetchStore`, `ChangeDetectorRef`, `DeletePortalCommandInput`, `JPADynamicsBlock`, `ReducerNode`, `NavigatorAxis`, `Conv2DConfig`, `SourceNode`, `NavigationNode`, `GPUAdapter`, `DiagnosticMessageChain`, `Overmind`, `DatabaseReference`, `GDITrack`, `GfxResource`, `ResolverInfo`, `ScaleContinuousNumeric`, `StudioBase`, `AssetMarketPrice`, `DeepMocked`, `BreadcrumbService`, `AggregationType`, `ScheduleActions`, `ResizeObserverCallback`, `ContestModel`, `Desc`, `MockedKeys`, `ScanSegmentVectorItem`, `ListPlaceIndexesCommandInput`, `Sequelize.Sequelize`, `VisualizationLinkParams`, `EmotesProvider`, `ModuleLinks`, `NumberPattern`, `ContainerProps`, `InternalCredentialManager`, `KeySchemaElement`, `SerializedRootCID`, `NameExpression`, `KeysToKeysToAnyValue`, `AggsSetupDependencies`, `TInjectTokenProvider`, `ThyTableColumn`, `TestHelper`, `GenericThemeShape`, `MockComm`, `NoteSnippetContent`, `uibPagination`, `Typehole`, `RibbonComponent`, `Timestamp`, `TranslationProject`, `ScrollViewProps`, `FullQuestionWithId`, `RulePathEntry`, `ProcessingEvent`, `FunctionResult`, `NetworkIndicator`, `NullableDateLimit`, `RequestProps`, `MeshStandardMaterial`, `ChannelStateWithSupported`, `Previews`, `MappingTreeObject`, `Depth`, `ConnectionSettings`, `LoggingService`, `ConfigValueFormat`, `SeriesBarColorer`, `webpack.LoaderContext`, `FirebaseAuthState`, `CompilerJsDoc`, `TsDocumentService`, `InstanceFailoverGroup`, `WebhookRequestData`, `RecipientCounts`, `ESLCarousel`, `CharacterStatsCalculator`, `RendererPlugin`, `UIEdgeInsets`, `IPolygonPoint`, `SimpleDeep`, `AxisData`, `ConsoleColor`, `PrinterService`, `DecomposedJwt`, `OcsConnection`, `MapDispatch`, `ProjectStatsChartDataItem`, `SemanticsAction`, `BrowserFeature`, `DiceRoller`, `HttpStatusCode`, `JiraIntegrationService`, `VaultItem`, `NzResizeEvent`, `THREE.Shader`, `CategoryThread`, `IDom`, `BluetoothCharacteristicUUID`, `TxData`, `NormalizedPapiParameters`, `TooltipOptions`, `UpdateDomainNameCommandInput`, `UserPasswordEntity`, `UseQueryPrepareHelpers`, `AttachedProperty`, `SqrlStatementSlot`, `ModbusEndianness`, `PerpV2BaseToken`, `IGroupCellRenderer`, `InvalidInputException`, `C7`, `Watchman`, `IHeaderExtensionObject`, `PathResolver`, `DynamoDB.BatchGetItemOutput`, `IParticle`, `CloudFrontWebDistribution`, `ScrollRect`, `IMeta`, `IHTMLInjection`, `Destination`, `ISavedObjectsRepository`, `UploadChangeParam`, `VpcSubnetType`, `Events.deactivate`, `ScopedHistory`, `NativeBookmarks.BookmarkTreeNode`, `UpdateRequest`, `ResourceCollection`, `SavedObjectEmbeddableInput`, `ViewPortComponent`, `PutPolicyCommandInput`, `RSTPreviewManager`, `ListConfigurationsRequest`, `WalletObjective`, `ConfigurationSectionEntry`, `ClientException`, `AlertCluster`, `SelectionManager`, `ResizeHandler`, `ForbiddenException`, `ParsedRequest`, `BehaviorTreeStatus`, `SectionMarkerConfig`, `GalleryState`, `AppInstanceJson`, `EditprofileState`, `ImageFormatTypes`, `ICacheEntry`, `HTTPHotspotObject`, `CrochetModule`, `Tsoa.Parameter`, `AWS.ELBv2`, `VariantMatchedResult`, `Compiler`, `IterationTypesResolver`, `py.AST`, `Area2DSW`, `AdInfo`, `CopyOptions`, `StorageLayout`, `LinkedAccountsService`, `WarningLevel`, `CodeGenOptions`, `SpawnHandle`, `NotebookModel`, `QueryStringFilter`, `TaskRoutine`, `NumberSymbols`, `ProposalService`, `HandlerDecorator`, `FilesystemEntry`, `ExtendedObject3D`, `ImGui.Vec4`, `ReducerAction`, `RouterService`, `FluentRules`, `ModuleDependencies`, `PropAliases`, `TableOfContentItem`, `FunctionImportParameters`, `TableConstraint`, `DestinationFetchOptions`, `ScannedClass`, `ParjserBase`, `TooltipOffset`, `ButtonStyles`, `oai3.Model`, `ParameterValues`, `ts.IntersectionTypeNode`, `Ray2d`, `IdentGenerator`, `Percent`, `SModelRoot`, `ContactCardEmbeddable`, `TriangleOrientation`, `RV`, `NodeCore`, `ModalComponentType`, `PartialTypeGuard`, `IAvailabilitySlotsCreateInput`, `HeaderActionIconProps`, `PathElement`, `DeclarationKind`, `EventActionCallable`, `TreeNodeIndex`, `ListNotificationsCommandInput`, `UntagResourceResult`, `NumbersImpl`, `NodeJS.Signals`, `TexImageSource`, `ListResponseModel`, `BIP32Interface`, `TSource`, `IImageAsset`, `System`, `ChannelChainInfo`, `ast.NodeTag`, `A11yConfig`, `AppContext`, `TimeseriesDataRecord`, `AuthHttp`, `TooltipProps`, `SKColor`, `ActualTextMarker`, `EventRegistry`, `MultipleFieldsValidator`, `GetGlobalObjectOptions`, `FluidObject`, `IUsedState`, `gang`, `IImperativeError`, `FetchData`, `FusedTeamMemberType`, `HeaterState`, `ITypedEdge`, `NumberSchema`, `iNotification`, `jqXHR`, `APIGatewayProxyHandler`, `RegisteredServiceAccessStrategy`, `WaveFile`, `E.Either`, `StagePanelManagerProps`, `zod.infer`, `restify.Server`, `TreeItem`, `ThroughStream`, `ICounter`, `Events.pointermove`, `TargetDiezComponent`, `ConchVector4`, `IMutableFlatGridItem`, `Conv3DTranspose`, `angular.resource.IResourceClass`, `SyncOpts`, `EventUiHash`, `FakeProviderConnection`, `NextComponentType`, `IUserState`, `ReactionCanHandleOptions`, `Re`, `WalletStateType`, `GXMaterial`, `Verification`, `EdgeCalculator`, `Exhibition`, `NetworkService`, `AddressFormat`, `ExecutableItemWrapper`, `ChildNodeType`, `NewObjectOptions`, `ExtensionModule`, `NodeKeyJSON`, `TsSelectedFile`, `IPass`, `SassError`, `CodeModExports`, `TestStatus`, `NavMenu`, `TablePipeline`, `EnrollmentAPIKey`, `DeleteAliasCommandInput`, `QuerySubmitContext`, `NewBalanceFn`, `SubCategory`, `DeviceCreateParams`, `IRegularAttr`, `OnePageDataInternal`, `MultiSigSpendingConditionOpts`, `ESFixedInterval`, `SetStateCommitment`, `V2SubgraphPool`, `IDataFilterValueInfo`, `Redis.RedisOptions`, `ManifestApplication`, `PathTree`, `MediaObserver`, `lf.schema.Column`, `BlobDownloadResponseParsed`, `AuthCredential`, `Slack.Message`, `From`, `PolicyProxyHookOptions`, `SingleVertexInputLayout`, `FirebaseFirestore.CollectionReference`, `EffectiveTypeResult`, `CmsIndexEntry`, `StatefulChatClientOptions`, `ActionMetadata`, `MuteRoomTrackResponse`, `GroupService`, `V1Secret`, `ColumnState`, `TokenStore`, `StopItem`, `CreateSiteCommandInput`, `GoalKPI`, `Mission`, `SharedFunctionStub`, `AddressListItem`, `AndroidProject`, `IConstructor`, `FTP`, `GlobalNames`, `PartitionSmallMultiplesModel`, `TextInputLayout`, `IAppError`, `IGenerateReleaseNotesOptions`, `StdioOptions`, `ChannelEffects`, `CdkDrag`, `TaskFunction`, `FieldArrayWithId`, `InfectableParticle`, `SerializedBoard`, `TipLengthCalibration`, `DiffParser`, `AttendanceService`, `SolflareWallet`, `LabelPropertyDataFilterer`, `DefaultEditorAggAddProps`, `ILayoutState`, `SceneParams`, `PIXI.Sprite`, `ElementSize`, `Section`, `ThemeProperty`, `sdk.SessionEventArgs`, `BleepsSetup`, `MainTab`, `TsInterfaceInfo`, `PromiseType`, `OriginConfig`, `ZebuLanguage`, `ISerializedInterval`, `HttpClientResponse`, `Bitstream`, `FaunaDBClient`, `VpcData`, `TimePickerProps`, `SlashCommandStringOption`, `GenericOneValue`, `GeneratorManifest`, `ResolutionHelper`, `TheRdsProxyStack`, `TypeInfo`, `MiddlewareAPI`, `PropertyValues`, `ExplorerExtender`, `PasswordService`, `URLMeaningfulParts`, `requests.ListIncidentsRequest`, `GeoPointInput`, `Security2CCNonceReport`, `DiagnosticRelatedInfo`, `BizResponse`, `StatusNotification.Status`, `VPC`, `InternalsImpl`, `GetRegexPatternSetCommandInput`, `IAnimatable`, `AbstractColumn`, `PackageTreeItem`, `THREE.DataTexture`, `UseCaseFunction`, `CrudFeatures`, `IPackageFile`, `GraphWorkspaceSavedObject`, `IInboundSignalMessage`, `DraftArray`, `Compose`, `Y.XmlText`, `MapOfType`, `Pose`, `BitbucketAuthResponse`, `AxisOrientation`, `RecoilState`, `WrapperOptions`, `ServiceRepresentation`, `BulletViewModel`, `Cycle`, `MenuMapEntry`, `ISetBreakpointsArgs`, `ITrackWFeatures`, `Statement`, `IBatteryCollectionItem`, `IKLink`, `Mountable`, `GetSpaceParams`, `AzureDevOpsOpts`, `IPaginationProps`, `ToneConstantSource`, `CarsService`, `GraphQLContext`, `CompilerEventBuildLog`, `PostInfo`, `AppCheck`, `TestBufferLine`, `UiSchema`, `Peak`, `U2NetPortraitConfig`, `ParameterValue`, `IArticleAction`, `IContentSearchOptions`, `MergeFsResult`, `GeneratedPoint2D`, `IWebsocketMessage`, `ActionHistory`, `PageType`, `WebDNNCPUContext`, `CompilerStyleDoc`, `CustomerLayoutState`, `AddressLabel`, `OnMessageFlags`, `RawSkill`, `AbridgedFormatErrorMetadata`, `TestFunctionImportComplexReturnTypeParameters`, `FiltersActions`, `NamedTypeNodeDef`, `TooltipData`, `LeaseOperationResponse`, `OutputNode`, `EventInstance`, `LaunchConfig`, `DataTableRow`, `UserAction`, `MessagingDeviceResult`, `LegacyDrawing.Animation`, `PathContext`, `IConnextClient`, `EmbeddablePackageState`, `AppSettingsFormValues`, `B4`, `IAddGroupUsersOptions`, `QueueType`, `angular.ICompileService`, `ComputedOptions`, `DescribeCertificateCommandInput`, `SetOperations`, `CommonProps`, `PriorityQueue`, `SessionModel`, `SetupResult`, `ODataModel`, `MaterialGroup`, `ID3Selection`, `NPC`, `SaveResult`, `AssemblyExpressionContext`, `SerialPort`, `ContactDocument`, `Names`, `PinReference`, `firebase.firestore.QueryDocumentSnapshot`, `LSTMLayerArgs`, `Mmenu`, `ScrollBar`, `FragmentDefinition`, `HyperionWorkerDef`, `GatewayTreeItem`, `ScaleConfigs`, `AppMessage`, `StateModel`, `StdSignDoc`, `TrackItem`, `UserRef`, `IAuthenticatedHubSearchOptions`, `ComponentContext`, `MutableVector4d`, `DefaultTallyConfiguration`, `BodyType`, `IUsersRepository`, `Royalty`, `ElfSectionHeader`, `moment.Duration`, `InteractionForegroundService`, `DisplayNameOptions`, `BaseAction`, `CurveExtendMode`, `OutChatPacket`, `AnimationReference`, `FiatCurrency`, `PerformWriteArgs`, `InteractionState`, `TimeSection`, `SnapDB`, `IpPermission`, `BasicProps`, `MultiWord`, `tStringCurrencyUnits`, `GroupProps`, `ValidationState`, `Conv1D`, `SocketAddress`, `App.SetupModule`, `__SerdeContext`, `DateRange`, `requests.ListExternalDatabaseConnectorsRequest`, `IMatcherFunction`, `LabelDoc`, `monaco.editor.IModelDeltaDecoration`, `IDisposer`, `TeamMembershipProps`, `SMTFunction`, `D3Service`, `UpdateCustomVerificationEmailTemplateCommandInput`, `CertificateAuthorityLifecycleState`, `MockMember`, `IStateMachine`, `DeleteCampaignCommandInput`, `FaunaRef`, `SnapshotQuotaExceededFault`, `TocItem`, `FlowDocument`, `RefsDetails`, `tfc.io.ModelArtifacts`, `DescribeEngineDefaultParametersCommandInput`, `CSSVarFunction`, `NameValidationError`, `ProblemInfo`, `ModuleMetadata`, `NgForageOptions`, `IEmployee`, `ToastConfigCommon`, `CommandMap`, `IBundle`, `UnicodeBlock`, `PercentLengthType`, `StructuredStorageBaseHelperOptions`, `Counter1`, `QueryCreator`, `AnyEntity`, `StoryContext`, `USampler2DTerm`, `FileInfo`, `sdk.SpeechRecognizer`, `DetectorRecipeDetectorRule`, `TransformerFactory`, `Uint`, `CurrencyFractions`, `msRest.CompositeMapper`, `HookCallback`, `TKeyboardShortcutsMapReadOnly`, `CircleProps`, `FunctionDefinitionConfig`, `IconPosition`, `prng`, `TID`, `GalleryService`, `VdmActionImport`, `FlowPostFinally`, `CachedBuildRequestOptions`, `bitcoin.payments.Payment`, `ListFHIRExportJobsCommandInput`, `WebPhoneSession`, `CandidatePersonalQualitiesService`, `NavigateOptions`, `IPacketHeader`, `SearchProps`, `AbstractMaterialNode`, `coreClient.OperationSpec`, `GameEntityObject`, `SavedObjectsExportTransform`, `url.Url`, `RawMessage`, `FiniteIEnumerator`, `Contributors`, `Hierarchy`, `RnM2BufferView`, `DepthStyleProps`, `PanelActionParams`, `IEpisode`, `IPropertyListDescriptor`, `MergeItem`, `SizeResult`, `IAppointment`, `PageConfig`, `DeletePresetCommandInput`, `IIteratee`, `LazyExoticComponent`, `FMAT`, `SearchType`, `ITopic`, `BattleCommitment`, `fromUserActions.GetReviewersStatisticsCollection`, `Slide`, `ParsedFunctionJson`, `SlackMessageArgs`, `ImageSize`, `InterfaceName`, `DefaultTreeNode`, `PlayerType`, `NAVTestObject`, `BlueGreenManifests`, `MouseManager`, `VNodeProperties`, `ObservableVocabulary`, `PromiseWithProgress`, `PCLike`, `DeleteClusterResponse`, `interfaces.Newable`, `Models.LeaseAccessConditions`, `ZosAccessor`, `BufferState`, `NullableT`, `InteractionManager`, `sdk.ConversationTranslator`, `TypeDecorator`, `Lane4`, `IVector`, `StyleErrors`, `ListResult`, `ReleasesClient`, `ts.FunctionLikeDeclaration`, `ts.Type`, `RpcCallParameters`, `ModuleMock`, `messages.GherkinDocument`, `TransformMessage`, `LayerFromTo`, `HashHistoryManager`, `Category`, `VideoTileState`, `IFullItemState`, `BudgetSummary`, `BindingName`, `CustomSkill`, `Starter`, `MaybeProvider`, `Rope`, `TreeItemModel`, `PromiseDelegate`, `WriteConditionalHeadersValidator`, `ICommandBarItemProps`, `SignalListener`, `STMultiSort`, `ModuleName`, `IWarning`, `WaitContext`, `NotifyQueueStore`, `android.content.DialogInterface`, `CohortComposition`, `ts.Signature`, `ReadStream`, `JobExecution`, `ExecutionErrorProperties`, `TaskDefinition`, `PointSeriesColumn`, `TaskDraft`, `InvokeArgument`, `FSPath`, `Memoized`, `HsToastService`, `ClientGrpcProxy`, `TraceId`, `Fund`, `SignalingConn`, `GetInput`, `TranslationString`, `LoginComponent`, `Models.ModifiedAccessConditions`, `MergeEl`, `AlbumEntity`, `Chapter`, `ITagHandler`, `LogAnalyticsSourceMetadataField`, `RX.CommonProps`, `DataResolverOutputHook`, `Materialize.ChipDataObject`, `UserDeposit`, `Datastore.Transaction`, `LoadCallback`, `P2PEnhancedPeerInfo`, `EdgeImmut`, `AnySchemaObject`, `StackItem`, `ChainableTransform`, `IEventHandler`, `TilemapProject`, `SnapshotIn`, `NextService`, `StackInfo`, `Shorthand`, `AuctionViewItem`, `PossiblePromise`, `MdcSnackbarService`, `ACM`, `TabViewItem`, `ScriptDataService`, `CommandInput`, `ViewContainerPart`, `ReferenceNode`, `DelugeTorrent`, `KeyResultUpdate`, `Byte`, `ServiceContainerConfig`, `MerkleTree`, `HookEvent`, `Builders`, `GLintptr`, `d.HydrateDocumentOptions`, `Bridge`, `NotificationInfo`, `ValidationArguments`, `BindingInputBase`, `P2PRequestPacket`, `FlowAssignmentAlias`, `ts.ExpressionWithTypeArguments`, `DeleteRepositoryPolicyCommandInput`, `CalendarFieldsOptions`, `DaffCategoryFilter`, `DocumentUri`, `MatchInfo`, `ListenerFunction`, `MTD`, `Target`, `StyleManagerService`, `FeatureService`, `Agreement`, `ScaleTime`, `ConvexPolygon2d`, `FileOptions`, `OpenSearchClient`, `HMACKey`, `Learnset`, `TemplateParameter`, `EventBody`, `FormElement`, `MyDirectoryTree`, `Species`, `AudioModule`, `NetworkDiff`, `CliManipulator`, `RelativePlaceAnchor`, `StringifyOptions`, `LegacyOpenSearchError`, `ParserRuleContext`, `Arguments`, `RuleObject`, `RequestApprovalService`, `IDynoCollectionKeyValue`, `GitFileChange`, `HTMLElement`, `Stop`, `FormConfigProps`, `TypeScriptConfigurationBuilder`, `IMP4AudioSampleEntry`, `ServiceDownloadProvider`, `PlayerViewState`, `RiskViewEntry`, `InvalidParameterCombinationException`, `ThingView`, `PhysicsCollider`, `TooltipOperatorMenu`, `ReturnTypes`, `BridgeProtocol`, `SelectInfo`, `TinaFieldInner`, `CSSStyleRule`, `ColorInput`, `Utils`, `HeaderBag`, `ArraySchema`, `ChainInfoWithEmbed`, `AppStateTree`, `QueryResolvers.Resolvers`, `ErrorUtilitiesService`, `IHooks`, `SeparableConv2D`, `GraphQLEnumValueConfigMap`, `CanvasDepth`, `Locales`, `CacheAdapter`, `Coupon`, `CheckerResult`, `GunMsgCb`, `TestClass`, `BrowserNode`, `CustomRequest`, `ListJobsResponse`, `BrandModuleBase`, `DebugProtocol.Message`, `CodeQualityInformation`, `CreateOperation`, `RumPerformanceResourceTiming`, `WebGLCoreQuadOperation`, `ts.ImportSpecifier`, `TestChannel`, `CaseItem`, `BitMap`, `ReconnectingWebsocket`, `IReducers`, `PaperSource`, `SourceInformation`, `DeviceSelector`, `LiteloaderVersion`, `INorm`, `DateWidget`, `DialogData`, `IArmy`, `ContainerRuntime`, `GUITheme`, `ModbusConnection`, `UnidirectionalTransferAppAction`, `IProjectMetadata`, `IAccountDataStore`, `CLM.AppBase`, `TypographStyle`, `UserAgent`, `QueryDeploymentsRequest`, `PhysicalTextureType`, `SaveDialogReturnValue`, `vscode.DebugAdapterExecutable`, `IStep`, `SchemaDifference`, `DaffProductDriverResponse`, `DecodingTransformer`, `V1ExpressionModel`, `CompletionItemKind`, `FBSDKSharing`, `Angulartics2GoogleAnalytics`, `RectangleNode`, `NetworkInfo`, `DitherKernel`, `WeakGenerativeCache`, `ICached`, `QualityLevel`, `ProofRequest`, `NotificationsService`, `Def`, `Dispatched`, `WlDocs`, `Database.User`, `GasTokenValidator`, `ReadonlyVec2`, `GT`, `angular.IWindowService`, `ConnectionDataEnvelope`, `DirType`, `IDeploymentCenterPublishingContext`, `FieldElement`, `NonArpeggiate`, `ClassFacts`, `PermissionItem`, `OutputTargetDocsJson`, `SFCBlock`, `LongHeader`, `DatabasePool`, `IdentityIndex`, `IndexType`, `IPartitionLambdaConfig`, `ResourceNotFoundFault`, `CalendarType`, `IListFormResult`, `PointerOverEvent`, `MultiLineStringDataVariant`, `ContactEmail`, `NoInputAndOutputCommandInput`, `TaskExecution`, `ExtendedClient`, `PGTransform`, `UnknownError`, `ControlInterface`, `TimeOpStatementContext`, `SidebarMenuItem`, `NetworkRequestInfo`, `IntermediateToken`, `ResourceLimitExceededException`, `GenericComboBoxProps`, `Traversable2`, `PluginFunction`, `IConsoleResponse`, `I18nService`, `IArtTextCacheData`, `ModifyDBParameterGroupCommandInput`, `requests.UpdateConnectionRequest`, `IBaseTransaction`, `NetconfForm`, `FalsyPipe`, `InitStoreState`, `Matrix2D`, `Service$`, `ModuleBase`, `UserMembership`, `ConverterContext.Types`, `OutgoingSSNResetRequestParam`, `ConvertComponent`, `DateRangeValuesModel`, `DaffCartReducerState`, `ThemeGetter`, `AnimationEvent_2`, `R.Morphism`, `PipelineResult`, `SupRuntime.Player`, `ConversionResult`, `GetUserInfoSuccessCallbackResult`, `HttpContextConstructorContract`, `UpdateDataSourceCommandInput`, `PositionalArgument`, `MentionDefaultDataItem`, `QuakemlService`, `RGBAColor`, `GeoInput`, `DefaultAnchors`, `IFieldProps`, `RendererStyleFlags2`, `GetConnection`, `HTMLIonRadioElement`, `FormState`, `StoredTransaction`, `SearchOptionModel`, `LoggerInterface`, `CTransactionSegWit`, `FirmaWalletService`, `MockAdapter`, `MongoDB.Filter`, `BulkApplyResourceAction`, `MDCTabScrollerAdapter`, `ArtifactFilePaths`, `config.Data`, `Refinement`, `GroupedRequests`, `ListResourcesCommandInput`, `KeyModifierModel`, `Subst`, `TransformOptions`, `SpacesServiceStart`, `TransmartSubSelectionConstraint`, `CID`, `CurrentHub`, `Color4`, `AppNotification`, `IApiOperation`, `DeveloperExamplesPlugin`, `TransportEvent`, `FieldBase`, `ExtensionManager`, `ParsedArgs`, `BullBoardQueues`, `PlayerContext`, `SettingsContextProps`, `TxHash`, `ethers.Contract`, `guildInterface`, `SearchDetails`, `PartnersState`, `Cypress.ObjectLike`, `GetJobResponse`, `GX.TevScale`, `IElem`, `UnitHelper`, `LocalStorageAppenderConfiguration`, `DirResult`, `MeetingAdapterState`, `FleetStartServices`, `KeyedTemplate`, `B16`, `Heater`, `Breakpoint`, `QuestionDotToken`, `TiledObject`, `GlobalLogger`, `IMatches`, `DataViewHierarchy`, `Doctor`, `NEOONEProvider`, `Dungeon`, `TmdbMovieDetails`, `GToasterOptions`, `NgxGalleryOptions`, `StackHeaderInterpolationProps`, `LanguageOption`, `ResourceIdentifier`, `PutScalingPolicyCommandInput`, `DP`, `PromptType`, `turfHelpers.Feature`, `AlertingAuthorization`, `WorkerFunction`, `WizardStep`, `IWireMessage`, `ResourceReturn`, `MetadataError`, `Indexer`, `SpeechRecognitionResult`, `AsyncIterable`, `VideoListQueryDto`, `ThrottlingException`, `TFLiteWebModelRunner`, `IApplicationHealthStateFilter`, `ClientError`, `VoiceFocusSpec`, `ComponentHTTPClient`, `ALong`, `PreprocessingData`, `protocol.FileRequestArgs`, `TextEditorDecorationType`, `OpenChannelEvent`, `UrlConfig`, `HeadConfig`, `EventQueueItem`, `Int8`, `ItemT`, `FunctionObject`, `BentleyCloudRpcParams`, `CssToken`, `vscode.FormattingOptions`, `OpenEdgeConfig`, `PatchResult`, `messages.FeatureChild`, `AudioContext`, `StoreST`, `ARecord`, `DeleteVolumeCommandInput`, `KubeContext`, `ITimeOffPolicy`, `GaxiosOptions`, `BindingDirection`, `UserInterface`, `StorageInfo`, `ViewService`, `FSNode`, `StepBinding`, `DirectionConstant`, `DragactLayoutItem`, `DeleteUserRequest`, `SelectableValue`, `KeyValue`, `JsonDocsMethodReturn`, `DataSourceItemGroup`, `JwtKeyMapping`, `MouseEventInit`, `socketIo.Socket`, `EdgeConfig`, `CustomControlItem`, `ComboTree`, `Darknode`, `CppBuildTask`, `Diff`, `TradeContext`, `AuxPartition`, `EntitySchema`, `TemporalArgs`, `NzNotificationRef`, `AssetMap`, `Pet`, `HardwareConfiguration`, `NodeID`, `GlimmerAnalyzer`, `Security`, `ParentContexts`, `cc.Button`, `AlertExecutorOptions`, `IndexedPolyfaceVisitor`, `SqrlConstantSlot`, `ArrayBufferReference`, `requests.ListUserAssessmentsRequest`, `TwitchChatMock`, `requests.ListComputeCapacityReservationsRequest`, `Initialized`, `DueReturn`, `NetworkKeys`, `SpeechGenerator`, `MatchingFunc`, `d.ConfigFlags`, `Output`, `RuntimeTransaction`, `IntentSchema`, `Configurations`, `Timezone`, `TranspileResult`, `Edit`, `ClusterService`, `FileWatcherCallback`, `Nil`, `types.CodeError`, `WWAData`, `PAT0`, `XhrRequest`, `NavigatorGamepad`, `ISideEffectsPayload`, `GX.TexFormat`, `DropEvent`, `ESLToggleable`, `IRealtimeEdit`, `ConceptTypeDecl`, `Reply`, `ClickEvent`, `CoreTheme`, `MultilineTextLayout`, `OrderDetailService`, `Production`, `IAuthOptions`, `ILog`, `Bar`, `PairSet`, `NodeChildAssociationEntry`, `ItemEventData`, `CodeEditor.IEditor`, `IntegrationCalendar`, `PopupComponent`, `ContractDefinitionContext`, `LocationStrategy`, `TKeyArgs`, `SlotStatus`, `IdeaId`, `IsInstance`, `DBQuery`, `InputDataConfig`, `Config.Path`, `ContentNode`, `UIAnalytics`, `StringContext`, `ISpecialStory`, `AllocationUpdatedArg`, `DataTable.Column`, `IGitProgressInfo`, `CharSet`, `CursorPopupInfo`, `UnsupportedBrowsers`, `ConnectionDetails`, `IQuery`, `RustPanic`, `UtilService`, `PDFContentStream`, `MatIconRegistry`, `DownloadJob`, `JoinMode`, `AbstractContract`, `ITerminalContext`, `LifecycleRule`, `thrift.TList`, `BMDData`, `selectorParser.Node`, `RouteCache`, `GenericModel`, `CanvasLayerModel`, `JQueryStatic`, `Yoga.YogaNode`, `PdbStatusDetails`, `IChannelState`, `PathState`, `WorkspaceFolderContext`, `ModelConstructorInterface`, `SendPropValue`, `IConfirmedTransaction`, `AttrMap`, `PolylineProps`, `CompoundStatementListContext`, `JupyterLabPlugin`, `cpptools.Client`, `FakeShadowsocksServer`, `CodeChangedEvent`, `InternalOpExecutor`, `RPCPayload`, `IExportFormat`, `DescribeImageVersionCommandInput`, `TokenAddressMap`, `BookStoreService`, `ex.PreCollisionEvent`, `ParamsSpec`, `CreateDBClusterSnapshotCommandInput`, `RegisterX86`, `AreaNode`, `TaskCacheSession`, `OmvFilterDescription`, `AppResourcesModel`, `ApplicationGateway`, `DiagnosticSink`, `PutItemInput`, `MockDeviceManager`, `SharedArrayBuffer`, `BaseHistory`, `Aspects`, `Environment`, `TinaCloudCollectionEnriched`, `DomModule`, `MultiKeyStoreInfoWithSelectedElem`, `TransactionOrKnex`, `SocialSharing`, `Overlord`, `CreateDBClusterEndpointCommandInput`, `Screenshot`, `AxisConfig`, `UserMetadata`, `UIViewController`, `RemovePermissionCommandInput`, `SitemapXmpOpts`, `RDQuery`, `ExchangePriceService`, `IoLog`, `FinalizeHandler`, `WebSocketSubject`, `DropTargetSpec`, `Intl.NumberFormatPart`, `NzNoAnimationDirective`, `DropViewNode`, `CircleModel`, `OrganizationalUnitResource`, `GfxInputStateP_GL`, `BSPNode`, `BlockMarketCategory`, `AwsS3PutObjectOptions`, `XNA_Texture2D`, `ProtocolExecutionFlow`, `LuaDebug`, `VRMFirstPerson`, `OpenSearchDashboardsReactPlugin`, `TokenContext`, `IGenericObject`, `KeyConnectorService`, `VideoSource`, `TilePath`, `UserResponse`, `BuildingColorTheme`, `Multiplexer`, `JsonDiffNode`, `ConditionalTransferUnlockedEventData`, `ShaderProgram`, `NoteContent`, `Mat`, `BulletOption`, `ComponentDocument`, `NodeInjectorFactory`, `CalendarUnit`, `WorkerTestHarness`, `ModifierType`, `CounterDriver`, `XAudioBuffer`, `NavigationProvider`, `PlannedOrganizationalUnit`, `ValidationChain`, `YieldEveryOptions`, `PointerPosition`, `UploadInfo`, `ComponentInfo`, `IWorkflowExecuteAdditionalData`, `ContractPrincipalCV`, `ImportRules`, `types.FormatTransfer`, `ContractCallResults`, `FabricSmartContractDefinition`, `HdBitcoinCashPaymentsConfig`, `GnosisSafeContract`, `JPACVersion`, `DaffCartTotal`, `TransactionBase`, `PredicateModel`, `MilkdownPlugin`, `OptionsMap`, `CommunOptions`, `PropsFromRedux`, `ApiTypes.Feed.Like`, `AngularFireObject`, `PoolData`, `SendableMsgBody`, `MatchingRoute`, `DescribeReplicationInstancesCommandInput`, `App.Context`, `DeviceManagerState`, `ListTagsForResourceCommandOutput`, `RRect`, `IsolationStrategy`, `ParamDef`, `IDataFilterResult`, `Field_Group`, `ShareButtonsConfig`, `amqplib.Options.Publish`, `CategoryItem`, `ComponentServer`, `EditorEvent`, `DeleteUserCommand`, `JsonPath.ExpressionNode`, `MainProps`, `RpcClient`, `BackupDestinationDetails`, `NodeEventTypes`, `MissingError`, `CreateMigrationDetails`, `MinimalViewPortConfig`, `StudioModelData`, `ListProjectsCommandOutput`, `VariableDeclarator`, `SMTExp`, `ProofMateItem`, `NodeType`, `DataConvertType`, `ThyPopover`, `Hideable`, `CellProps`, `IServerModel`, `IPersistence`, `Neovim`, `TestStateBase`, `PolicyResult`, `requests.ListInstanceagentAvailablePluginsRequest`, `MyState`, `IProcedure`, `ExpNumBop`, `HsSensorUnit`, `DeploymentTable`, `IdentityMap`, `HandlerContext`, `Ok`, `MetaverseService`, `TensorListMap`, `TEntityRecord`, `WithItemNode`, `InputManager`, `NumberNodeParams`, `InMenuEvent`, `ConstantBackoff`, `NoopExporter`, `RulesetVariable`, `TimelinePoint`, `ConfigureLogsCommandInput`, `angular.IPromise`, `t.CallExpression`, `ComponentLoaderFactory`, `GetPropertiesResponse`, `CommandConfig`, `JassTimer`, `ExtremaOptions`, `BindGroupLayout`, `AbiItemModel`, `IExtensionActivationResult`, `ClassStruct`, `ModelLifecycleState`, `AliasHierarchyVisitor`, `WsHttpService`, `PageBuilderContextObject`, `Attributions`, `IValidatorConfig`, `JSXElementAnalysis`, `L13Element`, `IconInfo`, `Transaction.Info`, `UpgradePlugin`, `Comp`, `HttpRequest`, `cdk.GetContextValueResult`, `ICategoryBin`, `AndroidAction`, `DangerResults`, `TextEdit`, `RewardTicket`, `ObjectTypeDefinitionNode`, `AssertTrue`, `CallbackFunction`, `MDCChipActionAttributes`, `MatchedRoute`, `TextDelta`, `ITransport`, `GreenBean`, `DocumentSettings`, `Message`, `ClientSocket`, `SignatureProvider`, `SpecialKeyMatchResult`, `HTMLSourceElement`, `CreateGroupCommand`, `specificity.Specificity`, `RoleState`, `TypeWithInfo`, `Start`, `MeshData`, `ChatThreadClientState`, `LimitItem`, `Direction`, `IConnections`, `FormatCodeOptions`, `CdsInternalOverlay`, `ScriptLikeTypes`, `Fork.Fork`, `WebKitEntry`, `ApplicationStateMeta`, `ReBond`, `ConceptServer`, `WebGLSampler`, `NoOpStep`, `EntireGame`, `amqplib.ConfirmChannel`, `SlackOptions`, `IFunctionIdentifier`, `RegisterParams`, `Renderer2`, `IOriginNode`, `d3Selection.Selection`, `AnalyticsProperties`, `RepoNameType`, `CategorySummary`, `MultiMap`, `InfiniteScrollDirective`, `JSONCacheNode`, `Drawable`, `ScalarCriteriaNode`, `VulnerabilityAssessmentPolicyBaselineName`, `SourceNodesArgs`, `iam.Role`, `PDFCrossRefStream`, `CheckSearchSessionsDeps`, `AsyncArrayCallback`, `DefaultReq`, `Level3`, `XMenuNode`, `G6Event`, `CommentKind`, `VariantHandler`, `MethodDocumentationBlock`, `Outline`, `Ref`, `VariableExpression`, `WKNavigation`, `WriteValueOptions`, `BodyAndHeaders`, `SEErrorRefresh`, `BillDebtor`, `ServiceSpy`, `InternalCoreSetup`, `FeeOption`, `TreeModelSource`, `CarouselConfig`, `EngineResponse`, `WorldCoordinates`, `SystemIconProps`, `Crdp.Runtime.StackTrace`, `ParseQueryOutput`, `BitbucketUserRepository`, `NetworkDefinition`, `ScheduledCommandInfo`, `CoingeckoApiInterface`, `SeriesConfig`, `ExtrudedPolygonTechnique`, `SearchableContainerInput`, `LoggerProxy`, `RLYTTextureMatrix`, `TaskQueue`, `REPLServer`, `NormalizedVertex`, `Expression`, `StateLeaf`, `AxiosResponse`, `TextEditorSelectionChangeEvent`, `LucidModel`, `PutRetentionPolicyCommandInput`, `UpdateTargetDetectorRecipe`, `PositionContext`, `TrackerEvent`, `mod.TargetGroup`, `messages.Feature`, `BlockAtom`, `StructureRoad`, `HapiAdapter`, `AnyCurve`, `TrackedImportFrom`, `MessageData`, `TransmartDimension`, `ElMessageBoxOptions`, `ThyTableColumnComponent`, `FoamGraph`, `ApiProxy`, `Contracts`, `FoldersService`, `SvgIconProps`, `IDistro`, `StoreView`, `AvatarOverload`, `skate.Component`, `SelectProps`, `VoilaGridStackPanel`, `Interval`, `requests.GetWorkRequestRequest`, `PointInfo`, `ActionEvent`, `UseLazyQueryReducerAction`, `IDSLCodeState`, `CellDrag`, `PrivilegeFormCalculator`, `IdQuery`, `TypeConsApp`, `ShadowController`, `MeaningfulDependency`, `CreateObservableOptions`, `Line2`, `MockStream`, `ReduxAppState`, `AttrEvaluationContext`, `StateAction`, `SqlManagementClient`, `ExtUser`, `http.OutgoingHttpHeaders`, `TestViewController`, `ProjectDto`, `VCSConnector`, `TScheduleData`, `AggParamsAction`, `MediaStreamAudioSourceNode`, `XYZNumberValues`, `CaseNode`, `AuthPermissions`, `ILogService`, `com.google.firebase.firestore.FirebaseFirestoreException`, `MenuApiResult`, `KeystrokeAction`, `RelationClassDecorator`, `GrpcResponseMessageData`, `TemplateChildNode`, `ElementProperty`, `VideoPlayer`, `ILayerDefinition`, `requests.ListDedicatedVmHostsRequest`, `HeadingSize`, `ProofCommand`, `TodoState`, `DMMFPAS_Directives`, `InsertDelta`, `SpyTransport`, `Base64`, `PersonService`, `ValueToken`, `Polygon`, `Shell`, `PathStyleProps`, `IGetContentOptions`, `ISettingsState`, `RLYTPaneBase`, `DataTypeFieldConfig`, `IBaseImageryPluginConstructor`, `IPluginOptions`, `MachinomyOptions`, `TemplateState`, `TokensBuffer`, `ToplevelT`, `SwitchStatement`, `CalendarData`, `HitDatabaseEntry`, `Table`, `LatestControllerConfigType`, `CropperTouch`, `ChatErrorTarget`, `CallbackDisposable`, `IColorableSequence`, `NotifyOpts`, `HSLColor`, `AWSLambda.Context`, `MetricResult`, `requests.ListIPSecConnectionTunnelRoutesRequest`, `ContractDefinition`, `commonLib.IExtra`, `Directive`, `AuthScopeValues`, `ReactRef`, `IDateRange`, `config`, `SpeakerInfo`, `FileAccessData`, `MatDialogConfig`, `Pipette`, `ITestFluidObject`, `EventInitDict`, `IComputedValue`, `DialogInput`, `IMarkerData`, `UnitType`, `Texture_t`, `Badge`, `TransformFactoryContext`, `DaffPaypalReducerState`, `UseTransactionQuery`, `Inspection`, `KeyHandler`, `UiLanguage`, `GX.CullMode`, `AsyncThunkPayloadCreator`, `PartialBot`, `CopyTranslateResult`, `ProjectInformation`, `ITionPlatformConfig`, `DecodedSignature`, `ModalManager`, `Agency`, `NamedImports`, `AllPackages`, `LocationReference`, `BackstageItemState`, `IDataObject`, `BrandService`, `DeleteInstanceCommandInput`, `Allure`, `PipelineStageUnitAction`, `LexContext`, `OfficeFunction`, `EvalResponse`, `RowFormatter`, `ThemeName`, `EmusakEmulatorsKind`, `ContractAddressOrInstance`, `IOdspAuthRequestInfo`, `TextureId`, `Tensor4D`, `NavigationLocation`, `StorefrontApiContext`, `IClothingStore`, `RouteDependencies`, `ISettingsDataStorePayload`, `StorageContainer`, `IApiInfo`, `DeleteParameterGroupCommandInput`, `RadixTreeNode`, `ISelEnv`, `MacroHandler`, `TargetGroup`, `TimelineKeyframeStyle`, `OAuthTokenResponse`, `NumberContext`, `ExpressLikeRequest`, `NetworkFilter`, `DescribeAutoScalingGroupsCommandInput`, `ImageEffectDirector`, `DictionaryKeyEntryNode`, `StructResult`, `LogMatchRule`, `DocumentMigrator`, `SavedObjectsService`, `RequestBuilder`, `HSD_TECnst`, `DesignedState`, `FacadeConverter`, `MockedRequest`, `Levels`, `Http`, `TTypeName`, `NavigateFunction`, `d.MsgToWorker`, `ScriptCache`, `GitHub`, `NodeSnapshot`, `QueryOpts`, `IMenuState`, `MDCTextFieldOutlineAdapter`, `PartSymbol`, `BasicScene`, `BitcoinishPaymentTx`, `AstExprState`, `RootDispatch`, `types.NestedCSSProperties`, `ReadModelRequestEnvelope`, `TemplateClient`, `BackupSummary`, `ValidateFn`, `MgtTemplateProps`, `ObjectValue`, `WorkflowStatus`, `SuitDone`, `FileEntity`, `SwapParams`, `EffectHandlers`, `NodeContainer`, `requests.ListCrossconnectPortSpeedShapesRequest`, `AnnotationRectProps`, `MarkerDoc`, `IWalletContractServiceStrategy`, `IPackageJson`, `ThyTooltipDirective`, `OutputTargetDistCustomElementsBundle`, `IParsedPackageNameOrError`, `Directories`, `IWorldObject`, `SynthesisVoice`, `requests.ListIPSecConnectionTunnelsRequest`, `CdkToolkit`, `DynamicEllipseDrawerService`, `KeyboardDefinitionSchema`, `CursorDirection`, `PreviewDataImage`, `TreeNodeInBlock`, `FoodsFilter`, `IInspectorListItem`, `UpdateChanges`, `EitherAsync`, `ParamContext`, `ZonesManager`, `ServerStyleSheets`, `StripePaymentSession`, `FolderPreferenceProvider`, `Break`, `DraggableInfo`, `TypedColor`, `webpack.Compilation`, `FieldNamePath`, `OrganizationPostData`, `RequestPolicy`, `ProviderResult`, `SprottyDiagramIdentifier`, `TransliterationFlashcardFieldName`, `Types.SocPromise`, `Answer`, `PiInstance`, `ts.CompilerHost`, `OutlineCreateTag`, `LitecoinAddressFormat`, `AudioResource`, `IFunctionIndex`, `Services`, `NotificationsState`, `FallbackProps`, `IRelatedEntities`, `BootJsonData`, `NamedTensor`, `BatchWriteRequest`, `DecoderOptions`, `RouteInfo`, `NativeCallback`, `MenuPositionY`, `ThumborMapper`, `IERC20ServiceInterface`, `MigrateOptions`, `PutPublicAccessBlockCommandInput`, `TypeWithId`, `MalType`, `ITexture`, `TheTask`, `Sender`, `MetricModalProps`, `JsonRpcResponse`, `W4`, `TokenEndpointResponse`, `WorkflowMap`, `CreatePhotoDto`, `React.TransitionEvent`, `KeyResultTemplate`, `BranchInfo`, `ComponentCompilerPropertyComplexType`, `ts.CallExpression`, `CreatedTheme`, `SectionModel`, `Yaz0DecompressorWASM`, `requests.ListSecretBundleVersionsRequest`, `IUserProfileViewState`, `Database.Replica`, `ConfirmProps`, `ActionService`, `FunctionSignature`, `LogAnalyticsParserFunction`, `LoginAccountsValidationResult`, `LegendEntry`, `Quadrant`, `perftools.profiles.IProfile`, `PositionTranslate`, `iI18nConf`, `BinaryShape`, `AType`, `ResourceFile`, `SaveManager`, `serializedNodeWithId`, `UrlState`, `Int64Value`, `Warrior`, `XYChartScrollbar`, `Headers`, `IUILayoutViewController`, `Field.PatchArgs`, `EventTouch`, `AuthorizationPayload`, `LayoutComponent`, `ListPolicyVersionsCommandInput`, `Range1d`, `MotionInstance`, `TransformerHandle`, `OrderedSet`, `PackageEntry`, `ICandidateCreateInput`, `ToolbarItemsManager`, `TimefilterContract`, `ConsumerExtInfo`, `AddressBook`, `GitHubRepo`, `BlendOperation`, `ITransactionRequestConfig`, `IncompleteSubtypeInfo`, `SortedPatchList`, `TypeResolvingContext`, `NetworkRequestId`, `TreeDiagramNode`, `SensorType`, `ConvoState`, `InfoType`, `IServerFS`, `InputEventMouseMotion`, `SyntaxModifier`, `TKeys`, `CdsButton`, `DATA`, `cToken`, `LiteralType`, `TextContextTypeConvert`, `UseContextStore`, `CustomSecurityService`, `EmojiType`, `GridCellBox`, `ResponseData`, `Render`, `ContainerWarning`, `TSettings`, `SwapFn`, `GX.CA`, `PromiseOr`, `yauzl.Entry`, `DaffProductFactory`, `StructDeclaration`, `RTCRtpSimulcastParameters`, `VectorLike`, `AuthReducerState`, `next.Origin`, `Suggestion`, `InetLocation`, `IGLTF`, `TileContentRequestProps`, `code.Range`, `NgmslibService`, `SagaGenerator`, `listenerHandler`, `ClassDescription`, `NativeClarityBinProvider`, `PIXI.Point`, `MiddlewareResultFactory`, `StringAsciiCV`, `PinModelData`, `GX.IndTexStageID`, `ServiceResponse`, `Int`, `ParticipantInfo`, `Cli`, `LeftCenterRight`, `FormFieldProps`, `StyleSheetData`, `IPumpjack`, `apiClient.APIClient`, `BuildVariables`, `IFileRequest`, `ChannelPresenceEvent`, `ValueKey`, `SearchServiceSetupDependencies`, `angular.ui.IStateParamsService`, `ZenObservable.Observer`, `MapObjectAdapter`, `VertexBuffer`, `DeleteArchiveCommandInput`, `INpmDependency`, `ColorRgb`, `ApiKeyHandler`, `DebugProtocol.NextResponse`, `ApiDeclaration`, `TransationMessageOrObject`, `api.ISummaryTree`, `ClarityValue`, `ts.BuilderProgram`, `BuildrootUpdateSession`, `NgModuleMetadata`, `SpeciesName`, `HostWithPathOperationCommandInput`, `EnumId`, `StreamableRowPromise`, `LabDirectory`, `SignatureProviderResponseEnvelope`, `AMapService`, `INote`, `ToneOscillatorType`, `CorsOptions`, `GfxSampler`, `IDatabaseApiOptions`, `NativeError`, `IDBPObjectStore`, `TileMapAssetPub`, `ScreenViewport`, `ComplexError`, `ElementContent`, `IDatabaseDataDocument`, `DartDeclarationBlock`, `CandidateFeedbacksService`, `ParamInfoType`, `TicketsState`, `monaco.languages.FormattingOptions`, `SpanContext`, `Events.stop`, `BufferCV`, `ARRotation`, `MDCChipAnimation`, `TSTypeAnnotation`, `MPPointF`, `IPersona`, `CreateDeliverabilityTestReportCommandInput`, `MaskModel`, `IUserOptions`, `IBeaconConfig`, `TexMtx`, `Month`, `TodoTask`, `XmppChatConnectionService`, `DependencyContainer`, `SpaceProps`, `DispatchedAction`, `DocumentPosition`, `DayPeriod`, `EdgeCalculatorHelper`, `ListAssetsCommandInput`, `ReadState`, `Funnel`, `Types.KeyValue`, `CompatibleValue`, `LayoutParams`, `TimeHistory`, `EditableBlock`, `FriendList`, `EventSink`, `TRecursiveCss`, `AvatarService`, `Mutation`, `ILocalizationFile`, `IExcludedRectangle`, `RequestResponseLog`, `ICellData`, `CompilerSystemCreateDirectoryResults`, `LifecyclePolicy`, `LotTypeOption`, `HashEntry`, `SSRMiddleware`, `ThrottlerHelper`, `Tsoa.Metadata`, `HTMLChar`, `CustomQueryModel`, `MultilevelSensorCCReport`, `BinaryType`, `requests.ListDbHomePatchHistoryEntriesRequest`, `IProcessedStyleSet`, `ProviderRange`, `MockPlatform`, `TestFileInfo`, `IFakeFillerOptions`, `StoreOptions`, `PositionDirection`, `DeleteRepositoryCommandInput`, `NodeDecryptionMaterial`, `StringTokenFlags`, `TestMessage`, `AppStackOs`, `SeekProcessor`, `ArgumentInfo`, `ArtifactFrom`, `PixelMapTile`, `HTMLScriptElement`, `OperationMetadata`, `ControlSetItem`, `DIDDocument`, `NodeInputs`, `Node_Struct`, `FlowVariableAnnotation`, `TransactionEnvelope`, `SDLValidationContext`, `ListRetainedMessagesCommandInput`, `ALL_POSSIBLE_CHART_TABS`, `ControllerValidateResult`, `OffersState`, `PairTree`, `EndUserAgreementService`, `SimplePath`, `ValidatedOptions`, `requests.GetRRSetRequest`, `ApmFields`, `LabelCollector`, `ChildExecutor`, `ItemsOwner`, `SelectionsBackup`, `PartialReadonlyContractAbi`, `IWorkerChannelMessage`, `MessageDoc`, `ts.ResolvedModuleFull`, `GraphData`, `NominalTypeSignature`, `TextRangeWithKind`, `FileStorage`, `CoreProcessorOptions`, `PubKey`, `MDNav`, `ScannedMethod`, `ExportedData`, `FabricEnvironmentTreeItem`, `ReadableStreamDefaultController`, `TypeVarScopeId`, `VideoGalleryRemoteParticipant`, `KBN_FIELD_TYPES`, `CoinHostInfo`, `INodeMap`, `UISession`, `PoiTableEntryDef`, `CompilerWatcher`, `PerpMarketInfo`, `ControlType`, `AuthActionTypes`, `StagePanelLocation`, `ParsedResult`, `SavedObjectsMappingProperties`, `Compilation`, `LocaleTree`, `CreateDatasetGroupCommandInput`, `DidactPanel`, `PDFStream`, `Fees`, `EventDoc`, `ISearchDataTemplate`, `CriteriaFilter`, `VpnClientParameters`, `AccountRepositoryLoginResponseLogged_in_user`, `ExchangeContract`, `PNLeaf`, `QueryCommandOutput`, `MatchedSelector`, `PositionLimitOrderID`, `BandcampSearchResult`, `VNodeChild`, `Bytes`, `Field`, `Secured`, `DeleteIntegrationCommandInput`, `CanvasFontSizes`, `ICeloTransaction`, `SelectSeriesHandlerParams`, `d.VNode`, `VisiterStore`, `React.FocusEvent`, `ColdObservable`, `InternalStores`, `WidgetResolveResult`, `SentenceNode`, `RouterConfig`, `ko.Observable`, `CourseStore`, `ExecutableCallRegular`, `Suggester`, `pxtc.ExtensionInfo`, `Cubemap`, `AsyncOrderedHierarchyIterable`, `TestIntegerIterator`, `IPanelProps`, `GltfPreviewPanelInfo`, `CookieOptions`, `RelayerTypes.PayloadEvent`, `ColorLike`, `ITransitionActions`, `ElementStyle`, `AutoUVBox`, `CoursesService`, `ISiteState`, `ChannelHandler`, `OneHotVector`, `ApiError`, `RailsWorkspace`, `HighlighterCellsProps`, `RelationModel`, `MustacheFile`, `IBrowsers`, `PaymentState`, `WebsocketRequestBaseI`, `Measure`, `StateData`, `HashSetStructure`, `TokenSigner`, `DateFilter`, `EventDecorator`, `UnparseIterator`, `ODataSchema`, `Dim`, `DSTInfo`, `Snapshots`, `SqrlParserState`, `VideoDetails`, `AccessTokenInterface`, `PartialGestureState`, `requests.ListAppCatalogSubscriptionsRequest`, `TkmLogger`, `TinyCallContext`, `UpdateExpression`, `FontMetrics`, `CPoolSwap`, `Type_AnyPointer_Parameter`, `MakeHookTestStep`, `License`, `SavedObjectsBaseOptions`, `MessageAttributeValue`, `UnaryFunction`, `CommandOptions`, `VSCodeBlockchainOutputAdapter`, `MatchJoin`, `InstanceKey`, `GitHubRepositoryModel`, `BRepGeometryFunction`, `UseBodilessOverrides`, `BuilderRuntimeNode`, `AstNodeMerger`, `EsmpackOptions`, `android.os.Bundle`, `ConsoleInterface`, `sinon.SinonStatic`, `RpcProgram`, `MapDispatchToPropsParam`, `BriefcaseDbArg`, `SequelizeOptions`, `CreateBotVersionCommandInput`, `DialogPropertySyncItem`, `TextStylePropsPart`, `IWaveFormat`, `MakeRequest`, `SModelRootSchema`, `OperationMethod`, `MIREntityType`, `StandardResponse`, `PropertyASTNode`, `Size`, `SavedObjectsBulkResponse`, `SankeyDiagramNode`, `PDFOperator`, `NzIconService`, `ProjectedXYArray`, `QuestionService`, `ThemeSpec`, `WithName`, `TimesliceMaskConfig`, `BasicRoller`, `Spy`, `TSESTree.Node`, `RedisCommand`, `BusinessAccount`, `SFATexture`, `BoxVo`, `EventSourceHash`, `SlashCreator`, `$N.NeighborEntry`, `CartItem`, `Checksum`, `core.App`, `PiProjection`, `Provider`, `ScannedImport`, `CategorizedOption`, `Interface`, `ArgumentContext`, `IAuthor`, `Appointments.AppointmentProps`, `CmsStructureConfig`, `RemoveGroupControlAction`, `BaseEventOrig`, `UserContext`, `WebAppStack`, `IModelOptions`, `ApiDefinitions`, `SectionItem`, `BirdCount`, `VisualizationProps`, `BinarySensorCCAPI`, `OrderedMap`, `UniqueNameGenerator`, `MigrateFunctionsObject`, `ContentRect`, `d.EntryModule`, `ChatPlugContext`, `FieldAgg`, `Triplet`, `YearProgressService`, `TaskType`, `item`, `CircleResponderModel`, `FormatterSpec`, `FetchedPrices`, `IPCResult`, `StorexHubApi_v0`, `Board`, `LockedGoldInstance`, `EnumHelper`, `SystemMouseCursor`, `GX.TexFilter`, `DebugProtocol.PauseResponse`, `CompilationResult`, `IssueSummary`, `Inner`, `MlRouteProps`, `ContextBinding`, `PutAccountsValidationResult`, `PopulatedFolderDoc`, `FaceletT`, `BatchSerialization`, `PokerHandResult`, `PluginNamingConfiguration`, `RecursiveXmlShapesCommandInput`, `MachineParseResult`, `Rx.Subject`, `TspClient`, `InputParallelism`, `StringAnyMap`, `DAL.DEVICE_ID_LIGHT_SENSOR`, `LoadStrategy`, `cg.Role`, `HealingValue`, `PLSQLSymbol`, `LanguageServerConfig`, `SerializerState`, `DialogOptions`, `EventArgDeclaration`, `DocumentDecoration`, `BrowserWindow`, `ClientAssessments`, `FilePickerBreadcrumbItem`, `FactoryKey`, `Model.Project`, `XmlNode`, `PluginEvent`, `apid.ReserveEncodedOption`, `FragmentSpreadNode`, `Page`, `ts.FormatDiagnosticsHost`, `Diagonal`, `DragPanHandler`, `PackageNode`, `ParsedValue`, `parse5.DefaultTreeDocument`, `SpywareClass`, `WithNumber`, `LoginData`, `IconSize`, `Path3`, `LinkTransport`, `IndexPatternsFetcher`, `ManagementOption`, `Brackets`, `ResponderExecutionStatus`, `TemplatePatcher`, `IModalProps`, `firebase.database.Reference`, `RefreshService`, `ISendOptions`, `OperationArguments`, `ERC1155PackedBalanceMock`, `NothingShape`, `ReactiveEffect`, `MemberMethodDecl`, `ICustomField`, `ElementRunArguments`, `RenderService`, `TargetDetectorRecipe`, `ThyIconRegistry`, `AnimationState`, `IDinoContainerConfig`, `ToastConfig`, `TestStruct`, `INodeWithGlTFExtensions`, `Draw`, `CreateExceptionListItemSchema`, `SelectPartyToSendDelegate`, `IContextLogger`, `StatusPublisher`, `IDatabaseDataAction`, `CheckPrivilegesPayload`, `TypeInference`, `PiNamedElement`, `RefInfo`, `TestERC20Token`, `OperationResponseDetails`, `Vertice`, `ReLU`, `IMatchingCriterions`, `Subscriptions`, `IMyDateModel`, `TCmdData`, `SModelElement`, `StreamPipelineInput`, `DCollection`, `UpdateAppCommandInput`, `Lit`, `SpriteWithDynamicBody`, `NpmFileLocation`, `StringValue`, `IndicatorValuesObject`, `Crdp.Runtime.RemoteObject`, `ZeroExTransactionStruct`, `WS`, `SUPPORTED_FIELD`, `CW20Currency`, `NjsActionData`, `BoxShadowItem`, `BarChartOptions`, `ng.auto.IInjectorService`, `LocalFilter`, `EsQueryAlertParams`, `IInputProps`, `SubscriptionHandler`, `CardTagsProps`, `GroupsGetterFn`, `ColorOp`, `GeneratorResult`, `ts.TransformerFactory`, `DeleteApplicationResponse`, `ChangePassword`, `ListNotebookSessionsRequest`, `FetchLinks`, `FSMCtx`, `AzureTokenCredentialsOptions`, `BasicIteratorResult`, `ValidatorsFunction`, `FluentNavigator`, `ValueConstraint`, `OnModifyForeignAction`, `GeneralStorageType`, `model.Range`, `WorldgenRegistryKey`, `SidenavState`, `ExpressionRenderDefinition`, `Vector4d`, `AtomOptions`, `InventoryStore`, `SVGRenderer`, `Configs`, `ModulePath`, `ListApplicationsCommandInput`, `OPCUAServer`, `QueryByBucketMethod`, `DeleteWorkflowCommandInput`, `GetRowIdFn`, `TextOp`, `Deployment`, `MappingParameters`, `StorageUtility`, `TextDocumentSyncOptions`, `PlatformRef`, `ItemCount`, `TerminalProcess`, `Listeners`, `OwnerKeyInfoType`, `Photo`, `DbResult`, `SxChar`, `WalletProviderInfo`, `SpaceQuery`, `ITableMarker`, `TileDocument`, `GraphRewriteBuilder`, `MultiStepInput`, `IDatabaseDriver`, `VoiceFocusTransformDeviceObserver`, `NSURLSession`, `CollisionStartEvent`, `FeeEstimateResponse`, `Accounts`, `RelationEntry`, `RestyaboardItem`, `HTMLBodyElement`, `LROperation`, `IReaderState`, `ChildGraphItem`, `Vec4`, `BrowserExceptionlessClient`, `ASSymbolType`, `WechatyInterface`, `InterfaceRecursive`, `FlowFlags`, `ESLNote`, `MultisigAddressType`, `GmailResponseFormat`, `ModelSchemaInternal`, `Web3Callback`, `GetConnectionCommandInput`, `TimelineDragEvent`, `TeamWithoutMembers`, `AuthenticateAppleRequest`, `ARAddBoxOptions`, `SortableSpecService`, `OrderTemplatesDetailsPage`, `UpdateExperimentCommandInput`, `MockS3`, `UserRepository`, `Movimiento`, `BaseClusterManager`, `Vector2D`, `InitialArgv`, `Circuit`, `Discussion`, `DeleteResourcePolicyCommand`, `ForumActionType`, `validateTrigger`, `PhysicsHandler`, `puppeteer.ConnectOptions`, `mapTypes.YandexMap`, `CSharpResolversPluginRawConfig`, `ValidationParamSchema`, `grpc.Client`, `InternalServiceError`, `ActionFactoryDefinition`, `TreeModelNode`, `IOSIconResourceConfig`, `VariantCreateInput`, `DomRenderer`, `SnapshotDiff`, `d.DevServer`, `VdmFunctionImportReturnType`, `AvatarSource`, `TestObserver`, `DayOfWeek`, `InitiateResult`, `NgRedux`, `Box2Abs`, `LoaderAttributes`, `ParsedIdToken`, `DeleteAttendeeCommandInput`, `DiagnosticSeverity`, `Trackable`, `IPlDocVariablesDef`, `ɵɵInjectableDef`, `IEBayApiRequest`, `MerchantUserService`, `SnakeheadDataTable`, `Subnet`, `MapRendererParameters`, `QueryDeploymentRequest`, `PersistencyPageRange`, `VisualizationContainerProps`, `EbmlElement`, `ContainerInstance`, `TypedData`, `LGraphCanvas`, `ReacordInstance`, `DocumentTypes`, `FakeDatasetArgs`, `WatchService`, `BuildProps`, `d.HydrateAnchorElement`, `BaseFunction`, `ScoreRecord`, `Validation.Result`, `IRowMarker`, `UnivariateBezier`, `PublicAppDeepLinkInfo`, `PyteaServer`, `RadioButtonViewModel`, `Oscillator`, `TerminalCommandOptions`, `runnerGroup`, `MongoEntity`, `PDFAcroForm`, `ComponentInstance`, `BoundingSphere`, `PatchDocument`, `DatabaseConnection`, `MicrosoftDocumentDbDatabaseAccountsResources`, `EmitResult`, `HttpServerOptions`, `Selectors`, `AbstractHttpAdapter`, `AllocatedNode`, `CurriedFunction5`, `RoomInterface`, `FuncKeywordDefinition`, `CodeGenExecutionItem`, `GaugeEvent`, `EthApi`, `RedioPipe`, `TaskState`, `TNSPath2DBase`, `FABRuntime`, `PageInterface`, `ProcessedPublicActionType`, `ArrayBufferSlice`, `UniversalRouter`, `Uint8ClampedArray`, `SearchResourcesCommandInput`, `PropInfo`, `WorkspaceLeaf`, `InvalidConfig`, `EditorView`, `ThemeTypes`, `IGetEmployeeJobPostInput`, `TemplateResult`, `IDropboxAuth`, `Recordable`, `SynWorkspace`, `AlgWithIssues`, `ParamMetadataArgs`, `VideoTile`, `GameManager`, `HomeState`, `Notification`, `SelectMenuItem`, `ThingDescription`, `ExpressionParseResult`, `ICompilerOptions`, `Pages`, `SelectOptionConfig`, `Viewer.Texture`, `CreateConnectionResponse`, `ApiOperationOptions`, `PluginMetadata`, `QuickFixQueryInformation`, `IAssets`, `SecurityGroup`, `DbLoadCallback`, `DataTablePagerComponent`, `TupleIndexOpNode`, `VersionStatusIdentifier`, `PyTypedInfo`, `CustomFieldDefinition`, `RepositoryEsClient`, `ClipPlaneContainment`, `FragmentDefinitionNode`, `StateCallback`, `PythonShellError`, `PlanNode`, `VariableInfo`, `StepIterator`, `AuthState`, `SWRKey`, `SpreadSheetFacetCfg`, `blockClass`, `IFabricGatewayConnection`, `IDBPCursorWithValue`, `OtherActionsButtonProps`, `SubjectDataSetJoin`, `FindOptions`, `JRPCEngine`, `TypedClassDecorator`, `IViewer`, `EmptyAsyncIterable`, `MouseDownAction`, `ConsensusMessage`, `ExtensionProperty`, `TimeChartSeriesOptions`, `electron.BrowserWindow`, `RectDataLabel`, `T10`, `ContentConfigurator`, `ServerWrapper`, `SubscriptionData`, `KeyPairBitcoinCashPaymentsConfig`, `JumpState`, `JWT`, `Address`, `SessionContent`, `ContentType`, `FieldDef`, `PromiseState`, `TypeAssertionSetValue`, `BinaryMap`, `PartiallyParsedPacket`, `Json.Value`, `GetComponentCommandInput`, `restify.Next`, `SqlTuningAdvisorTaskSummaryReportIndexFindingSummary`, `JavaDeclarationBlock`, `TypeDefs`, `LinkFacebookRequest`, `OcsNewUser`, `BackendDetails`, `d.JsDoc`, `DocSegmentKind`, `DeployStatusExt`, `CreateArticleDto`, `GitInfo`, `AudioBufferSourceNode`, `NextRequest`, `HTMLIonSegmentButtonElement`, `Giveaway`, `NotificationComponent`, `AsyncSystem`, `UiCalculator`, `ValidationProfileExt`, `TeamsMembersState`, `IChannelStorageService`, `AtomId`, `AsyncFluidObjectProvider`, `Jest26Config`, `DirectoryReader`, `DomElementGetter`, `IWorkflowPersona`, `Admin`, `IReferenceSite`, `PackagePolicyInput`, `Odb`, `DebugElement`, `RPCRequestPayload`, `BackgroundFilterOptions`, `ControlBarButtonProps`, `Jenkins`, `GetFindingsCommandInput`, `theia.Task`, `TutorialService`, `Bool`, `ConfigureResponse`, `StorageMeta`, `Pass`, `BackstageManager`, `Progress.ITicks`, `ITemplateBaseItem`, `ITypescriptServiceClient`, `ITableField`, `StreamingClientInfo`, `UseTransactionQueryReducerAction`, `EnumerateType`, `AllMdastConfig`, `NodeJS.WriteStream`, `TlaDocumentInfos`, `RevocationReason`, `AppHistory`, `Artifact`, `WeChatInstance`, `ODataClient`, `IdentNode`, `btRigidBody`, `FoodReducerState`, `SpineHost`, `TypingIndicatorStrings`, `CleanupType`, `ForeignInterface`, `BluetoothServiceUUID`, `RoundArray`, `ConnectionRequest`, `TagType`, `ICodeGenerationOutput`, `Construct`, `requests.ListBdsApiKeysRequest`, `Fault`, `RequestError`, `PackageDependencies`, `TestFrontstage`, `vscode.DocumentFilter`, `GLTexture`, `NumberFormatter`, `ProblemType`, `StringColumn`, `IncomingWalletConfig`, `GachaDetail`, `Deno.Listener`, `FormErrorProps`, `TableListViewProps`, `DescriptorProto_ExtensionRange`, `ILatLng`, `ArangoDB.Collection`, `DidState`, `TData`, `CSSLength`, `RawExpression`, `PrivateEndpointConnection`, `AsyncOperation`, `FilteredHintItem`, `Analysis`, `SwapTable`, `Bracket`, `FlowWildcardImport`, `AxeScanResults`, `SorterResult`, `FaucetConfig`, `Entire`, `InterfaceType`, `CryptoWarsState`, `Sig`, `HeadProps`, `StatusReport`, `SequenceTypes.Participant`, `Highcharts.AnnotationEventEmitter`, `EntityCacheSelector`, `SimulationState`, `GetVpcLinksCommandInput`, `AoptB`, `MetricsGraphicsEventModel`, `AggConfigsOptions`, `TestTracer`, `ModuleInterface`, `SPClientTemplates.FieldSchema_InForm`, `PreConfiguredAction`, `ITreeEntry`, `SortDirection`, `CombineOutputResult`, `_TsxComponentV3`, `RGBA`, `SensorGroup`, `NamedObject`, `DBProperty`, `IFeatures`, `BitcoinPaymentsUtilsConfig`, `IAddOrInviteContext`, `CollectionsService`, `BackendMock`, `Suffix`, `TrackedBuffEvent`, `PeerApiResponse`, `JFlap`, `Equalizer`, `MyComp`, `OpenIdConfig`, `RepositoryCommonSettingDataType`, `GetParseNodes`, `SymbolDataContext`, `HitResult`, `UpdateApiKeyCommandInput`, `GetExportCommandInput`, `HTMLParagraphElement`, `fromRepositoriesStatisticsActions.GetRepositoriesStatisticsCollection`, `CivilHelper`, `ForkStatus`, `LineDataSet`, `GenericMerkleIntervalTreeNode`, `ElementMixin`, `AuthorizationResult`, `ErrorCollection`, `TriumphFlatNode`, `Io.Reader`, `IResizeEvent`, `AudioDeviceInfo`, `AnnounceNumberNumber`, `RepositoryWithGitHubRepository`, `sourceT`, `ObjectMetadata`, `TSpanStyleProps`, `ILaunchSetting`, `LinkSession`, `Participants`, `TagName`, `StrategyParameterType`, `NavTree`, `PlatformBrowser`, `ChartsPluginStart`, `IViewInstance`, `PQueue`, `DetachVolumeCommandInput`, `NexusInputObjectTypeDef`, `FullOptions`, `messages.TableRow`, `BarStyleAccessor`, `CdkDragDrop`, `ScopedDocument`, `ComponentCompilerTypeReference`, `TypeQueryNode`, `SafeResourceUrl`, `FileService`, `EnumInfo`, `Slur`, `ITemplatedComposition`, `MicrofabComponent`, `FileEmbedder`, `ObjectMultiplex`, `ObiDialogNode`, `GetVpcLinkCommandInput`, `ResourceInfo`, `TransitionEvent`, `SASQueryParameters`, `ActionCreatorWithNonInferrablePayload`, `UnorderedStrategy`, `ObjectRelationship`, `TupleCV`, `HistoryOptions`, `DequeueSharedQueueResult`, `AuthEffects`, `StartChannelCommandInput`, `WebAppCollection`, `supertest.Test`, `InformedOpenLink`, `DownloadStationTask`, `UpdateInfo`, `com.stripe.android.model.PaymentMethod`, `WebGLShader`, `AnimationSampler`, `AzExtLocation`, `TextDirection`, `pxt.TargetBundle`, `XhrDetails`, `Screenshoter`, `LuaInfo`, `UnknownType`, `HeadingCache`, `JWTPayload`, `ApiModel`, `WeuData`, `Aux`, `IndexerError`, `requests.ListDbNodesRequest`, `JSDocTupleType`, `MongoError`, `IMailTransferAgent`, `ProofResponseCoordinator`, `SearchEsListItemSchema`, `GetRRSetResponse`, `ElasticsearchFeatureConfig`, `ICitableSource`, `requests.ListResolverEndpointsRequest`, `ExtractorContext`, `UploadAssetOptions`, `fnVoid`, `KeyPath`, `Number`, `ParsedMessagePart`, `TelemetryPluginSetup`, `ListTaskRunLogsRequest`, `ABLMethod`, `GuideEntryType`, `P4`, `ISimpleGraphable`, `BaseTelemetryProperties`, `commandParser.ParsedCommand`, `TaskRepository`, `MaybeRef`, `HTMLIonLabelElement`, `StandardChip`, `OctoKitIssue`, `RecordOf`, `Messaging.IPublish`, `TransformerContext`, `DAL.KEYMAP_MODIFIER_POS`, `PropertyConfig`, `ShipSource`, `Limit`, `Proto`, `RouteNotFoundException`, `StringUtf8CV`, `ThemeConfig`, `TokenKind`, `PieVisParams`, `WaiterConfigurationDetails`, `ViewValue`, `FormValue`, `NvRouteObject`, `AppsService`, `XPCOM.nsICategoryManager`, `Enforcer`, `GetParams`, `DeleteDomainNameCommandInput`, `SelectedUser`, `ethers.Wallet`, `OutputCache`, `LoggerContextConfigType`, `HarnessAPI`, `StyledDecorator`, `IntrinsicFunction`, `IRepositoryModel`, `GameWorld`, `RefreshOptions`, `MachineData`, `ClientRule`, `reflect.ClassType`, `RenderInput`, `ManagementAgentPluginDetails`, `ExtensionOptions`, `LovelaceCard`, `HierarchicalNode`, `PostProcessingFactory`, `InternalServerError`, `ContextMasquerade`, `ExpressLikeResponse`, `KeplrGetKeyWalletCoonectV1Response`, `ERenderMode`, `ExtHTLC`, `DirectedScore`, `AbortSignalLike`, `ManagementAppMountParams`, `AxisDataItem`, `UpdateDetectorRecipeDetectorRule`, `DefaultRequestReturn`, `ICommentData`, `RestApi`, `ScaleThreshold`, `DOMProxy`, `TDispatch`, `DataModel.CellRegion`, `StepState`, `requests.ListSendersRequest`, `CreateParameters`, `InvoiceItemService`, `DataTransfer`, `ListGroupsRequest`, `pulumi.ComponentResourceOptions`, `ActionButtonProps`, `PostRef`, `protos.common.IMSPRole`, `DescribeDBInstancesCommandInput`, `InvoiceQuotation`, `ConfigurableForm`, `ExtendedTypeScript`, `QueryFetcher`, `WechatOfficialAccountService`, `SqlTuningTaskStatusTypes`, `Span`, `IUserRepository`, `AccessListEIP2930Transaction`, `UI5Type`, `ChoiceSupportOption`, `TypeTreeNode`, `GlobalNameFormatter`, `WebSocket.Data`, `ArtifactEngineOptions`, `UITableViewCell`, `MockWebSocketClientForServer`, `puppeteer.Browser`, `ReaderTaskEither`, `StatementsBlock`, `TransmartHttpService`, `ComponentData`, `NavigationProp`, `Reserve`, `RefactorEditInfo`, `TradeablePoolsMap`, `DeferIterable`, `PackageJsonData`, `QueryMnemonic`, `server.AccessKeyId`, `TSFiles`, `IEntityModel`, `PackageJson`, `CommandDefinition`, `PullIntoDescriptor`, `Knex.JoinClause`, `DynamicFormNode`, `Trampoline`, `SecService`, `Ants`, `NgGridItemConfig`, `Ohm.Node`, `IGetItem`, `RequestChannel`, `nodes.Identifier`, `TypeAlternative`, `AccountItem`, `GetStageCommandInput`, `ApiDecoration`, `MainPageStateModel`, `ResolvedDeclarations`, `FolderInfo`, `Friend`, `Ed25519KeyPair`, `IExecutorHandler`, `UpdateCallback`, `ExportTypeDefinition`, `DOMRectReadOnly`, `BaseCommand`, `QueryFunctionContext`, `GraphQLDatabaseLoader`, `HealerStatWeightEvents`, `TableResult`, `CodeGenField`, `TimelineSpaceState`, `ITeamCardState`, `ResponseHeaders`, `BillingGroupCosts`, `DBSymbol`, `TileType`, `ManglePropertiesOptions`, `ErrorPropertiesForName`, `Float32ArrayConstructor`, `StyleManager`, `ICluster`, `ChangePasswordCommandInput`, `CreateDiagnostic`, `Axis`, `ArgumentType`, `TagEntry`, `Sinon.SinonStub`, `ProcessErrorEvent`, `RegionCardinality`, `Python`, `MarginCalculatorInstance`, `ApiTypes`, `CronJob`, `UpdateRuleCommandInput`, `DidCloseTextDocumentParams`, `DescribeConfiguration`, `DynamicLinkParameters`, `TaskManagerStartContract`, `Call`, `LabwareCalibrationAction`, `UpdateParams`, `SidePanelTransitionStates`, `SpawnSyncOptionsWithStringEncoding`, `IGetCountsStatistics`, `K.TSTypeKind`, `SetWindowProps`, `HapCharacteristic`, `DbPull`, `option`, `throttle`, `MIRGuard`, `CreateIndexCommandInput`, `SymVal`, `PoseNet`, `HealthStateFilterFlags`, `LeaderboardRecordList`, `html.Node`, `MiddlewareStack`, `EthereumERC721ContextInterface`, `PutDedicatedIpWarmupAttributesCommandInput`, `GetWebACLCommandInput`, `BlobWriter`, `Expr`, `FabSettings`, `ListRulesRequest`, `Tsoa.ReferenceType`, `DeleteDBClusterSnapshotCommandInput`, `ParserRule`, `Reflection`, `EnvelopeGenerator`, `PickingRaycaster`, `Universe`, `MatProgressSpinnerDefaultOptions`, `AxisMap`, `BatchType`, `EPNode`, `PathDefinition`, `ShippingEntity`, `LoadingState`, `ITransferProfile`, `DatabaseSession`, `StateWithNewsroom`, `YouTube`, `EmbeddableChildPanelProps`, `INodeInterface`, `ClrHistoryModel`, `Enumerable`, `PrimitiveStringTypeKind`, `CAInfo`, `ChatThreadProperties`, `IPercentileRanksAggConfig`, `Shape`, `ComplexSchema`, `Translations`, `GenerateTimeAsyncIterable`, `DocumentFormattingParams`, `ParsedTranslationBundle`, `TransportOptions`, `IDraggableProps`, `EquatorialCoordinates`, `HitBlockMap`, `Moods`, `AppThunkAction`, `EntryCollection`, `SubReducer`, `TransactionReceipt`, `Author`, `GetProfileCommandInput`, `ResultReason`, `mb.EntityType`, `AppMetaInfo`, `NT`, `XMLBuilder`, `RewriteMapping`, `MouseData`, `DescribeChannelMembershipForAppInstanceUserCommandInput`, `VisualizerInteractionTypes`, `HttpServiceBuilderWithMeta`, `WaitInfo`, `EosioActionTrace`, `JSDocTypeExpression`, `UIMenuItem`, `UserTenantRepository`, `FactoryState`, `SecurityClassOwner`, `SchemaType`, `HTMLStyle`, `IMyValidateOptions`, `ILangImpl`, `DefaultPrivacyLevel`, `SCXML.Event`, `DeleteFunctionCommandInput`, `ValueReadonly`, `IFormFieldData`, `InstancePoolPlacementSecondaryVnicSubnet`, `ComputedAsyncValue`, `ReadConditionalHeadersValidator`, `HttpProbeProtocol`, `paper.Point`, `WriterType`, `BoxSizer`, `InitObject`, `FileReference`, `ItemSearchResult`, `IExtension`, `Highlight`, `GameDataState`, `RunHelpers`, `GuiObject`, `JSONSchemaObject`, `CreateTag`, `AggregationFrame`, `BadgeStyle`, `WorkspaceFolderSetting`, `IObject`, `Intf`, `EditorsService`, `ServiceKey`, `FavouritesState`, `ast.SeqNode`, `GoToProps`, `MultipartFileContract`, `PatternSlot`, `MpqHash`, `SMTVar`, `ISshSession`, `MockStore`, `CallHook`, `ConnectionStatus`, `XRReferenceSpace`, `IEntityInfo`, `TimelineKind`, `SuiModalService`, `News`, `OptionsReceived`, `LanguageHandlers`, `PassthroughLoader`, `PanelMode`, `IMonthAggregatedEmployeeStatistics`, `Queued`, `SMTConst`, `MyServer`, `TasksEntityStore`, `IPublish`, `UIDatePicker`, `EnvSection`, `MeterCCSupportedReport`, `Memory`, `NodeJS.ProcessEnv`, `ContentRef`, `ModelPath`, `PublishState`, `UseGeneric`, `SerializedHouse`, `NodeView`, `GetShapeRowGeometry`, `ECPair.ECPairInterface`, `token`, `IStreamChunk`, `SendMessagePayload`, `T.Action`, `Commands`, `IndexTreeItem`, `SolutionToSolutionDetails`, `PluginAPI`, `DescribeChannelCommandInput`, `CoreTypes.TextDecorationType`, `BatchSync`, `RequestData`, `FlattenLevel`, `AssociationCCReport`, `TelemetryPluginConfig`, `Predicate2`, `Geopoint`, `ODataEnumType`, `Aabb2`, `pxt.Package`, `HttpCacheService`, `Point2DData`, `InputEvent`, `CreateDatasetCommandInput`, `SessionEvent`, `LedgerWriteReplyResponse`, `DefaultKeys`, `TextInputVM`, `Building`, `EncodedPaths`, `fopAcM_prm_class`, `Consensus`, `VirtualModulesPlugin`, `GridDataState`, `ClassNames`, `AsyncEvent`, `FrontmatterWithDefaults`, `ACTION`, `DocumentData`, `ValidResourceInstance`, `TopicForIndicator`, `nconf.Provider`, `TheSimpleGraphQLServiceStack`, `CubeFace`, `DBClusterRole`, `PacketHandler`, `RSV`, `TransitionType`, `ValueJSON`, `UrlParams`, `UnsignedOrder`, `TransformationResult`, `Squiss`, `ISubprocessMessageBase`, `GainNode`, `JSONSchema`, `WritingSettingsDelegate`, `vscode.TreeView`, `AccountsInstance`, `Duration`, `FcCoords`, `DIDDataStore`, `DVector3d`, `IObserverCallback`, `ParsedRequestUrl`, `FullscreenOptions`, `TriggerForm`, `NodeInfo`, `ODataApiOptions`, `FieldState`, `ObjType`, `IsRegisteredFeatureHandlerConstraint`, `DeleteResourceCommandInput`, `ChatCommand`, `AppDataType`, `IosTargetName`, `SyncMemoryDebe`, `GLProgram`, `MessagingSessionObserver`, `TExpected`, `UpdateConnectivityInfoCommandInput`, `ISize`, `IGetSurveyModelsResponse`, `Participant`, `PowerPartial`, `StopHandle`, `HttpProvider`, `Typography`, `HashBucket`, `VisTypeTimeseriesRequestHandlerContext`, `StopApplicationCommandInput`, `BookingVariant`, `ExampleData`, `AaveV2Fixture`, `LContainer`, `PathFinderGoal`, `GaugeStatus`, `DiagnosticTag`, `AssetPropertyVariant`, `RTCRtpCodingParameters`, `AutomationEvent`, `MdastNodeMap`, `Deno.Conn`, `ControllerRenderProps`, `ProjectSummary`, `ApplicationShell.Area`, `WatcherOptions`, `ISimpleType`, `AnimDesc`, `DescribeEventsCommandOutput`, `SecureTrie`, `UrlOptions`, `DecisionPathPlotData`, `CreepActionReturnCode`, `NetworkSecurityGroup`, `PublishedFurniture`, `MenuOptions`, `SerialAPIVersion`, `PlaneBufferGeometry`, `NamedMember`, `MalVal`, `ExpressionNode`, `AdaptElement`, `_MessageConfig`, `StreamLabsMock`, `SonarQubeApiComponent`, `StaticFunctionDecl`, `AnimationChannel`, `UserConfigSettings`, `EmailModuleOptions`, `LinterGetOffensesFunction`, `RequestHeaders`, `PointerEvent`, `DomSanitizer`, `MemoryAppenderConfiguration`, `HoverProvider`, `ConstInterface`, `IProjectNode`, `RouteLocationRaw`, `IEntityError`, `PDFParser`, `CardCollection`, `STPCardValidationState`, `thrift.Thrift.Type`, `FormBuilderConfiguration`, `URLSearchParams`, `VpnPacketCaptureStopParameters`, `Express`, `IsString`, `RequestProfile`, `SubMeshRenderElement`, `ISceneObject`, `RDBType`, `RowTransformerValidator`, `formatLinkHeader.Links`, `CosmosBalance`, `XPCOM.nsIXULWindow`, `OpenSuccessCallbackResult`, `ImageRef`, `IndexOpts`, `ListTagsForResourceResult`, `LoadableMeta`, `Ent`, `MutateInSpec`, `NVMOperationsResponse`, `CompilerContext`, `DataListProps`, `IAnimatedCallback`, `ApolloServer`, `IWarriorInstance`, `AdaptMountedElement`, `CollectionStore`, `Navigation`, `apid.RecordedId`, `WorkerConfig`, `ConversationItem`, `TreeSelectionModificationEventArgs`, `SimulatorDatabase`, `ResolveRecord`, `PathParameterValues`, `IPipeable`, `BlockchainHandler`, `YieldFromNode`, `TimeTravel`, `RoleIndexPrivilege`, `ImportInterface`, `HTMLIonAlertElement`, `FeatureSettings`, `jest.DoneCallback`, `IAmazonApplicationLoadBalancer`, `MouseButtonMacroAction`, `LayeredLayout`, `ExpressServer`, `SecureHeadersOptions`, `DocOptArgs`, `Ringmodulator`, `MetricsPublisherProxy`, `FunctionNode`, `RenderOptions`, `Deal`, `Recursion`, `FilterFunc`, `LogSeriesFragment`, `ModuleWrapper`, `MessageToWorker`, `ComponentOptions`, `VoidFunction`, `JSONObject`, `RowType`, `GrabOptions`, `OsuSkinTextures`, `TheoryDescriptor`, `ITypeEntry`, `DOMException`, `FutureWallet`, `SteeringPolicyRule`, `ValueValidator`, `MonoSynth`, `ContainerOptions`, `ApolloReactHooks.LazyQueryHookOptions`, `CallSignature`, `EventDeclaration`, `ColonyNetworkClient`, `AttributeFilter`, `GroupingCriteriaFn`, `Gettable`, `FocusTrap`, `AggTypeState`, `CompleteGodRolls`, `MappedTypeGuard`, `ParseMode`, `IHubRequestOptions`, `StartedTestContainer`, `Metadata`, `IClientConfig`, `MergeIntersections`, `IndexedReadWriteXYZCollection`, `IJsonPatch`, `DataTableColumn`, `EventProxy`, `FlowItemComponent`, `SequenceConfig`, `CraftProjectConfig`, `FcConnector`, `ProgressDashboardConfig`, `FcException`, `AckFrame`, `Alarm`, `PythonCommandLine`, `Sandbox`, `UIFunctions`, `SearchAllResourcesRequest`, `DummySpan`, `AppDependencies`, `TeamType`, `Terminator`, `ValidPropertyType`, `AuctionManager`, `JsonAstObject`, `TCollectionSchema`, `OptimizeJsInput`, `ZoomBehavior`, `PublicationRepository`, `Constants`, `IGameContextValue`, `XTableRow`, `TrigonometryBlock`, `PutEmailIdentityDkimAttributesCommandInput`, `d.CompilerBuildStats`, `DescribeOfferingCommandInput`, `UserSimple`, `UserDTO`, `BreadcrumbPath`, `TestAccounts`, `TemplateCache`, `DatePickerDayDateSource`, `Sqlite.Statement`, `CreateChannelRequest`, `TreeAdapter`, `RoomUserEntry`, `TokenMap`, `UnitTestTree`, `DayGridViewWrapper`, `DataSeries`, `ComponentCompilerVirtualProperty`, `ModbusForm`, `Ceramic`, `TSESTree.Literal`, `CellOutput`, `ElectronShutdownCommandOptions`, `ApplicationVersionFile`, `Keypoint`, `ExtensionInfo`, `BytesValue`, `StoreReadSettings`, `ClassDeclarationStructure`, `RecommendationLifecycleDetail`, `LineLeaf`, `IScheduler`, `IPFSDir`, `GzipPluginOptions`, `TraceOptions`, `WithSerializedTarget`, `SchemaArgInputType`, `SelectorMeta`, `QueryManager`, `ManyToMany`, `ExtendedLayer`, `PrRepository`, `ILanguageState`, `EntityAttributes`, `InstanceLightData`, `UIImageView`, `MatPaginatorIntl`, `MediaPlayerState`, `SettingItem`, `Share`, `ICreateUpdateLanguageConfig`, `TextStringContext`, `GfxRenderTargetDescriptor`, `TwoFactorProviderType`, `BarcodeScannerConfig`, `LocalDirName`, `ListShapesRequest`, `Market`, `ServersState`, `CapsizeOpts`, `QueryCertificatesRequest`, `RoleRepresentation`, `AttributeInfo`, `SwingTwistSolver`, `DropLogFile`, `CustomPriceLine`, `SchemaKey`, `Reg`, `EditablePoint`, `babel.Node`, `DOMPointInit`, `Compact`, `StyleMap`, `TeliaMediaObject`, `NodeImmut`, `Income`, `SchemaResult`, `TextGeometry`, `Ticks`, `IsCommon`, `PrivKeySecp256k1`, `ListaTarefas`, `JobHandler`, `AsyncRequestHandler`, `TestBedStatic`, `Lock`, `DtlsServer`, `Instruction`, `CompilerHost`, `SortType`, `ListsState`, `SerializeImportData`, `DefaultRollupBlock`, `CompilerFileWatcherEvent`, `NgxsRepositoryMeta`, `request.OptionsWithUri`, `IconifyIconBuildResult`, `ConsoleAPI`, `ContentGroupProps`, `GovernanceMasterNodeRegTestContainer`, `LinearProgress`, `SelectItemDescriptor`, `JsonRpcHttpClient`, `LayoutCompatibilityReport`, `RenderPassDescriptor`, `ShaderSocket`, `CodeBuilder`, `ThemeColorable`, `vscode.TestController`, `IBazelCommandOptions`, `ListDataSetsCommandInput`, `INeonNotification`, `ast.UnaryNode`, `IconStorage`, `FilterRule`, `requests.ListDbVersionsRequest`, `EncryptedObject`, `RangeBucket`, `CallAgent`, `DynamoDbPersistenceAdapter`, `RestMultiSession`, `ChromeMessage`, `GQtyError`, `DisplayErrorPipe`, `VideoDownlinkObserver`, `Parsed_Result`, `BigSource`, `LocalNetworkDevice`, `Geolocation`, `BisenetV2CelebAMaskConfig`, `NetWorthSnapshot`, `ResultProgressReporter`, `DynamicFormValidationService`, `JOverlap`, `TodoListRepository`, `DocumentTree`, `ConfigOptions`, `SettingsState`, `DeployParams`, `RollupAggregator`, `RemoveEventListenerFunction`, `DynamicDialogConfig`, `FormFieldModel`, `DockerAuthObj`, `MIRInvokeFixedFunction`, `ResolvedRouteInfo`, `Handlebars.TemplateDelegate`, `Monad`, `ActivityComputer`, `ProjectChangeAnalyzer`, `DeleteBackupCommandInput`, `DataProxyAPIErrorInfo`, `ISlackPuppet`, `ListenerCallbackData`, `ISubImage`, `RoomInfo`, `UpdateCustomEndpointDetails`, `TransactionVersion.Testnet`, `ImageEncoder`, `Die`, `INode`, `EquipmentSharingPolicyService`, `SourcemapPathTransformer`, `QComponentCtx`, `ListrContextFinalizeGit`, `ContainerGetPropertiesResponse`, `HydrateImgElement`, `Deps`, `Properties`, `ReducerArg`, `QueryEntityKey`, `DocgeniHostWatchOptions`, `ContentRequestOptions`, `ThySelectionListChange`, `ChannelsState`, `AccountsContract`, `lambda.Function`, `CtrEq`, `UI5Namespace`, `Kind3`, `DialogStateReturn`, `ml.Attribute`, `SocketEvent`, `Parts`, `ISessionRequest`, `EntityCollectionDataService`, `GetRRSetRequest`, `IItemRendererProps`, `IRemote`, `M2ORelation`, `DashboardPlugin`, `IStoryItemChange`, `PixelType`, `Zoom`, `WebAssemblyInstantiatedSource`, `NavigationActions`, `HostComponent`, `EdaDialogCloseEvent`, `InternalFailureException`, `CliOutput`, `PutObjectRequest`, `GraphTxn`, `DaffCountry`, `iTickEvent`, `UseFormReturn`, `PathCursor`, `OwnPropsOfRenderer`, `ExchangePair`, `IListenerAction`, `HighlightRange`, `SerializedGame`, `BlockHash`, `MlClient`, `Behaviour`, `CommonMaterial`, `UnscopedEmitHelper`, `CodeMirrorEditor`, `RTDB.Get`, `BadRequestErrorInfo`, `FileSystemCache`, `PropertyCategory`, `HttpProbeMethod`, `LinkI`, `runtime.HTTPQuery`, `Contest`, `GroupConfig`, `PromiseJsExpr`, `TouchEvent`, `LetterSpacing`, `Serializable`, `BasePackage`, `CustomElementRegion`, `Color`, `SetBreadcrumbs`, `interfaces.Context`, `PetStoreProduct`, `ClassWriter`, `ListTagsForResourceMessage`, `EnhancedSku`, `CSSEntries`, `LockType`, `STWidgetRegistry`, `SpeculativeContext`, `ListTablesResponse`, `NodePrivacyLevel`, `Ext`, `ITerminalProvider`, `EventInterface`, `ThemeCss`, `Types`, `RTDB.Subscribe`, `GeoBox`, `BinarySensorType`, `SchemaBuilder`, `IRequestConfig`, `XUL.contentWindow`, `OrganizationPolicySummary`, `SuccessfulParsedMessage`, `ColumnFormat`, `AuthConfig`, `IconType`, `CosmosOperationResponse`, `FolderDoc`, `AppError`, `ExecutionContextInfo`, `IDeclaration`, `VerifyJwtOptions`, `Purse`, `PrefBranch`, `CreateFileOptions`, `LoginUriView`, `Linear`, `ComponentTypeEnum`, `WebViewExt`, `IScriptingDefinition`, `ast.IfNode`, `SourceIntegrationInterface`, `PipelineRelation`, `FlowCondition`, `ITextDiff`, `CeloTokenContract`, `VercelConfig`, `ViewData`, `FaunaUDFunctionOptions`, `PackageManager`, `Instrument`, `flatbuffers.Offset`, `IJSONInConfig`, `iAction`, `ConfirmChannel`, `PluginDeleteActionPayload`, `K4`, `FoamWorkspace`, `ResultT`, `RegisteredSchemas`, `WeakRef`, `HeatmapDataSets`, `IFactor`, `TranslatePropertyInput`, `AnimationChannelTargetPath`, `EvmType`, `Snapshot`, `ToplevelRecord`, `PostConditionMode.Deny`, `MemberNode`, `LastValues`, `UpdateType`, `RequestTemplate`, `CollectionConfig`, `ReferenceMonth`, `DataModels.Kpi.ActiveTokenList`, `PolusBuffer`, `ExpansionResult`, `ListDatabasesRequest`, `SiteClient`, `ResponseMessage`, `LoggerService`, `PluginPackage`, `CategorizationAnalyzer`, `YAMLMapping`, `NoncurrentVersionTransition`, `CategoricalColorScale`, `CellPosition`, `TPageConfig`, `d.TypesMemberNameData`, `Dependence`, `IPrompter`, `MessageDataOptions`, `ShadowboxSettings`, `ValuedRivenProperty`, `ResourcePropsWithConfig`, `TextureConfig`, `DictionaryFile`, `ContractManifestClient`, `ITranslationMessagesFile`, `IndexDiff`, `SuperAgentTest`, `TS.Node`, `CssRule`, `Simulate`, `DownloadRef`, `TaskItem`, `GlobalPropertyStruct`, `NodeCheckFn`, `SkeletonTextProps`, `Gen`, `ExtendedAreaInfo`, `UpdateChannelReadMarkerCommandInput`, `AsyncWaterfall`, `AuthType`, `a`, `EntityProperty`, `ExtractClassDefinition`, `VerifiedCallback`, `CalcObj`, `TexturedStyles`, `DMMF.TypeInfo`, `LogicalQueryPlanNode`, `Workspace`, `FixOptions`, `StringToken`, `ProfileX`, `ConstraintSolver`, `RegistryPolicyTemplate`, `SVGGElement`, `Loggable`, `TimelineActivity`, `StartServices`, `ThresholdedReLU`, `MessageToken`, `ModelData`, `H.Behavior`, `KibanaRequest`, `FilteredLayer`, `SystemVerilogImportsInfo`, `EntitySelectorsFactory`, `BemSelector`, `DeploymentDisconnectStatus`, `DeleteIntentCommandInput`, `tf.LayersModel`, `TwingSourceMapNode`, `IRenderDimensions`, `DirectedEdge`, `Mocha`, `BinaryTree`, `EncodedQuery`, `ICheckOut`, `FileDeleteOptions`, `ResourceCacheData`, `WorkspacePlugin`, `AggTypeConfig`, `SelectionsWrapper`, `ComponentsCompiler`, `BuildData`, `CameraController`, `LyricLanguage`, `ComparatorFn`, `SubdivisionScheme`, `Listenable`, `CalendarPatterns`, `ClientSubLocation`, `t_As`, `Screen`, `PiLimitedConcept`, `GaugeRenderProps`, `TableSeg`, `IGenericTaskInternal`, `BodyParser`, `DocumentGenerator`, `Selector`, `ListAutoScalingPoliciesRequest`, `StaticFunctor`, `OptionsMatrix`, `VRMSpringBone`, `GitUrl`, `SourceMap`, `Props`, `d.HydratedFlag`, `ExportedConfigWithProps`, `GraphDataProvider`, `NodeDependency`, `P1`, `LeafletElement`, `requests.ListZoneTransferServersRequest`, `RelationshipPath`, `Poker`, `Yendor.Console`, `PackageJsonOptions`, `EditPageReq`, `ISummaryContext`, `GfxQueryPool`, `Volume`, `OutputWriter`, `estypes.AggregationsAggregationContainer`, `IStatusView`, `OutputCollector`, `INormalEventAction`, `RenderBatchKey`, `I18n`, `DeleteRetentionPolicyCommandInput`, `ts.Map`, `ProgressMessage`, `ClientImpl`, `Angulartics2GoogleGlobalSiteTag`, `EnvProducer`, `STS`, `WebPartContext`, `SingleConsumedChar`, `AddressNonces`, `XActorRef`, `FunctionCallArgumentCollection`, `CustomText`, `GfxBufferBinding`, `HintResults`, `NzDrawerRef`, `Labware`, `FriendRequest`, `QuestService`, `RoutingRule`, `IPathfindersData`, `InstrumentationLibrarySpans`, `EntityOp`, `ListUserProfilesCommandInput`, `Powerlevel`, `MIRRegisterArgument`, `ethers.providers.JsonRpcProvider`, `LoadedTexture`, `Charge`, `ProgramCounterHelper`, `MagicOutgoingWindowMessage`, `TransactionEventType`, `AtRule`, `GlobalDeclaration`, `IEditEntityByMemberInput`, `NestedOptionHost`, `InfluntEngine`, `ClassRefactor`, `MetamodelService`, `ChartjsComponentType`, `PortObject`, `Guy`, `ValidationResultsWrapper`, `SwitcherItem`, `requests.ListCloudAutonomousVmClustersRequest`, `LLVMNamePointer`, `DalgonaState`, `DiagnosticsOptions`, `CreateAppointmentService`, `SecondaryIndex`, `FormType`, `SubscriberEntity`, `S3Source`, `EntityDefinition`, `PositionProps`, `NexeCompiler`, `MiddlewareFnType`, `SetState`, `MeetPortalAnchorPoint`, `GestureUpdateEvent`, `ImportData`, `GlyphSet`, `TimelineActivityKind`, `TableOptions`, `OutdatedDocumentsTransform`, `NodeI`, `BuildApiDecOpts`, `models.ISegement`, `TransactionResult`, `MinimalNodeEntryEntity`, `GetJobCommandInput`, `Path0`, `PanEvent`, `VfsEntry`, `IStorageSyncOptions`, `GenericAsyncFunc`, `AuthToken`, `SignedByDecider`, `StepChild`, `LinkedList`, `SymExp`, `DebugProtocol.ConfigurationDoneResponse`, `PropertyFlags`, `LoaderManager`, `RpcNode`, `TextureOverride`, `Pass1Bytes`, `WebpackAny`, `Loadable`, `ArgumentMetadata`, `ZipMismatchMode`, `PDFAcroPushButton`, `Toggleable`, `ICurrentControlValidators`, `Tally`, `TAction`, `FromViewOpts`, `AddAtomsEvent`, `TaskSchema`, `Node.Identifier`, `ArrayExpression`, `DropdownOption`, `ILoggedInUser`, `yubo.PlayOptions`, `d.MinifyJsResult`, `CheckboxValue`, `PinoLogger`, `AttributeType`, `CommonStyleProps`, `UserDto`, `ParsedQueryNode`, `FunctionParameter`, `OptiCSSOptions`, `TimeAveragedBaseRateOracle`, `ITokenInfo`, `NameObjFactoryTableEntry`, `VaultTimeoutService`, `ColumnBands`, `InputTypeComposer`, `SymbolWriter`, `OpenChannelObjective`, `AsyncIterableX`, `ChatError`, `ListServicesResponse`, `ArrowFunctionExpression`, `PlayerAggHistoryEntry`, `Record`, `AWS.CloudFormation`, `UserSettingsModel`, `btSoftBody`, `ClassExportDoc`, `StatsService`, `ICloudFoundryServerGroup`, `RequestCancelable`, `ApmPluginContextValue`, `IAresData`, `DMMFClass`, `Certificate`, `CreateHitTesterFn`, `TagEdit`, `VstsEnvironmentVariables`, `FetchEnd`, `DragDropIdentifier`, `ExecutionLogSlicer`, `WorkflowInputParameterModel`, `ContextMenuParams`, `FileBlock`, `AuditResult`, `ReturnModelType`, `ShoppingCart`, `Offsets`, `Country`, `OrderDirection`, `SignInPayload`, `TransitionDescription`, `CommonToolbarItem`, `SpaceService`, `Errno`, `InitTranslation`, `BabelPluginChain`, `RequestSuccessAction`, `rp.OptionsWithUrl`, `Batch`, `Debug`, `PathFragment`, `BitcoinTransactionInfo`, `BSplineCurve3dH`, `CombatVictorySummary`, `Note`, `CrochetCapability`, `d.LogLevel`, `TrueGold`, `ImageService`, `IBranch`, `PumpState`, `DemoService`, `Rule.RuleListener`, `_IRelation`, `DoorFeatureType`, `CommandReturn`, `IAdministrationItem`, `ResourceComponent`, `ExecutableSpec`, `KeyBindingCommandFunction`, `SelectedState`, `EngineArgs.DevDiagnosticInput`, `BookmarkHelperService`, `AST.SubExpression`, `DocumentConnectionManager`, `NamePosInfo`, `ObjectAllocator`, `ColorHelper`, `ProjectedDataItem`, `Math2D.Box`, `ReleaseDefinitionSchema`, `IPageNode`, `RegularizationContext`, `Closeable`, `WithStringLiteralProperties`, `ApplicationMetadata`, `ExtensionDefinition`, `CasesClientArgs`, `RevealConfig`, `IJSONResult`, `EntityMapEntry`, `AppModels`, `StreamQuery`, `gameObject.Bullet`, `JsonDocsTag`, `VFileCompatible`, `StatusBarWidgetControlArgs`, `cPhs__Status`, `Speaker`, `FakePlatform`, `AuthenticatedUser`, `HttpResources`, `Placement`, `BaseConfig`, `t.STSelector`, `DescribeEventAggregatesCommandInput`, `AccountTransfersService`, `Crypto`, `OrthogonalDirection`, `FormatCodeSettings`, `ActionCallback`, `RespondersThemeType`, `LayerState`, `ConfigurableEnumConfig`, `DevicesButtonStrings`, `Config`, `TestReport`, `Router.RouterContext`, `MultiChannelAssociationCCRemove`, `MediationRecord`, `ElectrumNetworkProvider`, `IFBXLoaderRuntime`, `PythonDependency`, `CarouselProps`, `ShapeModel`, `TagNode`, `Regularizer`, `ITestsService`, `api.IZoweDatasetTreeNode`, `Insight`, `IconTheme`, `CountableTimeInterval`, `sinon.SinonSandbox`, `OutputFormat`, `CloudWatchDestination`, `ImportInterfaceWithNestedInterface`, `UntagResourceRequest`, `CallAndResponse`, `PromiseFast`, `JsxClosingElement`, `AsyncThunk`, `WebGL`, `RicardianContractProcessor`, `ForkEffect`, `RenderState`, `BottomSheetOptions`, `ModelInterface`, `ObservableQuery`, `CustomHttpResponseOptions`, `TaskRecord`, `ProxySide`, `CarouselService`, `TSpan`, `CreateScope`, `CourseState`, `DeleteGatewayCommandInput`, `Sample`, `ShapeGeometry`, `PiTriggerType`, `CreateFilterCommandInput`, `SavedObjectsCreatePointInTimeFinderDependencies`, `PieceAppearance`, `Segment3`, `requests.ListApplicationsRequest`, `TypingGenerator`, `ActionState`, `DOMExplorerDashboard`, `CeloTxReceipt`, `IShadowGenerator`, `ColumnMapping`, `ColumnSchema`, `PostToken`, `FunctionType`, `TypeAttributeKind`, `SwitcherResult`, `ActiveMove`, `ListComprehensionIfNode`, `ColonyExtensionsV5`, `VMContext`, `ReadTarball`, `PointerInfoBase`, `Resolvable`, `CreateWidgetDto`, `CardType`, `Jws`, `UpdateRouteCommandInput`, `S2Options`, `CommandResult`, `IGBPackage`, `BaselineResult`, `EToolName`, `BitmapFont`, `ThenableReference`, `BRepGeometryCreate`, `DomainPanel`, `PolicyContext`, `ClozeDeletion`, `Transaction.Options`, `CompilerInput`, `ContextName`, `SourceRootInfo`, `XYLayerConfig`, `ListenerCallback`, `ILexoNumeralSystem`, `UserMatched`, `LayerValue`, `JoinGroupRequest`, `DataRequestMeta`, `EditorOptions`, `FileMetaData`, `ControlState`, `TranslationLoaderService`, `CustomMerge`, `PrevoteMessage`, `JWKInterface`, `WideningContext`, `OpenApiSpec`, `HoverSettings`, `NixieEquipment`, `GenericMonad`, `SecondaryUnit`, `FullName`, `VirtualKey`, `EitherExportOptions`, `HsLogService`, `LunarInfo`, `SpeechConfig`, `d.HostRef`, `Cipher`, `requests.ListAcceptedAgreementsRequest`, `NetworkType`, `DMChannel`, `Oas20Parameter`, `ResourceQuota`, `WorkerResult`, `App.windows.window.IXulTrees`, `IPayloadAction`, `SingleKeyRange`, `IAPProduct`, `ISearchSource`, `ImageSource`, `CustomTemplateFindQuery`, `UpgradeDomain`, `TypePath`, `EventNameFnMap`, `AutoCompleteProps`, `Plyr`, `EnvironmentSettings`, `IGherkinOptions`, `SelectionModel`, `AnyClass`, `GetUserSuccessPayload`, `BoxBuffer`, `IRangeResponse`, `ColorInputProps`, `DistinctOptions`, `TransformHeadersAgent`, `ClipboardService`, `Descriptions`, `LinkedEntry`, `TAny`, `QualifiedOTRRecipients`, `StateStore`, `IGeometryProcessor`, `PhysicalKeyboardKey`, `RoamBlock`, `Tristate`, `TrackGroupIndex`, `Bleeps`, `AList`, `CalendarEventStoreRecord`, `LogicCommand`, `LogBoxLayout`, `StaticEllipseDrawerService`, `UpdateAlbumDto`, `HTMLStencilElement`, `ClientErrorResponse`, `MinAdjacencyListDict`, `InstallOptifineOptions`, `TArgs`, `RequestPopupModelAction`, `OptimizedSubSetKey`, `T.Position`, `RendererFactory3`, `DescribeGlobalClustersCommandInput`, `ShellOptions`, `MainPackage`, `IApplyJobPostInput`, `GetAccountSettingsCommandInput`, `ListConfig`, `PrismaClientClass`, `PluginCallbacksOnSetArgument`, `ODataPathSegments`, `LanguageVariant`, `ObservableProxy`, `JSDocState`, `OtherInterface`, `GlobalSearchResultProvider`, `IApplicationOptions`, `optionsInfo`, `BrowserPlatformUtilsService`, `CustomNode`, `AssetManifest`, `EmojiListObject`, `MIDIControlListener`, `AggregationResultMap`, `LoaderProps`, `ForceDeployResultParser`, `FrontendLocaleData`, `WellKnownTextNode`, `DraftHandleValue`, `DescribeDeviceCommandInput`, `ISwissKnifeContext`, `FeaturesDataSource`, `ITimezoneMetadata`, `CloudKeyStorage`, `ValueValidationFunc`, `IApp`, `XmlMapsCommandInput`, `HypermergeNodeDetails`, `ViewEntityOptions`, `IHandlers`, `GetDomainCommandInput`, `DriverMethodOptions`, `CartesianChart`, `ConfigStore`, `ValidationErrors`, `CipherCreateRequest`, `RemoveTagsFromResourceCommandOutput`, `TagDescription`, `Utf8ToUtf32`, `ValuesProps`, `ResolvedTupleAtomType`, `LastInstallFlag`, `BitWriter2`, `IObservableObject`, `IMethodHandler`, `Thrown`, `EvaluationScopeNode`, `MVTFieldDescriptor`, `StrategyParameter`, `IMutableVector2`, `EMSTermJoinConfig`, `INodeIssues`, `IDraggableList`, `ObjectDefinition`, `CookieParseOptions`, `LengthPrefixedString`, `FunctionBreakpoint`, `React.ReactChild`, `PortalInjector`, `RpcServerFactory`, `DropdownOptions`, `DynamicIndentation`, `MDXRemoteSerializeResult`, `EquipmentSharingService`, `DisplayCallbacks`, `ConstraintMember`, `SVFloat`, `sinon.SinonSpyCall`, `ParamWithTypeMetadata`, `MetricDimensionDefinition`, `KubeArgs`, `MetadataTypeGatherer`, `HandlerDelegate`, `ArrayLiteral`, `LockOptions`, `ListTranscriptionJobsCommandInput`, `HierarchyOfArrays`, `AttachedModule`, `ApiDefinition`, `MenuModelConfig`, `InboundMessageContext`, `ColorResolvable`, `GDIContext`, `FieldMap`, `GfxSamplerBinding`, `RoomClient`, `Prediction`, `DateFnsInputDate`, `AddressProtocol`, `TrueSkill.RankState`, `ArrayOrSingle`, `StateManager`, `TestAccount`, `NumberShape`, `KontentHttpHeaders`, `PostDocument`, `DOMElementType`, `IPageHeader`, `requests.ListCatalogsRequest`, `ServiceKeyType`, `FormRenderProps`, `IMembership`, `TileMapArgs`, `StableTokenWrapper`, `SelectMenuItemProps`, `UniformsType`, `CodeEditor`, `HoverTarget`, `EffectsInvocationContext`, `AppProduct`, `SankeyDiagramLink`, `CreateChildSummarizerNodeFn`, `OptionedValueProp`, `StateEither`, `RxFormGroup`, `SplitStructureAction`, `IResponseAggConfig`, `Measurement`, `RecordingTemplate`, `AutocapitalizationInputType`, `WorkerOptions`, `userData`, `NcTemplate`, `CommonCrypto`, `PermissionOverwrite`, `RequestObject`, `IntrinsicType`, `DxTemplateHost`, `Phaser.Scene`, `BytecodeLinkReference`, `indexedStore.Store`, `OnboardingService`, `GaiaHubErrorResponse`, `ArangoSearchView`, `CdkVirtualScrollViewport`, `CreateGroupResponse`, `IsvDebugBootstrapExecutor`, `ISearch`, `Trilean`, `MeasureSpecs`, `IALBListenerCertificate`, `TTargetReference`, `ItemRequest`, `messages.Rule`, `ColumnMetadata`, `NexeFile`, `FilePreviewDialogRef`, `RoomStoreEntryDoc`, `GreetingWithErrorsOutput`, `UnwrappedObject`, `Manager`, `MotionChartData`, `TreemapSeriesOptions`, `FilterResult`, `EchartsProps`, `tf.Tensor4D`, `WidgetModel`, `DefaultSession`, `VMLClipRectObject`, `ITestConfig`, `IniFile`, `InteriorInternal`, `CredentialPreviewAttribute`, `LoginState`, `NodeModule`, `ApiItemContainerMixin`, `GfxrRenderTargetID`, `ParserOutput`, `OrderByDirection`, `DebugContext`, `ConsoleLike`, `Slice`, `TabbedAggResponseWriter`, `IClassExpectation`, `TopUpProvider`, `SVGElement`, `CacheStorage`, `AppMenuItem`, `StackElement`, `PositionChildProps`, `LinearFlowFunction`, `IDropdownOption`, `FatalErrorFn`, `Figure`, `ShadowAtlas_t`, `requests.ListCategoriesRequest`, `GfxInputLayout`, `Semiring`, `Width`, `ComplexNode`, `sdk.Connection`, `RawTextGetter`, `IdentifierListContext`, `CloudfrontMetricChange`, `FeedbackContextInfo`, `IndexPattern`, `CacheContextContract`, `ColorRulesOperator`, `JustValidate`, `ISerializedResponse`, `ComputedStateCreationOptions`, `IResults`, `OP`, `ReverseIndex`, `DestinyInventoryItemDefinition`, `BufferMap`, `ParsedGenerator`, `TraversalContext`, `ProtocolRequest`, `ITfsRestService`, `IConnectionsIteratorOptions`, `WorkspaceSchema`, `LengthUnit`, `VariantFunction`, `UpdateIntegrationResponseCommandInput`, `PatternSequenceNode`, `InternalCallContext`, `IGuardResult`, `ShellComponent`, `VorbisDecoder`, `thrift.Int64`, `ObservableTitleTopBar`, `SongResult`, `AccountClient`, `DynamicValue`, `BaseText`, `SfdxFalconInterview`, `AvatarCustomization`, `PartyService`, `Pixel`, `MulticallClient`, `SnotifyToast`, `CustomersService`, `AttributeViewInfo`, `EntityCollectionReducers`, `SignatureInformation`, `DropType`, `AdamOptimizer`, `ClassField`, `IProjectConfig`, `OperationRequest`, `RibbonButton`, `IndexColumnModelInterface`, `Tool`, `AnyGradientType`, `ExpBool`, `ClassBody`, `ProjectTaskProperties`, `ClaimData`, `VMoneyOptions`, `ContractCalls`, `Design`, `Themes.Theme`, `NoiseModule`, `MapboxMap`, `PayloadDictionary`, `DependencyResolved`, `AnalyzeOptions`, `Navigator`, `StoredItem`, `DataLabelOption`, `egret.DisplayObjectContainer`, `GameSize`, `TextInputOptionProps`, `DAL.KEYMAP_ALL_KEYS_UP_POS`, `chalk.Chalk`, `LanguageSettings`, `CompilerProvider`, `RecognizerConfig`, `EntitySubjectStore`, `GMxmlHttpRequestEvent`, `Functor3`, `AsyncStepResultGenerator`, `SearchClient`, `TermSet`, `IChatJoinProperties`, `Location`, `CheckState`, `ProjectedEdge`, `PartitionOptions`, `Referenced`, `AffineFold`, `CreateDemandDTO`, `DbPush`, `CssClassMap`, `AXNode`, `SlidingWindow`, `StateMap`, `VinVout`, `ControlButtonProps`, `MetaDataCollector`, `LazyScope`, `Polymer.Element`, `ImportDeclarationStructure`, `ITaskChainFn`, `AreaProps`, `DGuard`, `QueueConfiguration`, `vfs.FileSet`, `VerificationGeneratorDependencies`, `ModifierFlags`, `ProtobufValue`, `VAF1`, `TransferOffchainTx`, `IDocumentStorageService`, `requests.DeleteProjectRequest`, `UsePaginatedQueryMergeParams`, `T.MachineContext`, `sourceTextureFormat`, `RegistrationForm`, `ExtractionResult`, `RenderMethod`, `AnalysisConfig`, `TileStyle`, `StatusState`, `ITour`, `GLTF.IAccessor`, `GridNode`, `AssertionTemplateResult`, `ReplacementBuilder`, `FileEditAction`, `FaunaId`, `MySQLConnection`, `FzfOptions`, `AccessRuleCriteria`, `AccountStellarPayments`, `OrganizationUnitDto`, `GX.ColorSrc`, `IUploadResult`, `ParseErrorCode`, `THREE.Raycaster`, `Vector3`, `LoaderConfig`, `SalesSearchOptions`, `SelectionEvents`, `DispatchProps`, `SyncedActivityModel`, `Stock`, `IMdcRadioElement`, `ThyDragDirective`, `FiberRoot`, `VisualizeEmbeddableFactory`, `IngredientOrResult`, `SsrcDescription`, `DocumentOptions`, `MetricUnit`, `RenderingDeviceId`, `ILecture`, `GLTFLoader`, `MpqFile`, `ITarget`, `RemoteBaseMock`, `vile.IssueList`, `mat3`, `RestServerConfig`, `IActionTrackingMiddleware2Call`, `ComponentRuntimeMeta`, `AssembledPipelinesGraphics`, `MessageThreadStrings`, `AccountsOperationIO`, `AuthTokenRequestSigner`, `OverloadedFunctionType`, `NzDrawerService`, `DeclarationBase`, `ScoreDoc`, `MultipartFile`, `StateMapper`, `FkDstrGridData`, `MassetDetails`, `EmitHint`, `EsHitRecordList`, `WildlingsAttackGameState`, `d.ConfigBundle`, `PointToPointLine`, `CronJobOptions`, `Composition`, `QRFunction`, `EmptyEventCreator`, `BlockSyntaxVersion`, `FetcherContext`, `TransformOrigin`, `MarketDataProvider`, `InstanceWithExtensions`, `RemoteConfigTemplate`, `VaultStorageService`, `FilesService`, `FirebaseError`, `ZoneSwitch`, `DataServiceError`, `ts.PostfixUnaryExpression`, `Mustering`, `TerminalState`, `TypeReference1`, `MatchExecutor`, `MLKitVisionOptions`, `mixed`, `ModelName`, `AtemConfiguration`, `BufferColumn`, `LockTime`, `WindowFrameName`, `KeySet`, `IsSpecificRowFn`, `PluginsClient`, `MetaQuestion`, `CliProfileManager`, `StreamingCmd`, `PSIInteger`, `Pallete`, `AngularFireUploadTask`, `DescribeResourcePolicyCommandInput`, `CallErrors`, `ReflectContext`, `MapViewInset`, `ThemeSetup`, `NodeList`, `Electron.IpcRendererEvent`, `TickFormatterOptions`, `MapShape`, `ActionsList`, `RentalService`, `NodeRecord`, `ResizerMouseEvent`, `NodeRpcService`, `TableInfo`, `UserStateService`, `WhereExpressionBuilder`, `S1GRDAWSEULayer`, `PiePoint`, `IRCMessage`, `RtpPacket`, `TerraformAuthorizationCommandInitializer`, `KeyAlgorithm`, `IObservableArray`, `ThemeInterface`, `SectionDataObject`, `INetworkInfoFeature`, `BarycentricTriangle`, `RepositoryCommonSettingType`, `Value.Of`, `InvalidState`, `PatternEnumPropertyOption`, `InputsType`, `MigrateStatus`, `CalendarMode`, `CallHierarchyDefinition`, `ActionPayload`, `ListCustomVerificationEmailTemplatesCommandInput`, `CompilerSystemRealpathResults`, `UserInterests`, `RotationSettings`, `KeyStop`, `SimpleType`, `DesignTimeProperty`, `JupyterKernel`, `ThyOptionComponent`, `SelectableDataPoint`, `PluginOpaqueId`, `PanGestureEventData`, `AwsCloudProvider`, `ExecaSyncReturnValue`, `TinyTranslatorService`, `ObjectOrArray`, `IFB3DOM`, `LambdaDataSource`, `ITimesheet`, `SHA256`, `GraphqlData`, `IIssue`, `eventInterface`, `EventListenerOrEventListenerObject`, `QuotePreference`, `SelectOptions`, `WeakSet`, `JSDocVariadicType`, `AsyncFrameworkFn`, `ethereum.Event`, `IColorSet`, `CurrencyObject`, `FileWatcherEventHandler`, `AddressRecord`, `USER`, `TodoDataService`, `ComponentSize`, `DisplayValue`, `ClassMap`, `ObjectValidator`, `PackageJsonLookup`, `ImmutableObjectiveGroup`, `SymbolTickerOrder`, `AuthType.Sponsored`, `MapScalarsOptions`, `TestERC721Token`, `AliasesMeta`, `JsonApiDocument`, `DescribeUserCommandInput`, `Eci`, `Pswp`, `FreezerContract`, `GQLEventSearchResultSet`, `ByteData`, `IMainState`, `TestAdapter`, `StoryLabel`, `SearchStrategyRequest`, `IAureliaComponent`, `CreateWorkspaceCommandInput`, `SinonStubbedInstance`, `SegmentClient`, `PageTemplate`, `ChartDataSet`, `ISettings`, `PromptOptions`, `ConfigurableFocusTrapConfig`, `TestSuite`, `TaskReport`, `PyrightJsonDiagnostic`, `DateTimeOffset`, `SurveyObjectItem`, `GroupRepresentation`, `WebSiteManagementModels.SiteConfigResource`, `HeaderMapManipulator`, `IGeneralFunctions`, `DatabaseInfo`, `CreateAssetProps`, `HandlerDomProxy`, `vscode.NotebookCell`, `StorageCacheService`, `ExportTraceServiceRequest`, `InventorySocket`, `RhoProcessor`, `StopInstanceCommandInput`, `ICordovaAttachRequestArgs`, `HuffmannNode`, `HasFancyArray`, `MinorEvent`, `DefaultValue`, `GraphicsLayerOptions`, `SavedSearchSavedObject`, `RenderResult`, `BoolArray`, `ElmType`, `ContainerAdapter`, `IWrappedEntityInternal`, `ArchiverError`, `GetAuthorizationTokenCommandInput`, `ApiExperiment`, `FnN5`, `SceneActor`, `IterableChangeRecord`, `ChromeStart`, `LanguageInfo`, `BlockDefinition`, `Answerable`, `AuthRequest`, `FormLabelProps`, `Persister.IPersist`, `SideNavComponent`, `SynthesisContext`, `Points`, `SpriteFrame`, `GoogleDriveSyncMetadata`, `Metric`, `Pooling1DLayerArgs`, `TCommand`, `CommonAlertParams`, `IntermediateTranslation`, `WrapExportedEnum`, `GDQOmnibarListItemElement`, `AssetWithMeta`, `DaffCategoryPageLoadSuccess`, `AddressSpace`, `TranspileResults`, `IconDefinition`, `LineView`, `QLabel`, `ChartState`, `GitBranchReference`, `BuildNoChangeResults`, `GX.FogType`, `SocketMessage`, `DynamicInputModel`, `FSM`, `StatePropertyAccessor`, `TextSpan`, `SCN0_Camera`, `IVector2Like`, `DatabaseType`, `BitcoinNetwork`, `TNew`, `ZAR`, `DataItems`, `Left`, `GetDomainDeliverabilityCampaignCommandInput`, `CGPoint`, `IEventSubscription`, `Scanner`, `BookingService`, `OpenYoloInternalError`, `CharList`, `WorkspaceSettings`, `DataKeyTypes`, `AddressChainType`, `OAuthAuthCode`, `ConnectedSpaceGraphics`, `GlobalStyleComponent`, `InitState`, `LanguageServerInterface`, `ClothingProps`, `DataPumpExcludeParameters`, `MiddleColumnPadCalculator`, `ViewQueriesFunction`, `IconProp`, `Arrayable`, `StarPiece`, `LayoutChangeEvent`, `TReturn`, `QRCodeNode`, `PrStatistics`, `CpuInfo`, `HsLayerManagerService`, `HasAttributeExpr`, `ManifestBuilder`, `PromptModule`, `Migration`, `RestEndpoint`, `PaginateConfig`, `ParsedColorValue`, `SerializationOptions`, `TextPlacements`, `UnitNormArgs`, `VerifyConditionsContext`, `Degrees`, `LayerPanel`, `TestCallback`, `OhbugConfig`, `EntitySchemaField`, `EntityActionFactory`, `SqlHelper`, `I18nFeature`, `SavedObjectReference`, `ServiceModule`, `ApiRx`, `DescribeCodeReviewCommandInput`, `ServerClient`, `HighContrastMode`, `BackendService`, `IRead`, `PersistedStore`, `ICompileOptions`, `RuntimeEnvironment`, `LogStackedLayout`, `SpriteBaseProps`, `IParticleSystem`, `LegacyAPICaller`, `OutputPort`, `TXReport`, `DispatcherEmitter`, `PrepareOptions`, `ThemeSettingsBreakpointAny`, `DockerFacade`, `JSDocNullableType`, `SecureNoteData`, `SpotMarketConfig`, `EncoderOptions`, `UpdateClusterResponse`, `FilterExpression`, `StorageManagementClient`, `ContractAddresses`, `LiteralTypeNode`, `Readme`, `DisplayOptions`, `SystemManagerImpl`, `egret.Shape`, `RedisStore`, `TestingWindow`, `LitvisDocument`, `VideoType`, `HubProduct`, `ModelCache`, `CSC`, `NotificationRequest`, `Statistics`, `WriteOptions`, `RTCRtpSendParameters`, `Try`, `OpenSearchDashboardsReactNotifications`, `DocgeniHost`, `RBNFSetBase`, `ListenerOptions`, `Locatable`, `PureTransitionsToTransitions`, `GfxInputLayoutP_GL`, `CreateWebACLCommandInput`, `PrivateAuthenticationStore`, `ProfileState`, `MikroORMOptions`, `IUserDto`, `GeomGraph`, `TransactionsBatch`, `ConfigHandler`, `MatchedPointType`, `AppTheme`, `LogObject`, `ViewportCallback`, `DateFormat`, `LiveMap`, `EntityCompanionDefinition`, `CorrelationIdGenerator`, `ELEMENT`, `IVConsoleNode`, `KCDLoader`, `IBooleanFlag`, `StackItemLike`, `PositionNode`, `Diffs`, `NotificationDataOptions`, `DomainBudget`, `PreKeyBundle`, `SCN0_LightSet`, `IChoiceGroupOption`, `ts.ForInStatement`, `TimeTrackingEntryIded`, `UrlWithStringQuery`, `VariableStatement`, `ObjectContext`, `Gui.Widget`, `AttributeReader`, `IVirtualDeviceValidatorResultItem`, `RQuota`, `NavigationProps`, `CreateIdentityProviderCommandInput`, `RestResponse`, `IdempotentParameterMismatchException`, `CapacityReservation`, `ChannelUpdateMessage`, `FieldRenderProps`, `IMemoryDb`, `MapFnOrValue`, `JSONSchemaSettings`, `IDeltaManager`, `FriendshipPayload`, `VTTCue`, `TypingsData`, `React.FormEventHandler`, `InstantComponentTransformation`, `NearestPointOnLine`, `ApiDoc`, `SimpleItemPricing`, `Pagerow`, `MappingItem`, `SelectorItem`, `TriumphRecordNode`, `OpenSearchDashboards`, `KeyCurve`, `Point3d`, `SeriesParam`, `Index`, `MarkdownService`, `HTMLTableElement`, `ToRunType`, `ReadModelStore`, `Array2DHashSet`, `VisualizeInput`, `FileWriter`, `TransactionInfo`, `ViewStateProps`, `ItemValue`, `Dishes`, `AddApplicationReferenceDataSourceCommandInput`, `SearchConfig`, `PlayerId`, `PopupDispatcher`, `ModifyEventSubscriptionResult`, `Attr`, `ALObjectWizardSettings`, `InstanceSummary`, `UtilityService`, `IBsLoadingOverlayOptions`, `MatRadioButton`, `DocumentSelector`, `TestingProject`, `ProviderItem`, `ResizeOptions`, `HistoryQuery`, `FilterMetadataStatusValues`, `BlockType`, `RepositoryRepository`, `EditorInspectorService`, `SessionRequest`, `FormBuilderService`, `Repeat`, `IAmazonNetworkLoadBalancerUpsertCommand`, `GherkinDocument`, `Quaternion`, `LangType`, `DataLayout`, `RumInitConfiguration`, `MinionStatus`, `DAL.DEVICE_ID_DISPLAY`, `PullState`, `SpacePropValues`, `Moon`, `VisibilityGraph`, `ClearingHouse`, `Benchmark.Event`, `FilterHeadersStatusValues`, `RedirectTask`, `IPackagesService`, `SpriteService`, `ConversationRecognizer`, `AutoconnectConfig`, `IAppDef`, `UpdateVpcLinkCommandInput`, `GLfloat2`, `BodyInit`, `StagePanelsManager`, `IParallelEnumerable`, `ifm.IHeaders`, `FeeType`, `postcss.Container`, `AzureNamingServiceOptions`, `request.Response`, `SymbolVisibilityResult`, `LngLatBounds`, `DBusClient`, `EventOptions`, `DataSourceService`, `MatrixItem`, `ErrorToastOptions`, `SplitAreaDirective`, `SelectionState`, `ConfigRuntime`, `HTMLIonContentElement`, `IWorkflowDb`, `ActionTicket`, `IUIField`, `MultiRingBufferReadableStream`, `QueryLanguage`, `SparqlItemService`, `AsyncQuery`, `TreeViewExpansionEvent`, `RadioGroup`, `SliderState`, `CommerceLayerConfig`, `DebugProtocol.AttachResponse`, `BuildPageRangeConfig`, `apid.RuleSearchOption`, `PokemonSet`, `ElementGeometryResultOptions`, `SubscribeResult`, `callback`, `CustomState`, `Next`, `Ids`, `OcsShare`, `ReplyChannelRangeMessage`, `IdType`, `BinaryValue`, `FieldView`, `OpenAPIParser`, `DescribeServicesCommandInput`, `FaastError`, `BrowserWindowRef`, `dia.Paper`, `SWRInfiniteKeyLoader`, `TerminationStrategy`, `AddArrayControlAction`, `SDKBase`, `Boolean`, `SwitcherItemWithoutChildren`, `Nuxtent.Query`, `TileDescriptor`, `ApplicationCustomizerContext`, `SpeechContext`, `TaskEither`, `BinaryExpression`, `IMyOptions`, `SplitTest`, `LineString`, `SVSize`, `TileMeta`, `NavigationTreeViewModel`, `PaymentsError`, `NodeInstance`, `ITranslation`, `ModuleNode`, `DeleteObjectCommandInput`, `CreateListenerCommandInput`, `ISimpleGridEdit`, `ZeroXPlaceTradeDisplayParams`, `SelectorCache`, `PlotAreaOptions`, `TypeElement`, `JsonRpcSigner`, `KanbanSplitResult`, `DecoderResult`, `TimeBucketsConfig`, `IgnoresWrappingXmlNameCommandInput`, `KeyType`, `apid.ProgramGenreLv1`, `QuicTags`, `DataMapper`, `EfParticle`, `OncoprintModel`, `FileSystemAdapter`, `Watching`, `virtualFs.Host`, `MaestroTipoModel`, `CoreDependencies`, `MapPartsShadowType`, `ClientLibraryState`, `ClassNameCollector`, `LocalFileName`, `FileUpload`, `DbList`, `CompleteLayerUploadCommandInput`, `OrganizationConfig`, `alt.Entity`, `WebHook`, `ForgedResponse`, `GX.IndTexBiasSel`, `DiffColumn`, `OnCameraFrameCallbackResult`, `CertificateDTO`, `tf.Tensor3D`, `InjectedIntl`, `EventTypes`, `AgentPolicy`, `ILocale`, `ArgonWebView`, `IdeaTags`, `EPerson`, `PlaybackState`, `IItemUpdateResult`, `IInstantiationService`, `EventBuilder`, `ISolutionWithFileIds`, `CompositeCollectionJavaIterator`, `ErrorCorrectionLevel`, `CameraContext`, `IWhitelistUserModel`, `ts.AnyObject`, `TextChunk`, `BemToBlockClassMap`, `DateHelperService`, `CkbTxInfo`, `UniListItem`, `PendingSuiteFunction`, `TexChunk`, `Suite`, `SelectedGroups`, `SonarQubeMeasureResponse`, `AuthenticationHeaderCloud`, `ResolvedGlTF`, `ConnectListener`, `IForwardIterator`, `SelectionMode`, `FilterStateStore`, `MdcDialogConfig`, `d.TransformCssToEsmInput`, `CDPSession`, `IRawOperationMessage`, `DeleteWorkspaceCommandInput`, `FilterComponentSettings`, `DialogSource`, `PlasmicLoaderConfig`, `msRest.HttpRequestBody`, `RxjsPipeline`, `CdkTableDataSourceInput`, `DataDirection`, `SequenceExpression`, `FunctionToMemoize`, `PrimaryFeaturePrivilege`, `TCacheKey`, `ScreenState`, `ResourceFetcher`, `s.CodeGeneratorRequest`, `HdPrivateKey`, `TSFile`, `RumPerformanceEntry`, `VertexAnimationEffect`, `HierarchyParents`, `MaybePatterns`, `ActionsService`, `ElasticsearchBoolQueryConfig`, `GrabListener`, `SchemaProvider`, `RARCFile`, `Matrix2x3`, `AWS.DynamoDB.DocumentClient.Key`, `OpenSeaPort`, `DesugaringContext`, `SessionOnDisk`, `SavedObjectsClientProvider`, `FieldFormatter`, `TypedDictEntry`, `UpdateDistributionCommandInput`, `ListSourceApplicationsRequest`, `AnimatedClock`, `IComponent`, `TypeAnnotationNode`, `UserMedia`, `UrlPropertyValueRenderer`, `PublicAppInfo`, `NZBResult`, `IMyDate`, `AbiOwnershipBody`, `Air`, `DeviceClass`, `IntersectionObserver`, `TrackingInfo`, `DirectSpiral3d`, `LoginSuccessCallbackResult`, `ListServiceQuotasCommandInput`, `ts.GetAccessorDeclaration`, `AddTagsInput`, `ClassifyService`, `TokenFlags`, `RoleContext`, `ScopeMap`, `ChannelEthContract`, `AutoImportSymbol`, `SpreadAnalysisResult`, `ChunkContentCallbackArgs`, `DrawerControl`, `DecodedToken`, `ClientStatus`, `GithubGlobalConfig`, `IInputList`, `DefineComponent`, `UITextPosition`, `PrivateUser`, `CombinedJobWithStats`, `ReduceArguments`, `IStateContext`, `FramerAPI`, `Dialog`, `IExecutionContextProvider`, `Affect`, `FrameEntryType`, `ImagePipeline`, `IntegrationTenantService`, `Articles`, `RenderRule`, `TypedAxiosResponse`, `IPlugin`, `ContributionProposal`, `StartStopSingle`, `IndexerManagementModels`, `TransferDetails`, `ACLService`, `IParameterDefinition`, `ValidationRuntimeOptions`, `TLE.FunctionSignatureHelp`, `UnusedAttribute`, `FilterBuilder`, `SupervisionContext`, `ConversionType`, `RequestApproval`, `SnackbarType`, `ResolutionConfig`, `Aggs`, `FadingFeatureParameters`, `THREE.OrthographicCamera`, `MessageResp`, `ISetCategoricalFilter`, `LegendPosition`, `THREE.WebGLRenderTarget`, `FTPResponse`, `SuiLocalizationService`, `CiBuildInfo`, `RangeFieldMeta`, `RenameModuleProvider`, `UnformattedListItem`, `HealthCareApisClient`, `PermissionOverwrites`, `ProjectLocale`, `IAssetTag`, `ProductControlState`, `ObjectId`, `SugiyamaLayoutSettings`, `InterleavedBufferAttribute`, `DeleteDatasetResponse`, `ViewerEventType`, `ITagsState`, `CurrentMoveInfo`, `TouchList`, `IMask`, `RecurringBill`, `CSSStyleDeclaration`, `HomogeneousPatternInfo`, `TransitionDoneFn`, `SubscriptionDiagnosticsDataTypePriv`, `ConnectController`, `WorkspaceConfiguration`, `GenericType`, `OauthSession`, `IProfile`, `VertexDeclaration`, `TFLite`, `LinearGradient`, `ProcessQueue`, `Peer`, `ClassAndSelector`, `EPerspectiveType`, `TableState`, `Projector`, `ts.TransformationContext`, `RangeContext`, `Decorations`, `TimeSeriesMetricDataPoint`, `ICustomFunctionParseResult`, `DateRangeInputProps`, `HSD_TEArg`, `ForwardingConfig`, `RpcRouter`, `App.storage.IStorageApiWrapper`, `Chart`, `CallbackEntryHelper`, `BooleanNode`, `SGroup`, `Patch`, `ElasticsearchConfigType`, `QueueModel`, `IVisibilityJobPostInput`, `DecoratorFn`, `MetronomeNote`, `BundlingOptions`, `CacheContext`, `ethersProviders.Provider`, `PrimaryButtonProps`, `UniLoginSdk`, `AnalyzableProperty`, `BatchProcessResponse`, `L.List`, `TextToSpeechClient`, `LastfmTopTracks`, `StorageState`, `AnalysisResult`, `StringListNode`, `nock.Scope`, `CreateProjectRequest`, `StyleClasses`, `RPCRequest`, `IConfigurable`, `DeleteYankChangeAction`, `SVGPolygonElement`, `TransformId`, `GX.TexGenMatrix`, `TwoFactorEmailRequest`, `StubBrowserStorage`, `IFooter`, `ConnectionEvent`, `RenderOutput`, `CookieService`, `BinaryEngine`, `TimePoint`, `TagModel`, `RoverWorkload`, `TryPath`, `CodeBuild`, `Intl.DateTimeFormat`, `ExecutionState`, `SignatureData`, `Continue`, `UserPositionsAccount`, `ShorthandProperty`, `FilterFormatterFunction`, `RMSPropOptimizer`, `MetaData`, `AuthTokens`, `GanttGroupInternal`, `AnyState`, `HomebridgePlugin`, `ThyOptionSelectionChangeEvent`, `Db`, `ITimelineData`, `ExtractControlValue`, `Host`, `TypeScriptServerHost`, `OrderBy`, `IFormatterParserResult`, `ace.Editor`, `ChannelMessageUpdate`, `IDEntry`, `EvaluatorFlags`, `InitializationData`, `CephLine`, `SampleUser`, `NineZoneStagePanelManager`, `EditPhotoDto`, `FeedbackActions`, `InitAckChunk`, `comicInterface`, `GethRunConfig`, `paper.CompoundPath`, `VercelClientOptions`, `ProjectVersionMeta`, `DeleteStorageObjectsRequest`, `CurrencyOption`, `TransportTime`, `puppeteer.JSHandle`, `SubscribeState`, `MiddlewareType`, `MutableColorRgba`, `RunContext`, `CtxLike`, `ReminderFormatType`, `SignatureHelpParams`, `NineZoneStagePanelManagerProps`, `Before`, `ImportRecord`, `MethodVisitor`, `PropertyDeclarationStructure`, `NgModule`, `MessageKind`, `ResourceField`, `TMethod`, `AggregatedColumn`, `Magma`, `MouseEvent`, `UpdateStreamCommandInput`, `EnvoyHttpRequestInit`, `TimestampManager`, `PartsType`, `TodoListModule.Actions`, `ExtractActionFromActionCreator`, `Languages`, `SymbolIntervalFromLimitParam`, `sdk.SpeechRecognitionCanceledEventArgs`, `AppImages`, `IClusterContext`, `Networks`, `MetadataSchema`, `HTMLHRElement`, `I18nStart`, `DeserializeWireBaseOptions`, `HttpHandler`, `ContractTransactionOverrides`, `SystemPortalSelectionTag`, `DotnetInsights`, `DebugProtocol.ThreadsResponse`, `MigrationLifecycleStates`, `MessengerData`, `WritePayload`, `ParamsOfAppDebotBrowser`, `DatasetResource`, `PrincipalTokenCurveTrie`, `chrome.runtime.Port`, `MapPoint`, `Filler`, `DigitalComponent`, `Entity`, `UserRoleService`, `TransactionFormState`, `JsxAttributes`, `DropdownProps`, `Clipper`, `AssetEvent`, `OutputType`, `Arity`, `Dictionary`, `TestResource`, `ConsoleTransportInstance`, `IncrementalQuinTree`, `UseGoToFormConfig`, `UIFont`, `triggeredTrap`, `FlowExhaustedMatch`, `vscode.OpenDialogOptions`, `FormFieldPreviousValueObject`, `AuthActions`, `VideoRateType`, `ISnapshotOptions`, `GitBuffer`, `Contributor`, `AvailabilitySlotsService`, `AccountStellarPaymentsConfig`, `ViewSize`, `BrowseCloudBatchJob`, `SearchItem`, `VideoPreference`, `NextCallback`, `Processed`, `LambdaFunction`, `DropResult`, `IModDirection`, `IApiStashTabSnapshot`, `OrganizationalUnit`, `ClientCredentialsResponse`, `StateReaderObservableEither`, `VersionArray`, `TrackedAbility`, `NormalizeContext`, `SubscribedObject`, `OutputChannel`, `BuildingFacade`, `LocationDescriptor`, `NotificationCallback`, `StickyVirtualizedListProps`, `Unbind`, `ICommitAuthor`, `Models.OrderStatusUpdate`, `StateWrapper`, `PkgJSON`, `ModelSpec`, `IMedia`, `RouteAction`, `BindingDescriptor`, `ELineTypes`, `LimitOrder`, `HotModuleReplacement`, `IOwnProps`, `ITaskAgentApi`, `BotTelemetryClient`, `TypeDefinition`, `MessageStatus`, `GenericTagId`, `RBNFRule`, `LnRpc`, `BoosterConfig`, `babel.ObjectExpression`, `IProblem`, `ContractMethodDescriptorClient`, `TaskResult`, `FunctionArgument`, `IAchievement`, `database.DataSnapshot`, `Formula`, `FindListOptions`, `EnabledPoliciesPlan`, `BufferArray`, `EnvoyContext`, `EntityMaterialParameters`, `Sync`, `CheckNodeResult`, `ODataPathSegmentsHandler`, `CodeBlock`, `ICredentialType`, `PlayOptions`, `WindowProtocol`, `UserRepresentation`, `IExtraArgument`, `SyncDBRecord`, `RecursivePartial`, `TriggerType`, `IconifyBrowserCacheType`, `coreClient.FullOperationResponse`, `AuthorizedClientRequestContext`, `ScriptLoaderService`, `BindingMetadata`, `MatDialogContainer`, `ServerRegion`, `CryptoCurrency`, `ProgressHandler`, `StringTable`, `SelectableListState`, `DataflowState`, `SplitLayoutNode`, `PoseNetConfig`, `UseFormValues`, `ConditionTypeEnum`, `UpdateUserCommandInput`, `SectionComponent`, `IModify`, `WifiNetwork`, `IKeyboardFeatures`, `IScalingPolicy`, `TestFormComponent`, `FormattedExecutionResult`, `WorkflowModel`, `Namespace`, `AnnotationProviderBase`, `FirebaseApp`, `StylableTransformer`, `EidasResponse`, `CppRequestSpan`, `LangiumLanguageConfig`, `Tests`, `ParsedData`, `Flattened`, `DragHandle`, `TransitionService`, `FormatterConfig`, `Crumb`, `ListSettings`, `CompilerTargetHandler`, `HandPoseOperatipnParams`, `THREE.Vector3`, `OpeningHour`, `CookieSerializeOptions`, `DemoMeta`, `StringToUtf32`, `fs.ReadStream`, `ValidateResult`, `AggsStartDependencies`, `DropAction`, `CGAPIResourceHandle`, `ColorObject`, `DraftEditorCommand`, `PvsResponse`, `ManagementDashboardForImportExportDetails`, `MqttClient`, `Singleton`, `ErrorMessages`, `Facebook`, `bindable.BindingOptions`, `PlayerViewCombatantState`, `t.AST`, `Attendee`, `StatefulChatClientWithEventTrigger`, `OperatorToken`, `Ped`, `requests.ListViewsRequest`, `PanelSide`, `ListWorkRequestErrorsRequest`, `JsonClassTypeOptions`, `TDiscord.MessageReaction`, `ParsedNumber`, `KnownFile`, `NodeOutput`, `PDFTextField`, `QueryCreateSchema`, `CancellationId`, `IICUMessageTranslation`, `SqliteStatement`, `EdmxEnumMember`, `IHotKeyConfig`, `ValueAxis`, `ChangesType`, `LayoutElement`, `FeatureManager`, `LCH`, `ex.Scene`, `KeyVaultManagementClient`, `StyleResourcesLoaderNormalizedOptions`, `VerifiedStateUpdate`, `Taint`, `IAureliaClassMember`, `Toggle`, `ITargetReference`, `NofloComponent`, `RequestQueryParser`, `WorldBuilder`, `TestPage`, `CellRenderer`, `MediationRecipientService`, `BehaviorDescription`, `IApiServer`, `FindWithRegexCb`, `TrezorTransport`, `ICreatorOptions`, `ObjectRemover`, `ActivityService`, `FibaroVenetianBlindCCSet`, `WithdrawStakingRewardUnsigned`, `InternalServerErrorException`, `FeatureItem`, `V1DeleteOptions`, `ObservableThese`, `CodeMirror.Position`, `JsxAttribute`, `NzNotificationService`, `ConfigMigrator`, `GoogleAuthProvider`, `StateDecoratorAction`, `Marks`, `SVGStyle`, `UpdateDomainResponse`, `SafeParseReturnType`, `ArcadeBody2D`, `HalResource`, `BoardEvent`, `TreeviewItem`, `ParsingExtension`, `LinePointItem`, `TextVerticalAlign`, `ICircle`, `CreateGroup`, `NamedTensorMap`, `ExecuteResult`, `React.ReactNodeArray`, `server.TextDocument`, `LoadAction`, `UrlMapping`, `d.ComponentRuntimeMembers`, `PosSpan`, `SingleOrMultiple`, `DepListener`, `requests.ListStreamsRequest`, `JNICallbackManager`, `NavigationEvent`, `TSAudioTrack`, `ICancellable`, `SignalingClientSubscribe`, `ViewDefinition`, `Lane`, `ResourceConflictException`, `EventStore`, `AccountDetails`, `DOMInjectable`, `ErrorLike`, `ICompetition`, `NodeWithScope`, `BaseNode`, `DevtoolsInspectorState`, `RegionInfoProvider`, `C3`, `DebugProtocol.SetBreakpointsArguments`, `MVideo`, `MDCDrawerAdapter`, `ElasticSearchOptions`, `IProductCreateInput`, `IRating`, `MdxModel`, `apid.GetReserveListsOption`, `ExecutionRole`, `Stylable`, `BoosterGraphQLDispatcher`, `TuxedoControlCenterDaemon`, `RestElement`, `RaguServerConfig`, `RuntimeDatabase`, `PlaceholderReference`, `TrimmedDataNode`, `NavigationBarNode`, `TokenizerState`, `FormFieldType`, `KudosPollService`, `IConfirmProps`, `NamePath`, `ISubscription`, `requests.ListPublicationPackagesRequest`, `Archive`, `TextAlign`, `InstancedMesh`, `UserPhotosState`, `Z64Online_EquipmentPak`, `SnippetModel`, `SpriteVID`, `EncodeOption`, `GetDomainItemsFn`, `InterceptorManagerUseParams`, `ReportingDescriptor`, `JsxFragment`, `GroupInput`, `requests.ListConfigurationsRequest`, `EnhancementCache`, `ExtrusionFeature`, `BasicBlock`, `UnbindFn`, `TextDocumentContentProvider`, `CompileState`, `GroupMember`, `PageDependencies`, `HeatmapVisualizationState`, `MinMaxConstraint`, `UIDialog`, `CallSite`, `IMappingState`, `MockOptions`, `TranslatorService`, `ChemController`, `EffectPreRenderContext`, `ErrorTransformer`, `ToggleCurrentlyOpenedByRoute`, `MomentData`, `AgeRepartitionType`, `ITransitionData`, `TuplePage`, `PumpCircuit`, `CalendarContext`, `MspDataView`, `HdStellarPayments`, `ComputedStyle`, `IProjectWizardContext`, `TEX1_TextureData`, `MeiliSearch`, `CoreImageEnt`, `ID`, `ManyToManyPathMap`, `HookReturn`, `CasesClientMock`, `UA`, `Solar`, `PrismaClientRustPanicError`, `AnnotationControllable`, `EmbeddedViewRef`, `AsyncHierarchyQuery`, `ProjectionMetadata`, `NotificationStartedInfo`, `ISubView`, `Keymap`, `GetDeviceCommandInput`, `IterationTypes`, `BookmarkTreeItem`, `CursorQueryArgsType`, `requests.ListHttpRedirectsRequest`, `StaticConfig`, `Models.Timestamped`, `IEmailOptions`, `ELU`, `unwrapContext`, `SmallMultiplesSpec`, `NativeStorage`, `ast.QuoteNode`, `TestStepResultStatus`, `MatrixDynamicRowModel`, `GetTokenResponse`, `ITransactionData`, `AriaLivePoliteness`, `CliScriptGenerator`, `ThyFormValidatorGlobalConfig`, `IDynamicPerson`, `QObject`, `IHubSearchOptions`, `JestExtRequestType`, `PointModel`, `JsonUnionsCommandInput`, `PostProcess`, `Model.Element`, `TokenDocument`, `requests.ListIPSecConnectionTunnelSecurityAssociationsRequest`, `StepVariable`, `sdk.TranslationRecognizer`, `SupervisionCCGet`, `HostStatus`, `CmsService`, `J3DModelData`, `ServiceList`, `ApplicationCommand`, `IIconItem`, `Pick`, `RecvDelta`, `RemoteRenderInfo`, `AccountStatus`, `ClassProperty`, `ClassResources`, `PrismTheme`, `UnitOfWork`, `pxt.Asset`, `ContainerRegistry`, `CoreTypes.TextAlignmentType`, `InternetGateway`, `messages.TestStepResultStatus`, `AqlQuery`, `OptionsService`, `UserAsset`, `TreeViewInfo`, `Strings`, `OutputGroup`, `pf.StackContext`, `SchemaValidatorFunction`, `ListContext`, `DataEntity`, `IGetTimesheetInput`, `ModdedDex`, `html.Element`, `ts.ArrayTypeNode`, `ToggleType`, `PartyCreate`, `OptionalObjectSchema`, `TransportConfiguration`, `MapLeafNodes`, `ReadOnlyReference`, `PawnFunction`, `HostState`, `DeleteApplicationOutputCommandInput`, `ServiceBase`, `IEndpointSpec`, `DispatchFunction`, `String`, `IInvoice`, `RTCPeerConnection`, `Parser.SyntaxNode`, `TreeModelNodeInput`, `LoopConverter`, `TypeOrmHealthIndicator`, `TranslationWidth`, `Http3RequestNode`, `QuestionStatus`, `RelationPattern`, `ImportNameWithModuleInfo`, `ParsedTsconfig`, `WayPoint`, `SharedDirectory`, `InvalidArnException`, `IQService`, `LocationInfo`, `RoutableComponent`, `MuteConfiguration`, `AlainAuthConfig`, `CreateScriptCommandInput`, `XMLElement`, `FourSlash.Range`, `Accessibility.ChartComposition`, `StakingCall`, `HtmlTag`, `RouteParam`, `BrowserLaunchArgumentOptions`, `SavedObjectOpenSearchDashboardsServicesWithVisualizations`, `FontInfo`, `API.storage.PrefObserverFactory`, `ILoader`, `Timetable`, `SliceAction`, `TSelections`, `AsyncHooksContextManager`, `Multicast`, `NativeView`, `FeatureKibanaPrivileges`, `Variables`, `ImportLookupResult`, `SecretManagerServiceClient`, `GlobalEventDispatcher`, `IVideoPlayerState`, `RedditComment`, `THREE.ShaderMaterialParameters`, `PathParams`, `CopyResults`, `requests.ListVnicAttachmentsRequest`, `Nameserver`, `AudioContextManager`, `Wiki`, `ConfigSetter`, `FSOperator`, `PyrightJsonResults`, `StreamReader`, `vscode.Selection`, `CreateEventSubscriptionCommandInput`, `VisitedItem`, `DiscordUser`, `InputType`, `IComponents`, `OctokitProvider`, `TestConfig`, `GenericRequestMapper`, `PropertyChangeData`, `MentionsState`, `paper.ToolEvent`, `KeyCode`, `L.Map`, `WlPeer`, `BaseAdapterPool`, `EnumTypeComposer`, `HypermergeWrapper`, `ProjectConfiguration`, `CompletionEntryDetails`, `IDOMRule`, `IGitAccount`, `IPluginAuth`, `V1CustomResourceDefinition`, `LocationChange`, `RulesProvider`, `AddressNode`, `requests.ListProtectionRulesRequest`, `Synthetic`, `UpdateCommand`, `UIViewAnimationTransition`, `Receipt`, `AddToLibraryActionContext`, `kChar`, `ZesaruxCpuHistory`, `PopupOptions`, `OwnProps`, `EventForDotNet`, `ListDeploymentsCommandInput`, `ContractsSection`, `IDatepickerLocaleValues`, `AuthorizationService`, `IOSDependencyConfig`, `StorageHelper`, `TimerInfo`, `ChannelMessageAck`, `CardRequirements`, `Danmaku`, `ListWorkRequestsResponse`, `INgWidgetEvent`, `ScaffdogError`, `PrimedGroup`, `TiledMapFeatureData`, `LogSampleTimestamp`, `DAL.DEVICE_ID_BUTTON_A`, `TLE.FunctionCallValue`, `ClippedRanges`, `AlignmentDirectional`, `AbstractControlState`, `ResolvedFunctionTypeParam`, `Technical`, `DirectiveHook`, `NTPTimeTag`, `FileBrowser`, `ICompareValue`, `MiRectConfig`, `AnyShape`, `ISeriesApi`, `EditModes`, `DecorateContext`, `TemplateExecutor`, `JSXContext`, `ContractFraudProof`, `BubbleSeries`, `LifelineHealthCheckResult`, `HitSensor`, `ViewAction`, `MatomoTracker`, `PanInfo`, `VectorOrList`, `Static`, `Distribution`, `KirbyAnimation.Duration`, `DAL.DEVICE_ID_BUTTON_AB`, `DeleteDetectorCommandInput`, `DeployLocalProjectConfig`, `RouterConfigOptions`, `SPDestinationNode`, `StandaloneDb`, `ClientAPI`, `MenuItemType`, `RouteComp`, `ConnectionPool`, `estypes.SearchHit`, `ContractInstance`, `Unregistration`, `IrecService`, `RouteSegment`, `AccessorCache`, `ConfigMap`, `OutHostPacket`, `FlipSetting`, `CookiesFilterParams`, `LiteElement`, `Htlc`, `SignalRConfiguration`, `NetworkPluginID`, `IMidwayContainer`, `Pair`, `ActionPlugin`, `DeleteSessionCommandInput`, `TransferItem`, `MessagingOptions`, `IUserRole`, `YearProgressModel`, `UpdateRegistryCommandInput`, `BinSet`, `TELibCall`, `FIRQuerySnapshot`, `PresentationTreeDataProvider`, `ITooltipProperty`, `Token`, `GatewayConfig`, `sinon.SinonSpy`, `MagitRemote`, `RequestPayload`, `TextOrIdentifierContext`, `IAuthUser`, `TestingUser`, `GUIController`, `FilterDefinition`, `SpriteArray`, `JsxChild`, `ExistingAccountError`, `ResponsiveProperties`, `HTMLIonToastElement`, `ObjectID`, `VsixInfo`, `DescribeHomeRegionControlsCommandInput`, `Tooltip`, `ImportNamespace.Interface`, `QuadrantDirection`, `RunLengthChunk`, `Keplr`, `DocumentSymbol`, `VideoInputDevice`, `common.Region`, `VisibilityMap`, `PopupManager`, `CallMethodResult`, `ListChannelMessagesCommandInput`, `CancelSubscription`, `PackageFiles`, `IConfiguration`, `TestEntry`, `EYaml`, `RouterDirection`, `TList`, `DeleteUser`, `CacheValue`, `PDFAcroTerminal`, `ImgAsset`, `StatefulCodeblock`, `SystemStats`, `ShareUserMetadata`, `SlideDirection`, `EventMessage`, `Dereferenced`, `PolymorpheusContent`, `IPageModel`, `InjectorServer`, `Events.pointerwheel`, `WorkspaceHost`, `TypesImportData`, `MalformedPolicyDocumentException`, `MigrationDiff`, `Vis`, `DiscogsReleaseInfo`, `SxParserState`, `jsPDF`, `WssRoom`, `SyncStore`, `HsLayerDescriptor`, `IdeaEntity`, `IBranding`, `CopyDescriptor`, `CallStatus`, `StatusAction`, `AggsCommonSetup`, `types.IActionContext`, `Hub`, `StellarSignatory`, `InteractionSettings`, `FlatVector`, `TextDocument`, `Contract`, `INestMicroservice`, `TestSourceIO`, `LinkedHashMap`, `Portable`, `TronUnlock`, `Generics`, `instantiation.IConstructorSignature8`, `PublicUser`, `PeerSetupWithWallets`, `vec4`, `Multi`, `RegInfo`, `monaco.editor.IStandaloneCodeEditor`, `XLSX.WorkBook`, `ZoomSettings`, `AbstractVector`, `StatusCodes`, `TransientBundle`, `GoogleAnalyticsService`, `uproxy_core_api.Update`, `GitTagReference`, `NotificationColumnFilters`, `Registration`, `EpochIteratorConstructor`, `TextureState`, `Colord`, `IVocabularyTag`, `BoardSlice`, `XYState`, `ImageData`, `FunctionC`, `MockModelRunner`, `ParserEnv`, `AnimGroup`, `InstanceNamedFactory`, `Tensor2D`, `JSX.TargetedKeyboardEvent`, `VisTypeDefinition`, `Operands`, `EChartOption`, `BackupRequest`, `IScalingProcess`, `ReactionMenuState`, `null`, `StudyConstraint`, `HsLayerSelectorService`, `StaticOperatorDecl`, `ApiKeyProps`, `d.CompilerJsDocTagInfo`, `FindManyOpts`, `ELBv2`, `BasePrismaOptions`, `InputControlVisDependencies`, `ErrorBarStrings`, `DiscussionReplyEntity`, `StoreEnhancerStoreCreator`, `WebGLRenderingContextExtension`, `EntityName`, `EnhancedGitHubEvent`, `ThyTableGroup`, `PiecePosition`, `InternalRouteInfo`, `IServerGroup`, `AssociationCC`, `CandleLimitType`, `HealthCheckService`, `LoadEvent`, `VersionedSchema`, `MissingItem`, `IGCNode`, `TokenVerifier`, `WillExecutedPayload`, `SomeInstance`, `BlockedRequester`, `ColorComponent`, `GithubAuthTokenRepository`, `LineItem`, `CellConfig`, `ResumeNode`, `MessageConversation`, `FakeNumericDataset`, `ApiChanges`, `MediaItem`, `EntityCollectionCreator`, `TimelineDivisionBase`, `SnapConfig`, `ReqWithUser`, `ColonToken`, `SkinId`, `BackstageItemsManager`, `ReadableStreamDefaultReadResult`, `StaticPathLoader`, `UpdateChannelResponse`, `Resolved`, `IconData`, `Tokens`, `DisposableObservable`, `ChartKnowledgeBaseJSON`, `LoadConfigInit`, `SelectionLocation`, `MIRInvokeBodyDecl`, `VisibleBoundary`, `GoogleWebFontData`, `WebhookPayload`, `MigrationsContract`, `KeyboardLayoutData`, `ComponentTable`, `d.SitemapXmpOpts`, `IMoveDescription`, `DirectoryWatcher`, `USampler3DTerm`, `KMSKeyNotAccessibleFault`, `MarkdownSimpleProps`, `IDelta`, `PropertyConverterInfo`, `FfmpegCommand`, `TypescriptServiceClient`, `StateTransition`, `MdcDialog`, `IAppState`, `SystemState`, `ClassLikeDeclaration`, `SymbolOptions`, `TokenConfigs`, `BinaryEncoding`, `IContainerType`, `PersistedLog`, `UsageCollectionPlugin`, `instantiation.IConstructorSignature6`, `IBlockchainObject`, `DecipherGCM`, `DecodeContinuouslyCallback`, `cloudwatch.Metric`, `TaggedState`, `AggTypeAction`, `JProject`, `LayoutOption`, `NETWORK`, `IFoundElementHeader`, `UserBuildConditionals`, `TreeResult`, `TensorOrArrayOrMap`, `EqualFunc`, `_Connection`, `ContentLayoutDef`, `CombinedField`, `Accent`, `SelectQueryBuilder`, `TransformerArgs`, `ItemContext`, `TrackInfo`, `ClickSource`, `IEmbedVideoOptions`, `ThyFlexibleTextComponent`, `PipelineNode`, `PayloadBundleSource`, `PaginationParams`, `vscode.Location`, `RepositoryCommonSettingValueDataType`, `TexturizableImage`, `ProviderInput`, `ICassExploreModuleState`, `HttpConfig`, `LanguageService`, `VariantType`, `HaliaPlugin`, `FeaturedSessionsActions`, `ChatFlowPack`, `LayoutPane`, `ThemesTypes`, `OrderedHierarchyIterable`, `MockResponseInit`, `MouseDownEvent`, `React.PropsWithoutRef`, `CollectionService`, `Blobs`, `ParameterToken`, `CaseReducerActions`, `Vec2Sym`, `PriceHistoryMap`, `DiffPatcher`, `DeleteContactCommandInput`, `JwtHeader`, `AnyTable`, `IMockEvent`, `ElementDefinitionContext`, `VersionConstraintContext`, `TruthTable`, `ISPTermObject`, `GfxrAttachmentClearDescriptor`, `HdLitecoinPaymentsConfig`, `Monad2`, `SchemaInput`, `TLeft`, `DisplayValuePropertyDataFilterer`, `CreateJoinQueryOptions`, `HeaderGetter`, `StorageModuleOptions`, `WorkspaceSetting`, `KintoObject`, `ReplayContext`, `HtmlProps`, `DocumentLink`, `ModLine`, `IAstElement`, `ValueResolver`, `IRequestHeaders`, `CellPlugin`, `WebWorkerEnvironment`, `ArrayBufferLike`, `Entity.Status`, `NextPage`, `ConfigInfo`, `ExternalSourceFactory`, `OpenSearchInterval`, `IStyle`, `SignedByQuantifier`, `DecodeOutput`, `NzTabSetComponent`, `PlayerStatus`, `CardCommon`, `ConfigRoot`, `ExecutionStatus`, `CephAngle`, `TasksState`, `QueryResultProps`, `Rating`, `ExtendedUser`, `RebirthWindow`, `LogSource`, `P3`, `GridItemHTMLElement`, `GroupBy`, `ICheckboxProps`, `FsWriteOptions`, `GitService`, `d.HostRule`, `EntityMap`, `TransformCssToEsmInput`, `NullableLocatable`, `XSLTToken`, `PartialExcept`, `CellRepo`, `JavaScriptDocument`, `GroupOrName`, `LQuery`, `InvalidateMask`, `LanguagesEnum`, `ListContentConfig`, `PodSecurityPolicy`, `NativePlaceTradeChainParams`, `Github.PullRequestsGetResponse`, `BuildingTree`, `ViewportSize`, `DepthwiseConv2DLayerArgs`, `CommandLineParser`, `ScanArguments`, `IconSettings`, `ArmService`, `IDataState`, `Branched`, `CompletionContext`, `Klass`, `ManualConflictResolution`, `T5`, `JsonfyDatasource`, `DefinerClauseContext`, `JssState`, `NoneType`, `BoardBase`, `ObjectUpdatesEntry`, `ExceptionType`, `IEcsServerGroupCommand`, `SetOpts`, `TaskSpec`, `RestOrderbookRequest`, `DOMMatrixInit`, `Parallelogram`, `QualifiedValueInfo`, `VisualizeSavedObjectAttributes`, `GlobalParametersService`, `IPostMessageBridge`, `HelmManager`, `Dog`, `SignalRService`, `XmppChatAdapter`, `DataSink`, `RawBlock`, `Ninja`, `HybridOffsets`, `BrowserControllerReturn`, `SwitchWatcher`, `IntersectionInfo`, `SyncState`, `TypeClass`, `EventsFactory`, `DayCellStyle`, `ParsedStructure`, `Bucket`, `FunctionFragment`, `PopoverPosition`, `IOrganizationDepartmentCreateInput`, `TxParams`, `requests.ListLoadBalancersRequest`, `Hsv`, `CuePoint`, `BreakpointMap`, `Node.Node`, `ContentReference`, `RecordData`, `DropListRef`, `ethereum.CallResult`, `CLM.Template`, `UpdateState`, `FastFormFieldMeta`, `GeometricElement3dProps`, `ContractFunctionEntry`, `DeleteServiceCommandInput`, `ECH.CommandClient`, `ScopeType`, `FileTransport`, `ts.SignatureDeclaration`, `Graphic`, `DejaViewPortComponent`, `http2.ClientHttp2Session`, `CSS.Properties`, `DirectiveList`, `ComponentEnhancer`, `TransactionCache`, `ActionResult`, `MiToolsSyncData`, `PacketChunk.TypeTCCStatusVectorChunk`, `ElementGeometryInfo`, `configuration.LaunchConfiguration`, `CreateManyInputType`, `ClientCardIded`, `SecurityRule`, `CANNON.Vec3`, `d.SourceTarget`, `CompositeSubscription`, `Place`, `OptionalDefaultValueOrFunction`, `IpcAPI`, `BitcoinBalanceMonitor`, `PublicRelayerConfig`, `JobId`, `Biota`, `NodeCreator`, `ConciseBody`, `OpenNodeTracker`, `Degree`, `CeramicCommit`, `CreateAppFunction`, `ConflictNode`, `ResourceSource`, `Option`, `IncludeRecord`, `Cart`, `IRouteMatch`, `ResponsiveService`, `ChatMessage`, `RpcMessageData`, `FloatFormat`, `NewWindowWebContentsEvent`, `HitDetail`, `NexusScalarTypeDef`, `UseCaseExecutor`, `IUserOrganization`, `SegmentAPIIntegrations`, `Broker`, `DMMF.ModelMapping`, `Oni.Plugin.Api`, `TypeKindEnum`, `CorePreboot`, `Snake`, `MarkdownTreeNode`, `GetMeetingCommandInput`, `YRange`, `QueryMap`, `PackagedNode`, `AcceptTokenResponse`, `TransportRequestOptionsWithMeta`, `d.TypeInfo`, `SMTCallSimple`, `ClipRectAreaModel`, `HistoryValue`, `Rest`, `FakerStatic`, `AZDocumentSymbolsLibrary`, `ProjectPost`, `RulesClientFactory`, `SymbolData`, `CreateEmManagedExternalExadataMemberEntityDetails`, `GherkinLine`, `Commune`, `RelationIndex`, `Translator`, `CommonState`, `StreamDescriptions`, `ReturnCode`, `GitUser`, `NetworkSubgraph`, `BaseStateContainer`, `IMutableGridCategoryItem`, `ListMigrationsRequest`, `GenerateInFolderOptions`, `DeleteAssociationCommandInput`, `S1`, `ImportAdder`, `TurnContext`, `IHttpInterceptController`, `BaseName`, `requests.ListConnectionsRequest`, `DrawEvent`, `JoinedEntityMetadata`, `IICUMessageCategory`, `RewriteAppenderConfig`, `GenericCompressorProperty`, `AnalyzableNode`, `NoticeToastRequest`, `CategoryChannel`, `SignedCipherObject`, `FKRow`, `MetricService`, `LiteralTypeBuildNode`, `FragmentElement`, `DocumentInterface`, `AuthorizeConfig`, `EthArg`, `T9`, `PointerCoords`, `IFuture`, `CompleterComponent`, `OpenSearchDashboardsLegacyPlugin`, `TemplateOutput`, `ProjectionType`, `Bm.Dest`, `AR`, `ListServersCommandInput`, `inquirer.Answers`, `ListReservationsCommandInput`, `ICircuit`, `GroupedTask`, `OperationLoader`, `ParamFunction`, `TxOutput`, `Gunzip`, `ImageTemplate`, `DataGroup`, `SlashingProtectionBlock`, `AuthenticatedSocket`, `requests.ListImageShapeCompatibilityEntriesRequest`, `ForceGraphLink`, `IJsonDocument`, `SchemaProps`, `ECPair`, `SubtitlesState`, `ErrorCode`, `JQuery`, `NamedFragmentDefinition`, `KratosService`, `ClassName`, `TTK1AnimationEntry`, `RelayModernEnvironment`, `BullBoardRequest`, `WebpackConfigurator`, `TestContract`, `CloudFrontRequestEvent`, `ColumnChartOptions`, `AClassWithSetter`, `GeoLocation`, `DateRawFormatOptions`, `LoadOpts`, `WudoohStorage`, `MigrationItem`, `AuthTokenService`, `Mode`, `DomService`, `CertificateConfigType`, `ABLDocument`, `IErrorsBySection`, `GridCellParams`, `IAbstractGraph`, `ErrorHttpResponseOptions`, `AnyExpressionTypeDefinition`, `MappingLine`, `PUUID`, `AdapterContainer`, `Generations`, `SBDraft2CommandLineToolModel`, `SpriteState`, `PromiseMap`, `LogicalType`, `HttpResponseCreated`, `MockCallback`, `CipherView`, `FloodProcessEnv`, `NodeStack`, `Events.pointerdragleave`, `HasShape`, `TenantSettingService`, `RawTransaction`, `TabRepository`, `SelfList`, `MeasureUnit`, `FileStatusBar`, `OutputContext`, `HelloMessage`, `E2EElementInternal`, `express.Handler`, `QueryListsCommandInput`, `TextLayoutStyle`, `TimeQuery`, `AggName`, `requests.ListStacksRequest`, `ResourceOptions`, `OidcProviderService`, `BooleanFilterFunction`, `KanbanBoardRecord`, `DeleteCertificateCommandInput`, `TraceSet`, `Response.Wrapper`, `GraphProps`, `IntersectionObserverCallback`, `GundbMetadataStore`, `ColumnNode`, `TestWorkspaceFactory`, `Operation`, `ApplicationContext`, `ml.Element`, `ExchangeQueryService`, `LogLevelValues`, `TestDoc`, `ApiResource`, `CreateResourceCommandInput`, `ProjectedPoint`, `DropdownItem`, `CALayer`, `BuildEntry`, `requests.ListNotebookSessionShapesRequest`, `ICategoricalLikeColumn`, `PropsWithChildren`, `SafeElement`, `DebugSession`, `INavigationData`, `ServerOptions`, `LendingPool`, `OutputTargetCopy`, `PusherChannel`, `JwtToken`, `pino.Logger`, `GroupDescription`, `requests.ListComputeCapacityReservationInstanceShapesRequest`, `ScrollItem`, `NodeLoadInformation`, `IPagination`, `ChartDataPoint`, `ThemeContextType`, `ZoomLevels`, `RegisteredMessage`, `PushContextData`, `CodeScopeProps`, `LanguageTag`, `ArticleState`, `ProfileInfo`, `CategoryProps`, `GeographicCRSProps`, `MatchedSegments`, `TrackQueryOpts`, `ProtocolNotificationType`, `jwt.SignOptions`, `ServerUtil`, `d.ScreenshotBuildData`, `ElementAction`, `IDataFilter`, `ISequencedOperationMessage`, `PayloadMetaAction`, `EventNames`, `TimerOptions`, `TableOfContentsEntry`, `JsonAtom`, `IPersonaProps`, `Sampler2DTerm`, `EdgeProps`, `AST.OperationNode`, `PlugyStash`, `OperatorEntry`, `VisualSettings`, `BinaryToTextEncoding`, `FSError`, `BB.Activity`, `HttpLinkHandler`, `Basis`, `DeleteJobTemplateCommandInput`, `ColumnMeta`, `Variance`, `ElementFinder`, `ListChannelMembershipsCommandInput`, `AccountActions`, `CommunicationParticipant`, `QueryParameterBag`, `HealthChecker`, `ValidatorFunctionType`, `NormalizedProblem`, `IRowProps`, `JIssue`, `PartialPerspective`, `PlainData`, `Authorizer`, `SqliteDatastore`, `MsgDeleteProviderAttributes`, `CoreTypes.TextTransformType`, `GuildDocument`, `MatchedItem`, `LocaleType`, `MqttOptions`, `HttpErrorResponse`, `Web3.TransactionReceipt`, `IConfigurationComponent`, `IExpenseCategory`, `ClassAst`, `BinanceConnector`, `Update`, `SubmissionService`, `SourceConfig`, `EtaConfig`, `SearchServiceStartDependencies`, `V1ConfigMap`, `ProcessedImportResponse`, `VueApolloRawPluginConfig`, `InvalidRestoreFault`, `IReport`, `XAxis`, `HttpStart`, `DbBlock`, `SortablePlayer`, `Abi`, `MdcDefaultTooltipConfiguration`, `ClassListing`, `BuildDefinition`, `LineAnnotationDatum`, `DinoRouter`, `IQueryInput`, `DeleteReplicationConfigurationTemplateCommandInput`, `GLclampf4`, `ILayer`, `ast.Node`, `Whiteboard`, `SendMailOptions`, `RAL.MessageBufferEncoding`, `ShadowRootInit`, `coreAuth.TokenCredential`, `ResourceLabelFormatter`, `SearchForLife`, `UpdateTargetMappingsWaitForTaskState`, `Attribs`, `ActionCreatorWithOptionalPayload`, `AddEventListenerOptions`, `Forecast`, `EdmTypeField`, `RangeSet`, `PLSQLConnection`, `Dealer`, `TreeType`, `ListIndicesCommandInput`, `GunScopePromise`, `CrudOptions`, `ActionTypeExecutorResult`, `STHConfiguration`, `TransmartConstraint`, `TFS_Build_Contracts.Build`, `DAL.KEY_T`, `DBDriver`, `GetInsightSummariesCommandInput`, `IPhase`, `CompilerErrorResult`, `DiagnosticOptions`, `WebSession`, `DeployProps`, `monaco.editor.IModel`, `SpreadSheet`, `StorageData`, `DiscordMessageProcessor`, `CalloutProps`, `ProductOptionGroup`, `UnitCheckboxComponent`, `CreateJobCommand`, `HeaderPair`, `ZBarInstance`, `IFieldPath`, `CircuitBreakerOptions`, `QueryHelperService`, `ResAssetType`, `TableColumnConfig`, `DeploymentSummary`, `ECSqlStatement`, `FirestoreAPI.Value`, `CurrentDevice`, `MdxModelInstance`, `SGItem`, `vscode.QuickPickItem`, `VfsObject`, `ApplicationListenerArgs`, `UpdateConnectionDetails`, `PropertyEditorInfo`, `MassMigrationCommitment`, `VectorArray`, `DRIVERS`, `StacksTransaction`, `VirtualData`, `WritableFilesystem`, `NotificationDocument`, `SwapOptions`, `ClientFile`, `HmiService`, `ListImportsCommandInput`, `HttpArgumentsHost`, `LegendStrategy`, `AspidaResponse`, `PeerService`, `AuthenticationDetailsProvider`, `OperatorDescriptor`, `RunCommandInput`, `Eq.Eq`, `PanelPoints`, `BottomBarArea`, `IMutableVector3`, `ConcreteRequest`, `MethodParams.ProposeInstall`, `MockUdpTally`, `ExpandableTreeNode`, `FileStat`, `AnimationEntryMetadata`, `ListIdentityProvidersRequest`, `Loop`, `LocaleTemplateManager`, `ValueOrLambda`, `Cached`, `ExecResult`, `STATUS`, `TraceSpan`, `JSDocNameReference`, `ts.VariableStatement`, `Toast`, `GetConfigCommandInput`, `MIRTupleType`, `StoredNetwork`, `OnDemandPageScanRunResultProvider`, `IFeatureComment`, `Finish`, `GetError`, `InfiniteData`, `FindSubscriptionsDto`, `ComponentTheme`, `MockAttributeMap`, `ZodType`, `AccountCustom`, `CommandExecutionContext`, `Scales`, `AnimVector`, `SettableUserCode`, `CancelSource`, `RawOperation`, `CoreConnection`, `ITreeNodeAttrs`, `t.SelectablePath`, `ISchemaGenerator`, `PCancelable`, `IQResolveReject`, `IButton`, `RenderPassContextId`, `I18nContextType`, `ListAssetsRequest`, `Installer`, `StylingBindingData`, `requests.ListKeysRequest`, `TestVectorResult`, `ITaskWithStatus`, `SyncTasks.Promise`, `ListReportDefinitionsCommandInput`, `AddonProperty`, `MsgCreateProvider`, `Workbench`, `ApplySchemaAttributes`, `ToolbarOrientation`, `SVGPath`, `CreateTestConfigOptions`, `SKFillItem`, `Foxx.Router`, `IProposalCreateInput`, `configuration.APIData`, `TestStream`, `SharedStreetsGeometry`, `EvaluatedMetric`, `KibanaPrivilege`, `FieldFormatId`, `GUI`, `HttpClientConfiguration`, `ExcaliburGraphicsContext2DCanvas`, `ImportCodeAction`, `DataFrame`, `FormFieldEditorComponent`, `MockResolvers`, `ComposedChartProps`, `WebpackChain`, `ListMultipartUploadsCommandInput`, `ResourceTag`, `RetryHelper`, `TreeNodeProps`, `ListTypeNode`, `CipherGCM`, `UpdateChannelMessageCommandInput`, `ConnectionConfiguration`, `DiffResult`, `BridgeContracts`, `DatabaseUser`, `SkillMapState`, `IEmailDomain`, `Logquacious`, `TypeRef`, `MergeStrategy`, `ProductModel`, `TokenRange`, `EmitterInstance`, `CurrencyCNYOptions`, `ProjectParser`, `StateTaskEither`, `MoveCheck`, `IPreviewProps`, `QueryProvidersResponse`, `providers.JsonRpcProvider`, `labelValues`, `IProjectRepository`, `Pen`, `BrowserHistory`, `React.ForwardedRef`, `RpcResult`, `BracketType`, `FnU4`, `Idl`, `OutputDefinitionBlock`, `PersonData`, `Mill`, `CustomQueryHandler`, `WorkspaceService`, `DoneInvokeEvent`, `ReleaseChangelog`, `IKeyboardDefinitionStatus`, `ConfigVersion`, `ts.server.ScriptInfo`, `JMap`, `MergeTree`, `requests.ListAvailableSoftwareSourcesForManagedInstanceRequest`, `GfxClipSpaceNearZ`, `AppInputs`, `Encryption`, `ELogLevels`, `Callsite`, `requests.ListAutonomousDbVersionsRequest`, `GenericDeviceClass`, `DisassociateFromAdministratorAccountCommandInput`, `pulumi.InvokeOptions`, `TexCoordsFunction`, `RenderPass`, `TEdge`, `EnumField`, `ArmSiteDescriptor`, `BoundMethodCreator`, `WalletService`, `ArcShape`, `IGESDocument`, `ObjectLiteralExpression`, `DAL.KEY_DOT`, `AWSPolicy`, `IServiceInjector`, `ServiceSummary`, `EffectResult`, `textFieldModule.TextField`, `OneOf`, `BuildInPluginState`, `InstancePoolInstanceLoadBalancerBackend`, `ExpressionAstExpressionBuilder`, `Knex.SchemaBuilder`, `AxisAlignedBounds`, `AppearanceMapping`, `VRMSchema.VRM`, `handler.Queue`, `TSerializer`, `Transformation`, `DataTypes`, `MapStoreState`, `ServerStyleSheet`, `IProfileModel`, `FormProps`, `NormalizedUrl`, `d.BuildCtx`, `TaskLabel`, `Yeelight`, `VisDef`, `EncryptionAtRest`, `BytecodeWithLinkReferences`, `GitReference`, `CLDRFramework`, `PyVariable`, `CloudFormationStack`, `TranslateList`, `ThemeProviderProps`, `Int16Array`, `DbMicroblock`, `IRegion`, `PmpApiConfigService`, `GroupState`, `NatF`, `RectangleSize`, `ReferenceIdentifier`, `MutableContext`, `SocketChannelServer`, `EncryptionType`, `JSONPropPath`, `OnDiskState`, `LookupFnResult`, `AzureTreeItem`, `ImportTypeNode`, `ODataQueryOptionHandler`, `TransistorEpisodeData`, `GithubUserResponse`, `CodeKeywordDefinition`, `RuleTester`, `IKeymap`, `GroupRegistryState`, `SessionProxy`, `AutorestLogger`, `FromTo`, `LangState`, `B`, `NetworkTraceData`, `RelationQueryBuilderContract`, `KeyboardEventInit`, `WorkBook`, `IsGroupIndentCellFn`, `SortBy`, `GenericClassProperty`, `DescribeRoutingControlCommandInput`, `ISoundSampleDescription`, `TextWithLinks`, `vscode.NotebookDocument`, `IServerParams`, `ImportRelativity`, `SWRHook`, `JobsService`, `FormikHelpers`, `Interview`, `ListHttpMonitorsRequest`, `Fuse`, `CreateForgotPasswordDto`, `ListNotebookSessionShapesRequest`, `EmailConfirmationHandler`, `ObserverLocator`, `AnimatedMultiplication`, `StackDeployOperation`, `windowPositionCalculationState`, `LevelUp`, `NumberLabel`, `IScheduleApiModel`, `DeviceConfig`, `_rest`, `ConfigTypes`, `CSSRuleList`, `CSSMotionProps`, `ConfigurationListItemType`, `DynamicModule`, `ElasticsearchError`, `InternalSettings`, `IDraft`, `DetailedCloudFormationStack`, `T1`, `FeatureCatalogueSolution`, `HandlerMetadata`, `ELO.RankState`, `ResolvedNode`, `RoxieResult`, `RequestHandler`, `GetRuleCommandInput`, `NetWorthItem`, `OpenSearchDashboardsReactOverlays`, `requests.ListInstanceConfigurationsRequest`, `XRangePoint`, `Frontmatter`, `PointerState`, `AnyFunction`, `PathItem`, `ConnectionStore`, `ScullyRoutesService`, `MultiSelectProps`, `VimCompleteItem`, `Blob`, `i18n.Node`, `CheerioOptions`, `SecurityGroupContextProviderPlugin`, `ReadValueIdOptions`, `IFormTemplate`, `HaredoChain`, `ISystemInfo`, `EventTopics`, `TransmartAndConstraint`, `ColorFactory`, `DeployOpID`, `requests.ListDbServersRequest`, `Organization`, `HashTable`, `UiActionsServiceEnhancements`, `PluginCodec`, `FlipCorner`, `Fs`, `TabbedAggColumn`, `ArcRotateCamera`, `NormalisedFrame`, `RSTPreviewConfiguration`, `ILogoProps`, `MockServiceClient`, `ResponseComposition`, `Quest`, `HlsManifest`, `LoadedExtension`, `ResourceInsightProjectedUtilizationItem`, `IWalkthroughStep`, `TimelineById`, `AdminAPI`, `GraphQLType`, `IRasterizedGlyph`, `PipeOptions`, `PedProp`, `ErrorPayload`, `SCN0_Light`, `TUser`, `CreateBackupResponse`, `GasComputation`, `ScrollEvent`, `AppStackMinorVersion`, `EDBEntity`, `SFValue`, `Rule`, `HalfEdgePositionDetail`, `StoredDocument`, `IpPort`, `CharacteristicValue`, `IndexGroups`, `XmlNodeNop`, `GraphError`, `BpmnContext`, `ITypeFilter`, `UpdateResults`, `ContextValueType`, `LoginUserDto`, `HttpRequestWithFloatLabelsCommandInput`, `ContractContext`, `MosaicNode`, `Rotation`, `ISuperBlock`, `RESTService`, `CarModel`, `GulpClient.Gulp`, `EventModelImplUnion`, `TimeRangeInformation`, `ReservedParameters`, `PlistValue`, `VitePluginFederationOptions`, `RegistryDataStream`, `SecretKey`, `StageInterviewRepository`, `FrontstageProps`, `CLM.TrainDialog`, `R2Publication`, `signalR.HubConnection`, `BaseThemedCssFunction`, `CloudFrontResponse`, `React.RefForwardingComponent`, `Internals`, `DataHandler`, `Models.User`, `requests.ListAvailableUpdatesForManagedInstanceRequest`, `TimePeriodField`, `SidePanelOpenDirection`, `ReadModelRuntimeEventHandler`, `NotebookSessionShapeSeries`, `DraftInlineStyle`, `ToggleConfig`, `PaginationInfo`, `RelationMeta`, `SessionTypes`, `IParserOptions`, `AVRInterruptConfig`, `PiCommand`, `ReactCrop.Crop`, `gcp.Account`, `Fx`, `TabItem`, `Evees`, `ActionListener`, `LoopNode`, `HomebridgeLgThinqPlatform`, `TEventRangeType`, `SharedGeometryStateStyle`, `ColumnOrder`, `ServiceURL`, `ArgumentListInfo`, `HostWatchEvent`, `SpacesClient`, `PrintableType`, `IntrospectionTypeRef`, `OperatorType`, `LineWithBound`, `CarouselState`, `StoppingCondition`, `AnimatorFlowValue`, `IReserve`, `WorkspaceInfo`, `HalfEdgeMask`, `core.Coin`, `CreateTableBuilder`, `PropertyEditorParams`, `GlobalStateT`, `TextRangeDiagnosticSink`, `ByteVectorType`, `InvocationArguments`, `protos.google.iam.v1.IGetIamPolicyRequest`, `SchemaObjectMetadata`, `SettingsProps`, `GenericStoreEnhancer`, `FlattenedType`, `RoleKibanaPrivilege`, `GetTestDestinationOptions`, `MessageParams`, `VarScope`, `GridValueFormatterParams`, `DepList`, `ListDataSourcesCommandInput`, `UseSidePanelProps`, `ng.IIntervalService`, `IInstrument`, `DefaultFocusState`, `LayoutSandbox`, `Tween24`, `PageMargins`, `CredDef`, `MessageDataType`, `TemplateOptions`, `ReadonlyJSONObject`, `SyncHook`, `DecoderError`, `OutputTargetWww`, `CausalRepoStore`, `SemanticClassificationFormat`, `StatsAsset`, `HTMLIonPopoverElement`, `VueQuery`, `RenderContext3D`, `ProgressProps`, `IControllerAttributeExtended`, `T8`, `ResolveOptions`, `ReadonlyMat`, `ECPoint`, `AnnotationSpec`, `EnumDef`, `ApiClient`, `UserPaypal`, `ts.IfStatement`, `BuildInstance`, `CloudFrontResponseEvent`, `Import`, `StateByProps`, `CallExpr`, `B12`, `ListChannelMembershipsForAppInstanceUserCommandInput`, `FeatureChild`, `NgbActiveModal`, `WatchEventType`, `SecurityClass`, `BlockClassSelector`, `TransformFnParams`, `VueAutoRoutingPlugin`, `TextData`, `StyleElement`, `IDynamicGrammar`, `SliceState`, `IndexImpl`, `CascaderContextType`, `PatternMappingExpandEntryNode`, `AssembledSubjectGraphics`, `IDictionary`, `AuthorizationCode`, `NotifierPluginFactory`, `SignalingOfferMessageDataChannel`, `FieldsInModel`, `ViewStore`, `SubEntityLocationProps`, `unchanged.Path`, `PerformDeleteArgs`, `IDispatchProps`, `TypePredicate`, `ProseNode`, `Conference`, `FullAgentPolicy`, `CucumberRunner`, `apid.StreamId`, `PaginationResponseV2`, `CalendarEvent`, `HsLaymanLayerDescriptor`, `HierarchyPointNode`, `ts.BindingElement`, `TabState`, `PythonPlatform`, `LineDashes`, `SnackBarOptions`, `ConfigImagery`, `TodoRepository`, `PromiseOrValue`, `Shortcuts`, `Twitter.User`, `ModelSpecBuilder`, `CursorProps`, `PersonChange`, `Description`, `RoomUser`, `ParseNodeArray`, `TouchBar`, `FileLocation`, `ProblemRowData`, `ITagInputProps`, `AnyGuildChannel`, `NoopExtSupportingWeb`, `SubsetPackage`, `IPackageDescriptorMap`, `FilterSettings`, `handleParticipantEvent`, `AST.AST`, `GrpcAuthentication`, `ExportProps`, `FunctionalUseCaseContext`, `Master`, `BackendAPIService`, `requests.ListIntegrationInstancesRequest`, `GetAllRequestBuilder`, `IContainerRuntime`, `TransferBuilder`, `LatestClusterConfigType`, `ConditionalBlock`, `requests.ListAnalyticsInstancesRequest`, `Selection`, `ESSearchSourceDescriptor`, `AsyncThunkAction`, `glm.mat4`, `TPluginsStart`, `TokenLevelState`, `ChainInfo`, `WebKitGestureEvent`, `InAppBrowser`, `TestEmbeddable`, `IPatient`, `AggregatePriceService`, `ImportStateMap`, `IMdcSliderElement`, `DateEnv`, `EncryptionProtectorName`, `NumericScaleLike`, `Filterer`, `Farmbot`, `DIDResolutionResult`, `ValuePredicate`, `SFPPackage`, `Spring`, `CompletionState`, `RetryStatus`, `DisplayInfo`, `PrimitiveAtom`, `ProjectStep`, `HTMLFieldSetElement`, `DocumentContents`, `Yendor.Context`, `Base64Message`, `EventModel`, `ViewportRuler`, `TransmartTableState`, `RepositoryCommonSettingEditWriteModel`, `SCTP`, `ConstantAndVariableQueryStringCommandInput`, `SelectColony`, `WatchEffectOptions`, `CandyDate`, `CoreSystem`, `CBCentralManager`, `FilterMap`, `RadioGroupProps`, `ResolvedValue`, `AwrDbWaitEventBucketSummary`, `FlowCall`, `SiteEntry`, `TreeDataSource`, `UniswapV1Client`, `TestExtension`, `GetAttributeValuesCommandInput`, `LevelDocument`, `CounterMetric`, `ODataRequest`, `OpenSearchRawResponse`, `ListTableColumnsCommandInput`, `protos.google.protobuf.IEmpty`, `IKeyQueryOptions`, `KeyExchange`, `LitecoinPaymentsUtilsConfig`, `am4maps.MapPolygon`, `HoverProviderItem`, `ISliderProps`, `WebdriverIO.Element`, `Kysely`, `AccessExpression`, `CallbackFn`, `AuthenticateModel`, `PromiseFunction`, `API.services.IChromeFileService`, `IScriptSnapshot`, `BitField`, `SerializeNodeToHtmlOptions`, `UpdateProfile`, `ExcludedRule`, `EAggregationState`, `ValVersion`, `InputText`, `IAddress`, `ShotRequestOptions`, `fromTimelineActions.GetTimeline`, `VolumeIndicatorCallback`, `WebStorage`, `Rx.Subscriber`, `Gallery`, `SatObject`, `CredentialProvider`, `IStage`, `ConditionResolution`, `VdmServiceMetadata`, `Point3D`, `CanvasGradient`, `EditSettingsCommand`, `T13`, `ControlContainer`, `DeleteDirectoryCommandInput`, `EuiComboBoxOptionOption`, `TreeContext`, `CreateBidDTO`, `Payload`, `EAVNField`, `EthAsset`, `StudentEntity`, `externref`, `AppViewRoute`, `JSONDocument`, `ResponseBody`, `TomcatServer`, `ArDB`, `DeveloperClient`, `DAL.DEVICE_ID_ACCELEROMETER`, `PanRecognizer`, `OverlaySizeConfig`, `Dimensionless`, `IProxy`, `Quantity`, `pd.FindSelector`, `StorageLocationModel`, `RequestTemplateDef`, `Int32`, `SchemaObject`, `SnapshotRestoreRequest`, `GetStateParams`, `GetDeclarationParameters`, `vscode.TestItem`, `GRUCell`, `ChannelSettings`, `AuthMetadata`, `MergedBuildFileTask`, `CreateParams`, `OnNumberCommitFunc`, `InterviewPrizePlaylist`, `ResolvedVersion`, `RgbaTuple`, `pointInfoType`, `PrunerT`, `Avatar`, `React.CSSProperties`, `V1`, `PDFRawStream`, `UserDomain`, `RegionFieldsItem`, `EventEnvelope`, `VfsStat`, `SNS`, `ServiceException`, `SubShader`, `GfxTopology`, `MqttMessage`, `UIAlert`, `ClassMemberLookupFlags`, `TypeConstraint`, `DisplayObjectWithCullingArray`, `HTMLBaseElement`, `InternalOpAsyncExecutor`, `ChartDataItem`, `ITextAreaProps`, `StoredAppChallenge`, `UpdateRuleGroupCommandInput`, `Req`, `IDateRangePickerState`, `UserOrganizationService`, `SourceASTBuilder`, `BaseConvLayerArgs`, `IPAddressEntry`, `UseBoundStore`, `Element_t`, `HostPort`, `StatusMessageService`, `TestModelVersion`, `EnumRow`, `EnhancedModuleGraph`, `PaddingMode`, `ITracerProfile`, `CoercibleProperty`, `IBindingWizardContext`, `RequestArguments`, `UpdateCampaignCommandInput`, `ProposalIdentifier`, `RequestQueryOptions`, `AveragePooling1D`, `DescribeContactCommandInput`, `ArrayMap`, `CreateBucketCommandInput`, `SignalingClientConnectionRequest`, `ImplicitImport`, `Measurements`, `NodeBuilderFlags`, `NodeLinks`, `TextDocumentEdit`, `PLIItem`, `OnboardingLightData`, `ISourceMapPathOverrides`, `ApexLibraryTestRunExecutor`, `ProcessedCDPMessage`, `TokenFields`, `SnippetOptions`, `VApiTy`, `FindTilesAdditionalParameters`, `TableListItem`, `ListViewEventData`, `DeployOptions`, `NgModuleData`, `IContainerRuntimeBase`, `TableOfContentsItem`, `EditorService`, `UserSettingsState`, `ListStorageObjectsRequest`, `ICollection`, `CGAffineTransform`, `GovernanceAccountType`, `EventParameter`, `SocketInfo`, `V1Certificate`, `IPost`, `OsdFieldType`, `SearchDevicesCommandInput`, `FunctionDefinition`, `AuthorizationData`, `TokenMarker`, `TunnelRequest`, `Skola24Child`, `MockAirtableInterface`, `CriteriaGroupType`, `SearchTimeoutError`, `StackMode`, `DemoItem`, `OverlayKeyboardDispatcher`, `AttributeWeights`, `Collator`, `QueryExpressionParensContext`, `TypedFragment`, `IValueConverter`, `RequestDetails`, `RecordSourceSelectorProxy`, `UpSetJSSkeletonProps`, `AggsAction`, `MpElement`, `VueAuthOptions`, `UpdateWorkspaceCommandInput`, `CompareType`, `TileKey`, `ResponseOptions`, `SelectionType`, `Level1`, `WindowLocation`, `SurveyElementEditorTabModel`, `DataModels.UserTasks.UserTaskResult`, `ValidationProblem`, `Bills`, `AbstractSqlConnection`, `IExtensionElement`, `IssuePriority`, `SliderProps`, `ColorKind`, `HdRipplePaymentsConfig`, `Clauses`, `CoronaData`, `SubmitTexture`, `RangeData`, `FieldMappingSpec`, `SecurityManager`, `SpacesPlugin`, `RelativeRect`, `TChunk`, `DecodedResult`, `SelectorsSource`, `IChatItemsState`, `AudioState`, `AuthTokenEntity`, `HttpResponseException`, `PluginDeployerResolverContext`, `MemberNames`, `Mob`, `PasswordHistoryResponse`, `SSOAdmin`, `d.ScreenshotDiff`, `Vc2cOptions`, `BundleDataService`, `requests.ListDedicatedVmHostInstanceShapesRequest`, `CustomHtmlDivFormatter`, `FolderId`, `ChartHighlightedElements`, `AzureClusterProvider`, `PopulateOptions`, `DevOpsAccount`, `SystemLayout`, `WordStyle`, `JSONSchema6`, `Icons`, `t_b1f05ae8`, `BITBOXCli`, `ChannelMessageList`, `Scheduler`, `ContentRecord`, `POIDisputeAttributes`, `NavigationIndicatorCriteria`, `PROVIDER`, `PluginContext`, `ReflectedValue`, `Shrewd.IDecoratorOptions`, `ModifierKeys`, `MyDefaultThunkResult`, `FetchAPI`, `IteratorOptions`, `QueryRenderData`, `EventInit`, `TSClientOptions`, `CallbackType`, `MerchantGoodsSkuEntity`, `CheckOriginConflictsParams`, `StoryListener`, `allContracts`, `AssembledReportGraphics`, `TESubscr`, `SurveyCreator`, `PgClient`, `SqlToolsServiceClient`, `EntityOperators`, `objType`, `GdalCommand`, `r`, `DataEvent`, `ShapeData`, `moment.Moment`, `ResultMeta`, `SampleExtractionResult`, `BluetoothRemoteGATTService`, `VideoQualitySettings`, `PNGWithMetadata`, `PrintableArea`, `ParameterMap`, `ExtendedKeyboardEvent`, `ExpressContext`, `ValidCredential`, `AppMetadata`, `TestFunctionImportSharedEntityReturnTypeCollectionParameters`, `DeprecatedHeaderThemes`, `Indices`, `ChainIdLike`, `JTDSchemaType`, `Rules`, `enet.IConnectOptions`, `HdLitecoinPayments`, `MessageSpecification`, `configuration.Data`, `TileDisplacementMap`, `ResilienceOptions`, `RemoteUpdateListener`, `RouteDryMatch`, `ScheduledDomain`, `ResourceSystem`, `SpectatorService`, `NodeDisplayData`, `IKeyIterator`, `PreferredContext`, `TypeGenerator`, `DataViewRow`, `AnyPersistedResource`, `BrickRenderOptionsResolved`, `WebSocketLike`, `DistinctValuesRequestOptions`, `StructProp`, `ActionGameState`, `PlaceholderProps`, `lgQuery`, `PrivateStyle`, `SoftwareModel`, `LegacyObjectToConfigAdapter`, `LinkOptions`, `SchemaContext`, `IncompleteTreeNode`, `GX.TevOp`, `DiffPanel`, `StringType`, `FailedJob`, `DescribeModelCommandInput`, `LookUpResult`, `Zerg`, `Secp256k1`, `ServerKeyExchange`, `AnyNode`, `PowerlevelCCSet`, `VisualizeAppState`, `UnitRecord`, `IConsul`, `TSupportedFaction`, `WebRequest`, `ByteMatrix`, `ConnectionBackend`, `Viewer.ViewerRenderInput`, `grpc.CallOptions`, `UnwrapRowsComputed`, `RecursiveAnnotation`, `d.PrerenderManager`, `THREE.Event`, `Instantiable`, `MessageHandler`, `ModuleImport`, `Rule.Node`, `Vendor`, `ComponentDescriptor`, `IERC20`, `MarkdownRenderer`, `TreeDataProvider`, `CodeRepository`, `DialogRef`, `IGherkinStreamOptions`, `EntityMetadataMap`, `NetlifyConfig`, `PostgrestResponse`, `InterfaceServerResponse`, `WechatMaterialEntity`, `ICharacterData`, `WebviewWidget`, `React.EffectCallback`, `fhir.Bundle`, `IChart`, `PanGesture`, `IReadOnlyFunctionCallArgumentCollection`, `PromiseCollection`, `TokenCredentialsBase`, `PluginState`, `OpenSearchDashboardsConfig`, `TestWalker`, `SvgProps`, `ThermocyclerModuleState`, `ODataBatchRequestBuilder`, `FullLocaleData`, `PipelinesGraphics`, `DangerDSLJSONType`, `ItemResponse`, `UpdateConfigurationDetails`, `IISystemProto`, `TileDataSourceOptions`, `PipelinesService`, `GetBalanceActivityOptions`, `GuidGenerator`, `PuzzleAction`, `RetryConfiguration`, `CalderaElement`, `Vulnerability`, `X12Transaction`, `FileSystemConfig`, `Ray3d`, `TextureDescriptor`, `WorkerRequestEntry`, `GetUserResponse`, `net.Endpoint`, `eris.Client`, `IZoweDatasetTreeNode`, `TextTransformType`, `ConditionExpression`, `ListChannelsRequest`, `TableQuery`, `IdentifierAttribute`, `StringDictionary`, `MusicbrainzArtist`, `CreateGroupCommandInput`, `WildcardIndex`, `WorkspaceFileWatcher`, `InvalidOperationException`, `CalendarApi`, `TaskInProgress`, `CreateRuleGroupCommandInput`, `ScanRunResultResponse`, `NoteData`, `InsertPosition`, `WrongDependencies`, `ConfigurationChangeEvent`, `PeerSet`, `GCPubSubServer`, `MissionElement`, `TypeParser`, `ISpan`, `LogSeriesFragmentPushRequest`, `PartyDataSend`, `ConnectionManagerState`, `MP4Box`, `ByteVector`, `TextStringLiteralContext`, `STFilterComponent`, `NextConnect`, `OrganizationUserBulkRequest`, `TiledObjectGroup`, `ThyTreeNodeCheckState`, `requests.ListAgreementsRequest`, `AreaGeometry`, `ITelemetryBaseLogger`, `IAuthStatus`, `GroupModel`, `NumberConfig`, `ObjectTypeComposer`, `Argon.SessionPort`, `ImageUpdate`, `TranslationPartialState`, `AnyIterableIterator`, `ng.IDirective`, `ICommandBus`, `DockerContainer`, `UnionTypeDefinitionNode`, `GestureState`, `CdkTree`, `DirtyDiff`, `PriceAxisViewRendererOptions`, `DiffState`, `rootState`, `ARAddModelOptions`, `ClientAndExploreCached`, `HasJSDoc`, `FileVersionSpec`, `AggTypeFilter`, `SourceGroup`, `LogoState`, `RestGitService`, `FieldSpec`, `Atom`, `AllowAction`, `HAP`, `DecoratorOption`, `Ch`, `OrderRepository`, `LastfmArtistShort`, `DeleteInputCommandInput`, `YAnnotation`, `ModifyReadResponseFnMap`, `PLSQLCursorInfos`, `FloatKeyframe`, `FieldDefinition`, `AppendBlobClient`, `CreateDatasetResponse`, `StoreService`, `EntityBuilderType`, `SplitInfo`, `VectorLayerDescriptor`, `DescribeServiceUpdatesCommandInput`, `IMiddlewareClass`, `XNumber`, `requests.ListVaultReplicasRequest`, `Chromosome`, `ListBuffer`, `EliminationBracket`, `ToolTipProps`, `StacksMainnet`, `SharedKey`, `FirebaseProject`, `ApplicationStub`, `ListExecutionsCommandInput`, `GovernElement`, `Http3FrameType`, `SubmissionSectionError`, `FontVariant`, `UserSessionService`, `MagitRepository`, `PreparationTool`, `DisplayValueMapService`, `DefaultVideoTransformDeviceObserver`, `EntityMetadata`, `Crdp.Runtime.ConsoleAPICalledEvent`, `SelEnv`, `NoteCacheItem`, `ISerializer`, `IAmazonServerGroupView`, `protocol.Request`, `PickleStep`, `SelectorArray`, `Containers`, `ITokenObject`, `ValueFormatter`, `AlertsByName`, `FilePickerProps`, `SpineBone`, `S3Configuration`, `ModuleRef`, `ReportingNotifierStreamHandler`, `OutlineSurveys`, `IAreaData`, `RawSavedDashboardPanel610`, `CreateCampaignCommandInput`, `AssetVersion`, `ArenaFormatings`, `WebMessageRawPayload`, `StateBase`, `BitExprContext`, `WorkerService`, `PerspectiveTransform`, `IntervalHistogram`, `SpaceBonus.TITANIUM`, `BindingPattern`, `native.Array`, `ListExportsCommandInput`, `IUtxo`, `IHashMapGeneric`, `WriteBufferToItemsOptions`, `MoveSeq`, `PostgreSQL`, `DaffPaypalTokenResponseFactory`, `ReduxActions.Action`, `ParseResult`, `VisType`, `IGBCoreService`, `DeleteStageCommandInput`, `TSError`, `TimeTrackerService`, `BlockchainCode`, `SVGTemplateResult`, `SDKVersion`, `IConsole`, `WorkflowMapper`, `UpdateRecorder`, `FormGroupDirective`, `NewPackagePolicyInputStream`, `DeviceTracker`, `FuseResult`, `ViewOptions`, `SkillGaussian`, `ClientBase`, `ILoaderIncludePipe`, `colorModule.Color`, `TestUser`, `EllipsoidPatch`, `CourseComponent`, `StoreApi`, `TileCacheId`, `LineString3d`, `TFileOrSketchPartChange`, `ResourcesModel`, `ProgramAccount`, `RenderCompleteListener`, `EditRepositoryCommand`, `DisassociateServiceRoleFromAccountCommandInput`, `THREE.SkinnedMesh`, `DailyRate`, `NAVObject`, `PackageManagers`, `Tx.Info`, `GraphReceipt`, `ContainerState`, `CoreIndexFile`, `ComponentResolverService`, `MemberDefinition`, `InstanceTarget`, `HitDatabaseMap`, `AudioService`, `PropertyChangedEvent`, `BitSource`, `HeapObject`, `ToolGroup`, `ConfigValue`, `Generation`, `TestBackendTimer`, `UniqueIdGenerator`, `CameraConfig`, `ThyNotifyService`, `InvalidParameterValueException`, `AllureRuntime`, `MapLayer`, `EventHandlers`, `Extended`, `VisTypeListEntry`, `TInjectableOptions`, `OpenDialogOptions`, `MDCFloatingLabelAdapter`, `ImageBitmap`, `LocationCalculatorForHtml`, `FrontCardAppearanceShort`, `IntersectionState`, `FileSystemHost`, `PragmaDirectiveContext`, `requests.GetDomainRecordsRequest`, `IHistoryItem`, `OnRefreshProps`, `ConversationService`, `VersionMismatchFinder`, `StyleSheet`, `Path5`, `CanvasPattern`, `EncodeApiReturnOutput`, `GPGPUProgram`, `StatisticsSetType`, `IFluidDependencySynthesizer`, `TalkSession`, `PutAccountSendingAttributesCommandInput`, `GfxPlatformWebGL2Config`, `V1Deployment`, `IBreakpoint`, `LimitedTypedData`, `ReactPortal`, `ListState`, `PackageFailures`, `ITagMatchInfo`, `JsonaAnnotation`, `BlobClient`, `AdapterConstructor`, `NVMDescriptor`, `FrescoDrawee`, `GraphQLNamedType`, `PlayerInfo`, `NodeKeyType`, `ComponentPath`, `SchemaService`, `DateBodyRow`, `GetBucketTaggingCommandInput`, `RivenProperty`, `ParsedLineType`, `AuthResponse`, `FirebaseObjectObservable`, `AnimationNodeContent`, `RobotCard`, `NVM3Objects`, `... 23 more ...`, `ServiceBuilder`, `RuleAction`, `ReaderOptions`, `IColumn`, `MockedFunction`, `StampinoRender`, `QueryOption`, `NodeSourceOption`, `Swap`, `AuthenticateResultModel`, `IProjectConf`, `PolygonGeometry`, `PickItem`, `HostElement`, `ModuleDeclaration`, `SeriesDomainsAndData`, `DispatcherPayloadMetaImpl`, `UsedHashOnion`, `CoinbasePro`, `HookOptions`, `TimePickerModel`, `TheDestinedLambdaStack`, `IReactionPublic`, `CompileOptions`, `SimpleAllocationOutcome`, `IConcatFile`, `SearchIndex`, `TypeConverter`, `SymbolScope`, `SmsProvider`, `PoolTaskDataService`, `FieldHook`, `DataSource`, `FetchedIndexPattern`, `IntPretty`, `IntegratedSpiral3d`, `AsyncFnReturn`, `ValidatorModel`, `Molecule`, `BundleOptions`, `AlyvixApiService`, `AutocompleteFieldState`, `StackOperationStep`, `StellarBalanceMonitor`, `bool`, `dom5.Node`, `FilterLabelProps`, `CameraCullInfo`, `requests.ListVirtualCircuitBandwidthShapesRequest`, `SqrlParseErrorOptions`, `matter.GrayMatterFile`, `StyleExpression`, `IFileUnit`, `HeroById`, `core.JSCodeshift`, `BrewView`, `TType`, `MessageArg`, `Masking`, `UpdateProjectResponse`, `SuperTest`, `NonFungibleAssetProvider`, `IReactionDisposer`, `IMinemeldPrototypeService`, `ExecutionContainer`, `WorldComponent`, `RenderTreeFrameReader`, `Spacing`, `CFMLEngine`, `TranspileOutput`, `LayerConfigJson`, `CreateAndTransferTransition`, `ResourceNode`, `PvsVersionDescriptor`, `HubServer`, `RootContainer`, `Structures`, `FilterService`, `TagSpecification`, `ForkOptions`, `MsgToWorker`, `NodeSorter`, `TestRunnerAdapter`, `MinifyOutput`, `CharacteristicGetCallback`, `CustomPropertyGetUsage`, `ValueStream`, `ReadAndParseBlob`, `FunctionConfiguration`, `requests.ListTransferJobsRequest`, `IAllAppDefinitions`, `ResolverMap`, `TensorTracker`, `FirebaseUserModel`, `AccountSettings`, `FetchPolicy`, `InvalidStateException`, `GroupingService`, `DebugProtocol.StepInResponse`, `PoolFactory`, `Ctor`, `Nibbles`, `ExportContext`, `SystemIconStyles`, `FirestoreError`, `AppDeepLink`, `ContractNode`, `LedgerRequest`, `SubqueryRepo`, `BasisCompressionTypeEnum`, `URLBuilder`, `MdcRadio`, `CommsRecord`, `IPCMessages.TMessage`, `ListCardConfig`, `React.ComponentClass`, `ColumnObjectType`, `SerializedSavedQueryAttributes`, `IUserNote`, `BinaryBuffer`, `TemplateDocument`, `DatasetTree`, `IDocumentContext`, `MVideoFile`, `Magic`, `StencilOp`, `StatsModule`, `NbDialogService`, `Notations`, `DataView`, `GQtyClient`, `ElementState`, `LayoutMaterial`, `NzI18nInterface`, `CreateArg`, `FacetsGroup`, `ErrorCodes`, `SearchSourceDependencies`, `SetupDependencies`, `AccountingTemplate`, `Counter`, `TypeIR`, `LoginUri`, `ReadModelInterface`, `ItemStorageType`, `TEChild`, `TableBatchOperation`, `CompiledRuleDefinition`, `BanesAndBoonsInfo`, `SpyInstance`, `GitJSONDSL`, `QueryTimestampsCommandInput`, `API.storage.api.ChangeDict`, `FileAccessor`, `FolderComponent`, `DependencyMapEntry`, `RunResult`, `ApiResourceReference`, `SupportCodeExecutor`, `JsonRpcClient`, `IFormSectionGroup`, `DeviceLog`, `EzModel`, `SimulatorDevice`, `GoEngineConfig`, `ManagementSection`, `Hello`, `ISPHttpClientOptions`, `http.IncomingMessage`, `IXYOperator`, `DataPublicPluginStart`, `AuthHandler`, `InteractionProps`, `AssertNode`, `MessageResponse`, `LicenseInfo`, `RX.Types.ReactNode`, `LogDomain`, `OwnerService`, `IEntityKeyType`, `GlobalAveragePooling2D`, `QueryShortChannelIdsMessage`, `SampleProduct`, `Ripemd160PolyfillDigest`, `ISqlEditorTabState`, `PreloadedQuery`, `SummaryCollection`, `ApiValue`, `DescribeScalingActivitiesCommandInput`, `ReadonlyObjectDeep`, `UserProvided`, `TestSuiteNode`, `ButtonData`, `CompareFn`, `TypistOptions`, `DiscordBridgeConfigAuth`, `ModalInitialState`, `TSAssign`, `DynamodbMetricChange`, `Mask`, `IConnectionOptions`, `CreateClusterCommandInput`, `SearchBarProps`, `express.Request`, `IInstanceDefinition`, `TableHeader`, `RenderHookResult`, `TensorList`, `AppThunk`, `CreateApplicationCommandOutput`, `Cls`, `CallClientState`, `MenuModelRegistry`, `EventArguments`, `MutableQuaternion`, `DebugProtocol.ScopesResponse`, `PeerId`, `GeneratedFont`, `Download`, `AddressVersion`, `JSMs.XPCOMUtils`, `PropertyInfo`, `VNodeQueue`, `Survey.SurveyModel`, `IterableDiffers`, `LernaPackage`, `BumpType`, `InjectFlags`, `StaticConfigParsed`, `ListActionsCommandInput`, `ICompilerResult`, `RouteType`, `MiTextConfig`, `OutputLink`, `ShareParams`, `BuilderReturnValue`, `ExtensionReference`, `IIterationSummary`, `DecoratorOptions`, `ValueSuggestionsGetFn`, `ValidationMessage`, `RulesClient`, `NestedValueArray`, `Immutable`, `TapeNode`, `TestState`, `LegacySprite`, `PersistenceHelpers`, `GPUBindGroup`, `TextureLoader`, `FilterOption`, `ValueXY`, `DatabaseFactory`, `CrudService`, `EntityComparisonField`, `IngredientReducerState`, `ContextOptions`, `SlideData`, `CheckboxGroupState`, `FetchGroup`, `SortedMapStructure`, `DyfiService`, `StatePropsOfControl`, `ImmutableSet`, `BinaryOperationNode`, `InsightOptions`, `CursorState`, `HashCode`, `CalendarOptions`, `EightChar`, `QueryProviderRequest`, `BuildFile`, `ErrorController`, `FaunaData`, `Pier`, `CloudFrontRequest`, `sinon.SinonFakeTimers`, `EffectReference`, `PatchListener`, `SettingsStore`, `LoginUriData`, `TokenRequest`, `GetTemplateCommandInput`, `SRoutableElement`, `GlobalVariables`, `PlayerModel`, `ICreateOrgNotificationOptions`, `DeleteDataSetCommandInput`, `Supplier`, `RecordRawData`, `GameEngine`, `Filesystem.FileExistsSync`, `ActJestMoveTimeTo`, `CustomReporterResult`, `ISubscribe`, `LineModel`, `ActionheroLogLevel`, `NoneAction`, `BoxFunction`, `StateChangeListener`, `OclExecutionContext`, `TemplatePortal`, `SizeType`, `ThyUploadFile`, `TParam`, `FunctionN`, `AnalysisMode`, `CouncilProposal`, `SendRequest`, `PostSummary`, `AnimationKeyframeLinear`, `RedisOptions`, `SolanaKeys`, `PathToRegExpOptions`, `EndpointDetails`, `sentry.SentryEvent`, `SliceRequest`, `requests.GetConnectionRequest`, `QueryResult`, `TemplateAst`, `DynamicFormArrayModel`, `RobotApiRequestMeta`, `TransactionStatus`, `TypePredicateNode`, `AndOptions`, `T16`, `NavigationParams`, `PersistStorage`, `IssueProps`, `ResponsiveSpace`, `IChild`, `AStore`, `Reconciler`, `OpticType`, `Intl.NumberFormatOptions`, `Prefab`, `NodeCheckFunc`, `ParamDefinition`, `GeoBounds`, `CosmosdbSqlDatabase`, `Fig.Arg`, `MetadataType`, `SidebarService`, `IAdvancedBoxPlotData`, `Jb2Adapter`, `WebGLMemoryInfo`, `TocLink`, `PSIBoolean`, `IRecord`, `EmitHost`, `BackendErrorLabel`, `IMovie`, `InterfaceEvent`, `UnitAnalyser`, `ChannelId`, `PacketMember`, `NormalizedConfig`, `Directions`, `MnemonicSecret`, `AudioVideoObserver`, `requests.ListAutonomousExadataInfrastructureShapesRequest`, `ContentTypeSchema`, `ScopeOptions`, `AppRouteRecordRaw`, `EChartGraphNode`, `Fixture`, `ILaunchOptions`, `Window.ShellWindow`, `ForStatement`, `CmafEncryption`, `httpProxy`, `ConvaiCheckerComponent`, `IStaticFile`, `ReplicaSet`, `BSplineWrapMode`, `CreateBotCommandInput`, `GetEnvironmentTemplateVersionCommandInput`, `ChatUser`, `PublicParams.Swap`, `ServerConfigResource`, `OperationModel`, `TransformedStringTypeTargets`, `Phaser.Game`, `TinyHooks`, `LogStream`, `NormalizedParams`, `UseTransactionQueryState`, `TokenScanner`, `UniqueKey`, `LanguageIdentifier`, `CategoryLookupTables`, `QueryOrderRequest`, `TextMetrics`, `AESJsonWebKey`, `GfxBlendFactor`, `TestFabricRegistryEntry`, `PresenceHandler`, `BodyElement`, `InvokeMethod`, `SteamTree`, `... 7 more ...`, `Attitude`, `TextMatchPattern`, `CombatAttack`, `SectionList`, `IRootElasticQuery`, `IExplorer`, `LinuxJavaContainerSettings`, `PQLS.Library.TLibraryDefinition`, `WorkspaceOptions`, `RoosterCommandBar`, `UpdateDataSetCommandInput`, `TypeNameContext`, `DescribeExportCommandInput`, `ParsedQueryWithVariables`, `MongoClient`, `NgrxJsonApiStoreResources`, `ContextProps`, `UrlFilter`, `TypeArgumentResult`, `ShapeTreeNode`, `MessengerTypes.BatchItem`, `SpansRepository`, `CheckMode`, `GetRecommendationsCommandInput`, `FetchInit`, `DeployStatus`, `CommandEntry`, `ReadableBYOBStreamOptions`, `ts.TextRange`, `TutorialRuleStatus`, `ProviderStore`, `ExplicitFoldingConfig`, `RequireId`, `Average`, `IDescribeRunner`, `Pt2`, `SymBool`, `UniformState`, `ScriptProcessorNode`, `RgbaColor`, `SlpTokenGraph`, `FluentLogger`, `Providers`, `ValidationFunc`, `ExtrinsicDetails`, `WalletState`, `EclipticCoordinates`, `Emotion`, `BuildArtifact`, `IShareButton`, `UserDataCombined`, `MinimalTransaction`, `BaseLanguageClient`, `DayElement`, `SubscribeMessage`, `MyCombatLogParser`, `PropertyCollection`, `ClassConstructor`, `UpdateFindingsCommandInput`, `DimensionMapping`, `DaffAuthLoginReducerState`, `TextInputType`, `ChromeHelpExtension`, `ChartTooltipItem`, `LaunchTemplate`, `ExternalMaster`, `MutableRefObject`, `ShapePair`, `Row`, `LoginParams`, `IAggregationStrategy`, `ITableDefine`, `CertificateAuthorityTreeItem`, `DomExplorerNode`, `NativeInsertUpdateOptions`, `ObservableLightBox`, `EncryptionConfig`, `v2.WebDAVServer`, `PosAndDir`, `MeasurementKind`, `Autopanner`, `PositionAnimation`, `MnemonicX86`, `StateObject`, `Datasource`, `ListPortfoliosForProductCommandInput`, `THREE.Box3`, `IQueryBuilder`, `QualifiedIdentifierContext`, `CloudWatchMetricChange`, `LabelType`, `DescribeOrganizationCommandInput`, `UserPoolService`, `TravisCi`, `WesterosGameState`, `SubjectDetails`, `IntelRealtimeResponse`, `SidebarButtonProps`, `PropertyDecorator`, `IWebAppWizardContext`, `AST`, `IndyPool`, `CreateRouteCommandInput`, `OperatorFinishEncodeInfo`, `S3Destination`, `LayoutActor`, `restm.RestClient`, `DirectiveProfile`, `OidcState`, `CheckResultBuilder`, `NamedTypeNode`, `SQLite3Types`, `TestThrottler`, `AirSchema`, `DataType`, `ApiErrorParams`, `PDFImage`, `BsModalService`, `FormikProps`, `FnParam`, `NonEmptyList`, `NotifyFunc`, `IDeploymentCenterContext`, `InputBox`, `CB`, `mm.IFormat`, `ISearchOptions`, `ExchangeInstance`, `IGridAddress`, `AstroConfig`, `FlowsenseUpdateTracker`, `ComponentCompilerProperty`, `IProps`, `ModelStore`, `WebGL2DisjointQueryTimerExtension`, `BlobGetPropertiesResponse`, `ElementStyles`, `BreadcrumbOptions`, `VocabularyModel`, `PPTDataType`, `CampaignTimelineBoardViewerChanelsModel`, `RectilinearEdgeRouter`, `RxnPlus`, `Bag`, `Topics`, `Slides`, `AssetsOptions`, `AwsCredentials`, `ISmsProvider`, `Thing`, `Characteristic`, `cormo.Connection`, `DeployBuilderOptions`, `PointsGeometry`, `BLOCK`, `HTMLInputElement`, `ThemeVersion`, `InterpolationCurve3dOptions`, `ChatTab`, `dagre.graphlib.Graph`, `IPreset`, `TAtrulePrelude`, `Highcharts.VennRelationObject`, `SandboxContext`, `ParticipantListItemStyles`, `ICols`, `TypeDescription`, `ResponseErrorAttributes`, `PlaylistEntry`, `DeleteSubnetGroupCommandInput`, `requests.ListAutonomousDbPreviewVersionsRequest`, `XChaCha20Poly1305`, `TodoService`, `mongoose.FilterQuery`, `Events.visible`, `EthereumListener`, `ScopedClusterClient`, `CacheManagerGetOptions`, `DeleteApp`, `FoodModel`, `SingleLayerStringMap`, `FlagInfo`, `DaffSeoNameMetaDefinition`, `DaffCartAddressFactory`, `Elem`, `IModelHostConfiguration`, `SymFloat`, `CommandInteraction`, `IFormikStageConfigInjectedProps`, `IExtendedCommit`, `Normalized`, `NgEnvironment`, `StorageKeys`, `GLsizei`, `ThumbnailProps`, `RootNode`, `Console`, `EqualityFunc`, `Ratio`, `NineZoneStagePanelPaneManagerProps`, `UrlMatchResult`, `ElasticsearchClientConfig`, `EVENT_TYPE`, `MessagingServiceInterface`, `FilterConfig`, `Enzyme.ReactWrapper`, `ToastService`, `IAstItem`, `TypeNode`, `Etcd3`, `SavedObjectsTypeMappingDefinitions`, `RType`, `VisualizeAppStateContainer`, `FactorGradient`, `CoreStart`, `requests.ListMultipartUploadPartsRequest`, `ILinkedNodeWithValue`, `SemanticMeaning`, `EventSubscriptionQuotaExceededFault`, `PreviousSpeakersState`, `TableRowData`, `ChangeStateMap`, `BrandState`, `KDF`, `PerspectiveDetails`, `Http3HeaderFrame`, `IDiscordMessageParserResult`, `HasTagName`, `RequestSpec`, `OrganizationProjectsService`, `AccountEmail`, `ATNConfig`, `Pubnub`, `ILocalConfig`, `TimeOffPolicy`, `IRouterliciousDriverPolicies`, `IExecSyncResult`, `ApplyPath`, `PeerInfo`, `JSDocTypeTag`, `events.Handler`, `FieldFormatsStart`, `ConnectionArgs`, `ChunkIndex`, `LogAnalyticsParameter`, `TableDimension`, `ResolvedEphemeralListType`, `ResolvedCSSBlocksEmberOptions`, `Players`, `NumericValuesResult`, `SlotDoc`, `EventStatus`, `ATTRIBUTE`, `TestFormat`, `ApiRun`, `StackingState`, `DrivelistDrive`, `PinMap`, `NzMessageDataOptions`, `Runnable`, `ListUsersRequest`, `SettingsConfig`, `PreprocIncInfo`, `ViewResources`, `InstanceRejectOnNotFound`, `ILanguageObject`, `React.RefObject`, `SingleYAMLDocument`, `SynthIdentifier`, `LanguageClientOptions`, `AssetType`, `RuleConfigTuple`, `ServiceClient`, `ReactEventHandlers`, `IterableChangeRecord_`, `RTCRtpSender`, `Datatypes`, `SiteConfig`, `TimeWidget`, `IProductOptionGroupTranslatable`, `MockConnection`, `HeadersFunction`, `RegisterConfig`, `ExpectedCompletionEntryObject`, `DerivedGauge`, `CommandClasses`, `IWatchOptions`, `PoiBatch`, `NodeProperties`, `SettingOptions`, `ImGui.DrawVert`, `AbstractProvider`, `Balances`, `DetailsState`, `Door`, `SurveyLogicAction`, `SystemStyleObject`, `InterpolationCurve3d`, `PageButtonProps`, `MessageId`, `ArrayEntry`, `IMagickImage`, `JsonStringifierTransformerContext`, `MessageEnvelope`, `TaskFile`, `ActionsObservable`, `LayoutConfig`, `TypeExpression`, `HMACParams`, `RetryKeycloakAdmin`, `AddApplicationInputCommandInput`, `QueryBidRequest`, `AddressHashMode`, `Mentor`, `ListRunsRequest`, `ReadFileResult`, `ChangePasswordRequest`, `CloudFront`, `i8`, `ProjectionResult`, `ClientModel`, `CreateResult`, `SettingLanguage`, `SortedMap`, `ISelectionData`, `BspSet`, `MetricsConfiguration`, `WebGLRenderTarget`, `StageStore`, `X12QueryResult`, `DijkstraNode`, `TaskData`, `IRealtimeSelect`, `MaterialConfig`, `RebaseEditorContext`, `Pool2DProgram`, `PickFunction`, `JsonDocsPart`, `BaseEdge`, `AllStyleOption`, `ApplicationParameter`, `CfnCondition`, `CaretCoordinates`, `RecycleAccumulator`, `APIVersion`, `GX.IndTexAlphaSel`, `Combine`, `WorkNode`, `Howl`, `FileAnalysisResult`, `HttpManagementPayload`, `IRef`, `IPluginTimes`, `INohmPrefixes`, `PointerInfoPre`, `UserOperation`, `WebAudioInstance`, `MetaDefinition`, `LmdbEnv`, `Weather`, `OperationInfo`, `PlayingCard`, `Group1524199022084`, `TimeGridWrapper`, `CombinedJob`, `MemoryManager`, `SessionEntity`, `NetworkSourcesVirtualSourceList`, `LinkInfo`, `ReadonlySymbolSet`, `TimerEvent`, `BRepGeometryInfo`, `ICommonTagsResult`, `SfdxFalconResultType`, `InterfaceWithExtends`, `TodoFilter`, `esbuild.OnResolveArgs`, `PropertiesService`, `StoreMetaInfo`, `TransformStreamDefaultController`, `CompilerOutput`, `ReadableStreamDefaultReader`, `DidDocumentService`, `UnhashedOrder`, `TransactionVersion`, `Tarefa`, `PadplusRoomInvitationPayload`, `React.SetStateAction`, `Flow`, `IBook`, `TaskDefinitionRegistry`, `IModelReference`, `SemanticNode`, `IResourceRow`, `SpacerProps`, `WorkRoot`, `QueryClient`, `PropsHandler`, `PreProcessor`, `vscode.Disposable`, `SideBarTabModel`, `IncomingHttpHeaders`, `HierarchyCompareInfoJSON`, `StoredEventBatchPointer`, `LoadedVertexDraw`, `messages.DataTable`, `LinariaClassName`, `AnimationController`, `GeoJsonObject`, `unreal.Message`, `ElasticsearchResponse`, `GLTFLoaderExtension`, `Scale`, `Rx.TestScheduler`, `RetryDataReplicationCommandInput`, `MockMessageRequester`, `MaterialAnimationTrack`, `requests.ListAppCatalogListingResourceVersionsRequest`, `Datum`, `RxFormArray`, `ITemplatedBundle`, `FragmentManager`, `tf.NamedTensorMap`, `INativeMetadataCollector`, `ActionTypeBase`, `DAL.DEVICE_HEAP_ERROR`, `Datafeed`, `SearchService`, `StepResult`, `AccountJSON`, `AttrAst`, `CallClientProviderProps`, `TKey2`, `FormattingRequestKind`, `FutureNumber`, `MappedNameValue`, `SearchView`, `KeyFrameLink`, `Transporter`, `TooltipInfo`, `Buffer`, `CreeperPoint`, `EventFnSuccess`, `Split`, `FieldFilterState`, `StunProtocol`, `BrowserTranslateLoader`, `DebugId`, `Objective`, `SyncResultModel`, `RollupOutput`, `OutputData`, `UpSampling2D`, `ThermostatFanModeCCSet`, `IdentifierNode`, `Assign`, `DataMap`, `tflite.TFLiteModel`, `ListBundlesCommandInput`, `MDCFloatingLabelFoundation`, `BuildLog`, `INumbersColumn`, `YAMLWorker`, `requests.ListMultipartUploadsRequest`, `SiemResponseFactory`, `APIGatewayProxyEvent`, `Village`, `IIArticlesState`, `DateHistogramBucketAggDependencies`, `ChannelConstants`, `DialogActions`, `PolyfaceBuilder`, `MinAttrs`, `SimEnt`, `Ord`, `RuleModule`, `ISymbol`, `PlotBandOptions`, `Closure`, `KeywordToken`, `requests.ListServiceGatewaysRequest`, `SiblingGroup`, `SubscriptionNotFoundFault`, `JsonAstKeyValue`, `messages.PickleDocString`, `AppSettings`, `DeleteSchemaCommandInput`, `FakeExecution`, `ImageryCommunicatorService`, `CollapseProps`, `CleanupCallback`, `ArgParser`, `Toppy`, `XAndY`, `CustomBond`, `DiagnosticAndArguments`, `IIntegerRange`, `ImportKind`, `HlsPackage`, `NumberFilterFunction`, `DialogContext`, `BSPSphereActor`, `argsT`, `ElasticsearchConfig`, `CommitTransactionCommandInput`, `CompoundPath`, `HookNextFunction`, `IAzureMapFeature`, `VFile`, `EventAttendance`, `types.MouseData`, `HapiRequest`, `IEmailTemplateSaveInput`, `MetaheroToken`, `EditFn`, `SingleBar`, `CipherObject`, `Joiner`, `MigrateEngineOptions`, `CategoryResult`, `ReaderIO`, `EventUI`, `ZoneDef`, `AgencyApiRequest`, `RectInfo`, `XRPose`, `ComplexPluginOutput`, `MatrixReader`, `FlightDataModel`, `FileTypeResult`, `CKBConfig`, `BTCMarkets.instruments`, `JessParser`, `EmailPayload`, `DeleteInvitationsCommandInput`, `OasVersion`, `serialization.Serializable`, `AdministrationScreenService`, `BillCurrencyUnit`, `CreateRegistryCommandInput`, `OptionsObject`, `EditRepositoryPayload`, `SimpleBinaryKernelImpl`, `AutofillMonitor`, `RxJsonSchema`, `Equality`, `CallIdChangedListener`, `StyleDoc`, `RecurringActivity`, `AsyncTestBedConfig`, `PolicyFromES`, `Fig.ExecuteShellCommandFunction`, `IsInstanceProps`, `OSD_FIELD_TYPES`, `PlaceIndex`, `UpSetJSSkeletonPropsImpl`, `CheckType`, `PuzzleID`, `RegionConfig`, `CompressOptions`, `ClientSideSocket`, `FloatAnimationKeyframeHermite`, `KxxRecord`, `PrimitiveProps`, `FloatBuffer`, `ApolloRequest`, `SignatureEntry`, `GetDeviceRequest`, `Listing`, `Tensor`, `StyleFunction`, `DeleteBuilder`, `JsonDocsDependencyGraph`, `WorkflowContext`, `Filterable`, `PropertyInjectInfoType`, `IJsonResourceInfo`, `BinData`, `VideoChatSession`, `SeriesData`, `AckRange`, `ApolloReactHooks.QueryHookOptions`, `RestApplication`, `RestRequest`, `NumberOptions`, `SGSymbolItem`, `AccountGameCenter`, `OAuth`, `NohmClass`, `DistinctQuestion`, `ExposedThing`, `TooltipItem`, `MemoryEngine`, `f32`, `ResolvedTypeReferenceDirectiveWithFailedLookupLocations`, `SassNumber`, `DataResult`, `HyperScriptHelperFn`, `InputSize`, `List`, `SharePluginSetup`, `ApiRevisionContract`, `Legend`, `m.Recipe`, `DataResolverInputHook`, `api.State`, `VueRouter`, `Memento`, `AnimationNode`, `GuildEmoji`, `THREE.TextureDataType`, `KeySequence`, `DragBehavior`, `SQLParserListener`, `FunctionDataStub`, `AlainConfigService`, `ConsoleFake`, `ProofTest`, `ITuple2`, `After`, `Algebra.GroupNode`, `Apply`, `LoggerTransport`, `ICredentialsState`, `GetByIdOptions`, `DaffOrderItem`, `DonwloadSuccessData`, `AnnotationDimensions`, `IActorDef`, `NexusEnumTypeDef`, `B5`, `Decorators`, `MdcTextField`, `IPropertyPaneField`, `TestInputHandler`, `TestDialogConfig`, `AtomArrowBlockElement`, `IProperties`, `RLANAnimationTrackType`, `EditorProps`, `CryptoKeyPair`, `MCU`, `DescribeEventCategoriesCommandInput`, `IHelper`, `RoundingFn`, `AgChartOptions`, `SCNSceneRenderer`, `PiProperty`, `Protocol.Runtime.RemoteObject`, `DataCardsI18nType`, `MoveEvent`, `MatchList`, `IAssetItem`, `FeedbackDelay`, `CPUTensor`, `ProductV2`, `QueryResolvers`, `UIProposal`, `IntegrationMapService`, `ChainableConnectors`, `BotAnchorPoint`, `L2Data`, `TOutput`, `PackageLock`, `CustomScript`, `GridsterComponentInterface`, `ChangeBuffer`, `ThemeContextValue`, `XjointInfo`, `HashAlgorithm`, `IRegionConfig`, `IProductTypeTranslatable`, `MainSettings`, `ChainGetter`, `WizardComponent`, `ModelJsonSchema`, `PipeFlags`, `UICarouselItemComponent`, `ReflectType`, `RepoState`, `EngineDetails`, `StatementAst`, `IOffset`, `WebSocket`, `EntityCollectionService`, `RawTree`, `ClientAuthCode`, `MortalityService`, `StatementedNode`, `RematchRootState`, `IExpressionLoader`, `RenameFn`, `MaybeAsyncHelpers`, `PasswordPolicy`, `MailboxEvent`, `PostgresTestEntity`, `TagConfiguration`, `IParseProps`, `IndexThresholdAlertParams`, `EIP712Types`, `FilterItem`, `CeramicConfig`, `UpdateManyResponse`, `lsp.Range`, `TableValidator`, `PluginOptionsSchemaArgs`, `CallEndedListener`, `SecureClientQuery`, `DescribeReplicationTaskAssessmentRunsCommandInput`, `DateTimeFormatPart`, `Button`, `ModuleInfo`, `FilterManager`, `NetworkSet`, `CloudFormationResource`, `LoadmoreNode`, `VtxLoader`, `CodeProps`, `FilterCreator`, `IErrorObject`, `ts.IScriptSnapshot`, `btSoftBodyWorldInfo`, `JsxOpeningLikeElement`, `InternalBema`, `float32`, `ProgramArgs`, `AddressBookInstance`, `Point4d`, `PostRepository`, `t.TypeOf`, `CreateTagDto`, `BLE`, `SelectOption`, `RootReducerState`, `QueryInfo`, `WhereExpression`, `Bounds`, `EmailDoc`, `ModalConfig`, `ClassPrototype`, `FunctionBody`, `CashScriptListener`, `ChordNode`, `AzureAccessOpts`, `BleService`, `AttachmentView`, `OrderByClauseArgument`, `StringPart`, `HSL`, `PublicationView`, `Keyring`, `QCProject`, `DescribeChannelBanCommandInput`, `SidebarMenu`, `Scraper`, `PolicyBuilderElement`, `FlexConfigurationPlugin`, `GetProductSearchParams`, `IDocEntryWeight`, `XI18nService`, `SVGTitleElement`, `LocalFraudProof`, `CandyDateType`, `StackSeriesData`, `EventHandlerInfo`, `DataViewMetadataColumn`, `CompType`, `LRU`, `StackNavigationOptions`, `apid.EditManualReserveOption`, `PlaybackStatus`, `TransformFlags`, `ENSService`, `WordCloudDataPoint`, `ECPairInterface`, `StepModel`, `SimpleOrder`, `ScriptAst`, `StableSwap`, `GeometryQuery`, `ChartsPlugin`, `TimerProps`, `DistanceM`, `IconifyAPIQueryParams`, `CLM.UserInput`, `DynamicCstr`, `IAuthZConfig`, `requests.ListCompartmentsRequest`, `ProviderProxy`, `Action`, `InputValidationService`, `FlipperServerImpl`, `CommentService`, `SimpleFrameStatistics`, `ImageOptions`, `MagentoCartFactory`, `PropertiesSource`, `EnvTestContext`, `FolderWithId`, `ModelStoreManagerRegistry`, `AppInstanceProposal`, `SequenceContract`, `DeepPath`, `Todos`, `Accessory`, `d.OutputTargetWww`, `PlayCase`, `BillPayer`, `IAmazonImage`, `Project`, `loaderCallback`, `FadingFeature`, `SFCDescriptor`, `Docker.Container`, `ListOfRanges`, `S2GeometryProvider`, `match`, `GraphAnimateConfig`, `VimState`, `sdk.SpeechTranslationConfig`, `SerializerTypes`, `ServerRequestHandler`, `RenderAtomic`, `ScreenProps`, `NavigationBindings`, `AuthorizationDataService`, `K2`, `PlantMember`, `MyUser`, `OtherArticulation`, `WeaponObj`, `iconType`, `DokiTheme`, `NzTabNavItemDirective`, `WaiterConfiguration`, `CounterFacade`, `TableInsertEntityHeaders`, `objPool.IPool`, `TTransport`, `JsonaObject`, `ForceSourceDeployErrorResponse`, `ClientTools`, `ForOfStatement`, `types.DocumentedType`, `SWRConfigInterface`, `UserIDStatus`, `AlertProps`, `LoadMany`, `AudioWorkletNode`, `RpcKernelBaseConnection`, `IFullProps`, `RequestChunk`, `IFileStat`, `CreditedImage`, `UnidirectionalLinkedTransferAppState`, `CueAndLoop`, `ScenarioEvent`, `SpreadElement`, `DaffCompositeProduct`, `TweetMediaState`, `InternalNode`, `CreateDashboardCommandInput`, `FileTypeEnum`, `HostInstructionsQueue`, `IntegerType`, `OAuthEvent`, `OptionsStackingValue`, `ValidationType`, `RepoSyncState`, `StateInterface`, `Ctx`, `AcrylicConfig`, `PaginationService`, `PreparsedSeq`, `JsonDocsEvent`, `$p_Predicate`, `DynamicStyleSheet`, `Saga`, `GitExtension`, `EncodeInfoDisplayItem`, `RangesCache`, `ClientScopeRepresentation`, `ClusterInfo`, `BaseUI5Node`, `EnvironmentType`, `IAmExportedWithEqual`, `PWAContext`, `VirtualHub`, `IWorkflowData`, `WorkNodePath`, `knex.Transaction`, `SecureChannel`, `oai3.Schema`, `WebSocketChannel`, `turfHelpers.FeatureCollection`, `AccordionStore`, `RequestWithSession`, `SurveyQuestionEditorTabDefinition`, `TextShadowItem`, `EnumProperty`, `ROM`, `HashMapState`, `HTMLAnchorElement`, `IHandler`, `JJunction`, `RnM2TextureInfo`, `BrowserDriver`, `ResolvedInfo`, `HemisphereLight`, `IntegrationInfo`, `GridColumnExtension`, `vscode.WebviewPanel`, `SelfDescribing`, `fhir.Composition`, `DebtTokenContract`, `GuildResolvable`, `IntegrationSettingService`, `JPABaseShapeBlock`, `InjectedProps`, `ImportReplacements`, `FetchResponse`, `RaiseNode`, `TransactionSignature`, `TinyDate`, `MDCCornerTreatment`, `SmartPlayer`, `N4`, `AssociationCCRemove`, `Pool3DProgram`, `SQLRow`, `ImageRequestInfo`, `AstBlock`, `CatExpr`, `LocalEnv`, `ResourcePrincipalAuthenticationDetailsProvider`, `HTMLCanvasElement`, `RangeBasedDocumentSymbol`, `OnPushList`, `BriefcaseDb`, `IRolesMap`, `TraverseContext`, `ChannelResolvable`, `code.Position`, `MultiLanguageBatchInput`, `IQueryOptions`, `GetCanonicalFileName`, `DialogRow`, `BorrowingMutex`, `PluginComponents`, `GetServiceCommandInput`, `MockEntityMapperService`, `SchemaElement`, `GridItem`, `TextureSourceOptions`, `LossOrMetricFn`, `AppStateModel`, `ErrorArea`, `reqType`, `IGetTimeSlotInput`, `SidebarState`, `AnalyticsFromRequests`, `CustomResourceRequest`, `ITenantService`, `IFormState`, `Drawing`, `RootStore`, `SelectItem`, `VoiceOptions`, `Birds`, `SubgraphDeploymentIDIsh`, `AssetUtils`, `ParentGroup`, `BarData`, `PrismService`, `CollisionTree`, `dayjs.Dayjs`, `ChimeSdkWrapper`, `HttpProbe`, `makerjs.IModel`, `RegisterOptions`, `TrieNode`, `StreamDeck`, `VehicleEvent`, `ICitable`, `PieSectorDataItem`, `DateFnsHelper`, `DeleteDatasetCommand`, `SqlTuningTaskSqlExecutionPlanStep`, `ts.FormatCodeOptions`, `ItemStyle`, `StartExportTaskCommandInput`, `NativeEventSubscription`, `EmptyStatement`, `Extent`, `ModelResponse`, `NodeVersion`, `ModifyClusterCommandInput`, `GithubRepo`, `LoansService`, `KanbanBoardState`, `ParseResults`, `GridColumnConfig`, `ResolverContext`, `FrameRequestCallback`, `BoundedGrid3D`, `DePacketizerBase`, `ScopedHandler`, `ExecutionWorker`, `IconButtonGridProps`, `DeleteTransformsRequestSchema`, `IStrapiModelExtended`, `Masset`, `freedom.FreedomInModuleEnv`, `Tunnel`, `GeoJsonProperties`, `Optic`, `textChanges.ChangeTracker`, `RenderTarget`, `SortEvent`, `parser.PddlSyntaxNode`, `CallReturnContext`, `NodeWrap`, `Ellipsoid`, `RecordManager`, `express.RequestHandler`, `PartialCell`, `UnaryOpProgram`, `ScriptingDefinition`, `VehicleCountRow`, `PaymentProvider`, `AZSymbolKind`, `JwtUserData`, `S3Config`, `AuthorReadModel`, `MatChipInputEvent`, `ValueMetadataBoolean`, `RemoveEvent`, `PointerCoordinates`, `CrossMentor`, `SimpleOption`, `AnySpec`, `IPicture`, `MessageHeader`, `EntityDictionary`, `IPromise`, `HttpServerType`, `FP`, `TypeVarType`, `IAnyType`, `AUTWindow`, `A2`, `Node.MinimalTransaction`, `PartitionStyle`, `GetQueryStatus`, `LocIdentifier`, `RouterMenuItem`, `FacetValue`, `AsyncSchema`, `IParticleValueAnimation`, `ShortChannelId`, `CoinbaseKey`, `EngineArgs.ApplyMigrationsInput`, `AnyElt`, `StorableComponent`, `CheckAndApproveResult`, `IRequireMotionAction`, `SectionVM`, `DispatcherPayloadMeta`, `ILinePoint`, `ContainerRef`, `DocTableCell`, `EnvFile`, `CanvasLayer`, `Focus`, `FunctionShape`, `MetaBlock`, `ViewerOut`, `DQAgent`, `PickingInfo`, `SkeletalComponent`, `CheckRunPayload`, `SpotLight`, `Vector2Arrow`, `AnchoredChange`, `IBifrostInstance`, `SendInfo`, `ContextSetImpl`, `BooleanLiteral`, `u8`, `JSONSchema3or4`, `HandlebarsTemplateDelegate`, `DeleteBucketTaggingCommandInput`, `DefineDatas`, `NavBarProps`, `TaskManagerConfig`, `Z64Online_ModelAllocation`, `OS`, `NettuAppRequest`, `ProjectRole`, `PluginObject`, `FSJetpack`, `ExtractModConfig`, `KeycloakService`, `Posts`, `IDevice`, `filterInterface`, `Thread`, `GfxRenderPassP_WebGPU`, `PureSelectorsToSelectors`, `vscode.OnEnterRule`, `IParams`, `LoggerConfig`, `CSSResolve`, `AllureGroup`, `CommonAlertState`, `SearchSourceFields`, `ThyDialogRef`, `HTMLStyleElement`, `ServiceWorkerConfig`, `IServiceIdentifier`, `TableFilterDescriptor`, `DocLinksStart`, `SurveyElementEditorContentModel`, `SaveFileReader`, `WritableStream`, `AttributeMask`, `ISPList`, `ExecutionInfo`, `EnumOptions`, `ETHOption`, `SceneControllerConfigurationCCSet`, `RoleType`, `WhenCause`, `AssetInfo`, `G6Edge`, `Micromerge`, `QueryMwRet`, `StartFrame`, `GridIndex`, `ListRepositoriesCommandInput`, `TIndex`, `AuthSigner`, `UpdateBotCommandInput`, `FabricPointerEvent`, `TemplateType`, `EqualityFn`, `Phase`, `RegisteredServiceSingleSignOnParticipationPolicy`, `BrowsingData.DataTypeSet`, `formValues`, `SavedObjectsDeleteOptions`, `JPiece`, `MDCTopAppBarAdapter`, `ECSqlInsertResult`, `MiddlewareResult`, `RemoteDatabase`, `EncString`, `NotebookCellOutput`, `PostcssStrictThemeConfig`, `EventParams`, `StepConditional`, `WebGLRenderer`, `ConnectOptions`, `ethers.providers.TransactionRequest`, `PUPPET.payloads.Message`, `ListFilesStatResult`, `IBasicSessionWithSubscription`, `Customizable`, `NamedModel`, `AttachPolicyCommandInput`, `CssNode`, `LogAttributes`, `ListView`, `EventListenerRegister`, `ImageGallerySource`, `HeaderObject`, `SerializedTreeViewItem`, `UpdateData`, `ShortValidationErrors`, `pxt.auth.Badge`, `TemplateSource`, `GfxProgramDescriptor`, `SfdxWorkspaceChecker`, `ts.WatchOfConfigFile`, `CBPeripheralWithDelegate`, `FieldAppearanceOptions`, `PropertyLike`, `ReConfigChunk`, `SimpleDate`, `AndroidBinding`, `JSONSourceData`, `NzSliderValue`, `UrlGeneratorContract`, `DisjointSetNode`, `RouteConfig`, `DaffOrderTotal`, `TypeDefinitionNode`, `AggregateMeta`, `Process`, `Sinks`, `MembersInfo`, `ResolvedNative`, `FontName`, `PanelComponent`, `IUserWithGroups`, `EmitFlags`, `StateVariables`, `LanguageConfiguration`, `createAction.Action`, `TBEvent`, `SubEntityProps`, `Revalidator`, `JoinTable`, `WS.MessageEvent`, `CheckerBaseParams`, `timePickerModule.TimePicker`, `IndexFormat`, `CameraUpdateResult`, `DragSourceMonitor`, `CreateSelectorFunction`, `ContractInfo`, `ICXCreateOrder`, `RpcRequestFulfillment`, `IPropertiesAppender`, `CommandLineAction`, `RenderMode`, `ParameterNameValue`, `NetworkScope`, `TimeChangeSource`, `ReplyShortChannelIdsEndMessage`, `GetNetworkProfileCommandInput`, `DependencyName`, `LineIndexSnapshot`, `APIHandler`, `GenerateAsyncIterable`, `TableSuggestion`, `HistoryType`, `ExpectResponseBody`, `AlterTableModifyColumnBuilder`, `RootStoreType`, `BuildOptionsInternal`, `CalculateNodePositionOptions`, `WatcherHelper`, `SessionExpired`, `LocalSession`, `AngularScope`, `NzCarouselContentDirective`, `OnResolveArgs`, `MatchArgsToParamsResult`, `IntrinsicTypeDescriptor`, `TimelineDateProfile`, `EnvSimple`, `LoadedConfigSelectors`, `ReferencePosition`, `LayersTreeItem`, `StateDB`, `RenderTask`, `DBAccessQueryResult`, `Vec2`, `CustomCompletionItem`, `ParserResult`, `AnimationEvent`, `InputButtonCombo`, `SyncOptions`, `Retro`, `OOMemberLookupInfo`, `ClampedMonth`, `ISpace`, `EditorConfig`, `HintFile`, `DeleteSnapshotScheduleCommandInput`, `TConstructor`, `PointerStates`, `SCHEMA`, `EnhancedSelector`, `SignalID`, `RuleTarget`, `CircuitState`, `QueryTuple`, `ListMultipartUploadsRequest`, `AnyCardInGame`, `FetchType`, `ProviderConstructor`, `ConstantExpr`, `RenderItem`, `HsMapService`, `EqualityConstraint`, `DependencyManager`, `AppConfigService`, `Electron.WebContents`, `IHooksGetter`, `MarkdownItNode`, `FormatParams`, `TestRenderTag`, `Flanger`, `AppAndCount`, `DialogState`, `Arc3d`, `DarwinMenuItemConstructorOptions`, `IpfsApi`, `Mismatch`, `ISeries`, `Poller`, `faunadb.Client`, `SlippageTolerance`, `EventDispatcher`, `d.HotModuleReplacement`, `PutAccountDedicatedIpWarmupAttributesCommandInput`, `TranslateResult`, `INodeData`, `IMatch`, `ConnectionCloseFrame`, `NSArray`, `IndexField`, `SelectQueryNode`, `GaugeRangeProperty`, `CreateEventSubscriptionMessage`, `TypeRegistry`, `ts.LineAndCharacter`, `CommandInputParameterModel`, `VisToExpressionAst`, `FractalisService`, `DirectiveMetadata`, `PathFinderPath`, `FileBuild`, `ProductSet`, `PostsService`, `GameName`, `PhrasingContent`, `HtmlContextTypeOptions`, `CompilerFileWatcher`, `SelectorInfo`, `InlineDatasources`, `ActionGroup`, `AdminDatabase`, `ScreenSpaceProjection`, `Electron.BrowserWindow`, `TYPE_AMOUNT`, `Timing`, `ChildrenService`, `MarkdownIt`, `ICreateUserDTO`, `EdaBlankPanelComponent`, `IParseOptions`, `EncounterState`, `CustomQueryState`, `CommitterMap`, `MatchEvent`, `IFilterContext`, `ShaderPass`, `FailedShard`, `ActiveSession`, `UploadProps`, `TranslateOptions`, `IndividualTestInfo`, `Elt`, `CalendarViewType`, `jest.CustomMatcher`, `DidExecutedPayload`, `ComposedPublicDevice`, `ParticleEmitter`, `vscode.InputBoxOptions`, `MaybeCurrency`, `UnboundType`, `T.Refs`, `PlugyPage`, `ITagInputItemProps`, `Animated.CompositeAnimation`, `TimelineItemProps`, `Star`, `CommitChangeService`, `TreeSelectionState`, `GeometryKindSet`, `MenuContext`, `StructPrimitiveType`, `LimitExceededException`, `SuggestionsRequest`, `UpdateFilter`, `StatePropsOfCombinator`, `HsButton`, `JsonRpcRecord`, `BuilderEntry`, `MarkExtensionSpec`, `OperationStatus`, `Dryad`, `BoxKeyPair`, `DemoConfig`, `T.Effect`, `Secrets`, `CompareResult`, `BehaviorMode`, `IPermissionState`, `DynamicClasses`, `CollectorEntity`, `bAsset`, `GrayMatterFile`, `CourseId`, `Tabs.Tab`, `IQueryParam`, `ChunkGroup`, `PaletteType`, `SecretRule`, `Redex`, `STColumnButton`, `OmvFeatureFilterDescription`, `UserStore`, `PolygonEditOptions`, `UncachedNpmInfoClient`, `HybridConnection`, `FragmentSpread`, `SolStateMerkleProof`, `VNodeChildren`, `Downloader`, `IpcEvent`, `DeployFunction`, `ProjectState`, `Factory.Type`, `ListrBaseClassOptions`, `IAssetComponentItem`, `SocketStream`, `bsiChecker.Checker`, `NetMDInterface`, `MigrateDev`, `UseComponent`, `IResponseAction`, `StreamSpecification`, `NetworkConfiguration`, `PageModel`, `LoadingController`, `CalloutContextOptions`, `ethers.utils.Deferrable`, `IClientRegistrarOptions`, `KeymapItem`, `Mocha.MochaOptions`, `CombatService`, `React.TouchEvent`, `FieldConfig`, `evt_exec`, `WebrtcConn`, `NormalBold`, `hubCommon.IModel`, `ResponderConfiguration`, `FoldingRangeParams`, `EditorSuggestionPlugin`, `ImageUse`, `todo`, `ScriptBuilder`, `IFluidResolvedUrl`, `SolverT`, `IonRouter`, `CkElementProps`, `ActionSheetController`, `MockState`, `PartialTheme`, `CompositeDisposable`, `FragmentType`, `RecoilTaskInterface`, `VM`, `ConnectionsManagerService`, `RectDelta`, `P2`, `V1WorkflowInputParameterModel`, `AccountEmail_VarsEntry`, `ModelMesh`, `d.Encapsulation`, `MetadataRecord`, `Contour`, `PointCloudOctreeNode`, `Vec3Term`, `A7`, `CompilerBuildStart`, `ReadWriteStream`, `Seeder`, `ArgStmtDecl`, `FlatList`, `DependencySpecifier`, `SiteTreeItem`, `GfxBufferFrequencyHint`, `QueueObject`, `PrimaryKeyType`, `Conv2DProgram`, `ValueAccessor`, `AccountAttribute`, `EndPointService`, `IpAddressWithSubnetMask`, `Effector`, `Bot`, `IFeed`, `TreeViewNode`, `GitBlame`, `DialogService`, `WorkRequestResourceMetadataKey`, `TableData`, `CollectionContext`, `IndexState`, `RootValue`, `NuxtAxiosInstance`, `LogRequest`, `Aes256Key`, `DeleteListenerCommandInput`, `ProviderToken`, `ContractFactory`, `ChainService`, `SelectedScriptStub`, `LogContext`, `DropdownMenuInitialState`, `ImmutablePeriod`, `ListParticipantsResponse`, `VMLElement`, `Nav`, `TreeNodeType`, `t_63513dcd`, `RemoteUser`, `CodeRange`, `BerryOrm`, `DescribeImagesCommandInput`, `IOtherExpectation`, `AutofillField`, `Todo`, `location.CloudLocationOption`, `ServiceInfo`, `PadplusContactPayload`, `UI`, `CRDTObject`, `LengthParams`, `IMessageMetadata`, `WaitImageOptions`, `UnsupportedOperationException`, `ResponseFactory`, `MaterialCache`, `UICollectionViewLayout`, `JsonFile`, `browser.tabs.Tab`, `MetricDimension`, `OpDescription`, `ListingModel`, `unified.Processor`, `TransformPivotConfig`, `Pubkey`, `WsChartService`, `ActiveMigrations`, `RtmpResult`, `ColorPickerEventListener`, `d.JsonDocsMethod`, `VpnGateway`, `FunctionProps`, `DataFormat`, `Teams`, `CodeActionKind`, `FileExtensionMap`, `Vertices`, `ListrEvent`, `LoadingOptions`, `BVEmitter`, `DigitalNode`, `SortService`, `SemanticTree`, `ShapeDef`, `PersistedState`, `RawPackages`, `Insets`, `TransformBaseline`, `ModelHandle`, `ZoneSpec`, `TestHandler`, `MaybeArray`, `Key`, `DataSourceParameters`, `CodeFlowAnalyzer`, `Dropout`, `Contents`, `ApiMethodScheme`, `SymInt`, `ConfigurationCCGet`, `ts.DocumentRegistry`, `PathParser`, `Myth`, `SingularReaderSelector`, `Step`, `ClockOptions`, `WorldLight`, `Redux.Reducer`, `TimingInfo`, `TabOption`, `IpcResponse`, `ListJobsCommandOutput`, `ComputationCache`, `CertificateAndPrivateKeyPair`, `ScaleObject`, `FullUser`, `PreferenceStateModel`, `MessageValue`, `OpenAPIV3.SchemaObject`, `NestedPageMetadata`, `BadgeStyleProps`, `ColumnSeriesDataItem`, `IHttpRes`, `MaterialColor`, `RebaseEntry`, `ILine`, `Sblendid`, `DateUtilsAdapter`, `SwalOptions`, `CalculationId`, `Radius`, `Footnote`, `ISurveyStatus`, `FIRDatabaseReference`, `WordOptions`, `WithCondition`, `SectionsType`, `ISolutionService`, `CreepSetup`, `GraphicMode`, `CoordinatesObject`, `ILinkInfo`, `XPCOM.nsIHttpChannel`, `RecognitionException`, `StringOrNumber`, `Defs.CompactdState`, `AxesTicksDimensions`, `MapFunction`, `gameObject.Fish`, `SignedBy`, `EchPalette`, `DMMF.Mappings`, `SpawnSyncReturns`, `DeeplinkParts`, `internal`, `DriveItemData`, `JID`, `MediaListOptions`, `IDataProvider`, `ComponentMap`, `ProductType`, `IDirectoryModel`, `InputValueDefinitionNode`, `BabelFileResult`, `QAction`, `SendAction`, `TasksStoreService`, `Roles`, `DiffHunk`, `IFileStore`, `ArrowFunction`, `LinkRecordType`, `DescribeTagsCommandInput`, `MatMenuPanel`, `SearchModeDescription`, `TelemetrySender`, `IPublisher`, `VanessaEditor`, `CkbTxGenerator`, `vscode.TextDocumentContentChangeEvent`, `OptionsWithUrl`, `MultiFn1O`, `PutPermissionCommandInput`, `AwsClientProps`, `WEBGL_debug_renderer_info`, `GeneralActionType`, `RootProps`, `CommandLineArgs`, `Observer`, `Performance`, `RowOfAny`, `IAPIRepository`, `DDL2.Schema`, `WithGenericsSubInterface`, `MonthOrYearComponents`, `IDesignLike`, `DemoAppAction`, `ARGS`, `IPC.IFilePickerFileInfo`, `HapService`, `InputObject`, `GetTableRowsResult`, `DOMOutputSpec`, `FrameBase`, `ConvertedType`, `MetricCollection`, `GravityInfo`, `Uint16Array`, `AppearanceProviderFor`, `LightData`, `AuthoringWorkspaceService`, `AnalyticsProvider`, `ValidationContext`, `RequestCredentials`, `OnPreResponseHandler`, `DisclosureStateReturn`, `IdentifyOperation`, `GetProjectCommandInput`, `GridLayout`, `WorkerInterface`, `PathPredicate`, `PositionedTickValue`, `ProviderIndex`, `UseQuery`, `JKRArchive`, `ZeroXOrders`, `ILabShell`, `next.Sketch`, `ClientChangeList`, `IGif`, `BotAdapter`, `BitbucketPrEntity`, `TextElementGroup`, `requests.ListCaptchasRequest`, `Scheme`, `TheEventbridgeEtlStack`, `IBatteryEntityConfig`, `ISourceLocation`, `IFeatureCommand`, `CallbackDataParams`, `PrismaService`, `ZoneManagerProps`, `FileObject`, `HttpAuthenticatedConnection`, `FunctionAppService`, `SceneControllerConfigurationCCGet`, `ElementMetadata`, `SpatialDropout1DLayerConfig`, `DaffStatefulCartItem`, `CompiledHierarchyEntry`, `TestDispatcher`, `page`, `ParameterExpression`, `PIXI.interaction.InteractionEvent`, `LeafletEvent`, `Driver`, `ExtraContext`, `BoomTheme`, `CachedVoiceState`, `FactoryOptions`, `SavedObjectsExportablePredicate`, `RemoteCallParticipants`, `ItemPredicate`, `PopupType`, `GfxBindings`, `RulesModel`, `KsDiagnostic`, `IndexedNode`, `ExpressionAttributeValueMap`, `SortOption`, `GetState`, `AngularFirestore`, `ShapeView`, `RepositoryStatisticsReadModel`, `SoftwareTransaction`, `IPlayable`, `DAL.DEVICE_ID_SYSTEM_DAC`, `EmbeddableStateTransfer`, `Elements`, `Invalidator`, `VariableStatementStructure`, `SearchSessionsConfig`, `EventManagerConfig`, `RTCTrackEvent`, `ArenaCursor`, `PgClass`, `UpdateParameters`, `ItemData`, `PersonalAccessTokenCredentialHandler`, `Prefix`, `DescribeUsersCommandInput`, `Recognizer`, `TrackerConfig`, `TokenSharedQueueResult`, `StreamingClient`, `Letter`, `ByteReader`, `UmlNotation`, `RecommendationType`, `Screenview`, `CanvasEvent`, `MimeType`, `OcticonSymbol`, `ObjectPool`, `StoreManager`, `In`, `ParsedSelector`, `StatedBeanContextValue`, `Placeholder`, `EventActionHandlerMutationActionCallable`, `AccordionItemComponent`, `AnyExpressionRenderDefinition`, `SignalingClient`, `IListItem`, `ScalarMap`, `CalcScaleAnmType`, `BigComplex`, `Uniform`, `NestedResource`, `TestFailure`, `MatTab`, `EIP712Domain`, `DisassociateMemberCommandInput`, `UpdateDatasetEntriesCommandInput`, `StaticBlog`, `IIconProps`, `EventAsReturnType`, `DataAnalyzeStore`, `d.PrerenderResults`, `cxapi.Environment`, `DoClass`, `MapStateProps`, `DragCheckProps`, `TruncatedNormalArgs`, `ReactDivMouseEvent`, `RegularNode`, `T.Matcher`, `AbstractUIClass`, `lex.Token`, `RestServer`, `BuildingEntity`, `DescribeWorkspaceDirectoriesCommandInput`, `EnumLiteralType`, `CreateDBInstanceCommandInput`, `ITaskConfig`, `SourceCode`, `StyledIconProps`, `JwtPair`, `OaiToOai3FileInput`, `StoreValue`, `ExtendedKeyInfo`, `IAmazonFunctionUpsertCommand`, `TMeta`, `TableEntityResultPage`, `ShapeInfo`, `FC`, `IEsSearchResponse`, `HitCircleVerdict`, `DescribeDBClustersCommandInput`, `STATE`, `Defines`, `TileSetAssetPub`, `PhotosaicImage`, `INetEventHandler`, `core.DescribePath`, `DeleteRoomCommandInput`, `DkrTextureCache`, `Initializer`, `ReplicaOnPartition`, `JSONChunk`, `ModelViewer`, `OrbitControl`, `GraphImmut`, `CanvasRenderingContext2D`, `CoinSelectOptions`, `ErrorReason`, `PluginsConfig`, `WebGLProgram`, `IChunkHeader64`, `MatCheckbox`, `SaveEntitiesSuccess`, `EntityComparator`, `CsmPublishingCredentialsPoliciesEntity`, `DownloadItem`, `requests.DeleteJobRequest`, `ArrowProps`, `ParsedPacket`, `GenericGFPoly`, `TimeFormat`, `GAMEOBJECT_SIGN`, `InteractionType`, `OutputError`, `ReferenceRecord`, `PaginationState`, `MysqlError`, `ZRRawEvent`, `NumberLiteralContext`, `SFATextureArray`, `ECDSASignature`, `RustError`, `EncArrayBuffer`, `CreditCardEscrow`, `core.IProducer`, `TEntry`, `CodelistRow`, `AcceptChannelMessage`, `Realm.ObjectSchemaProperty`, `FeeLevel`, `DataFrameAnalyticsConfig`, `DaffCategoryIdRequest`, `SpatialViewState`, `NdQtNode`, `EventTarget`, `IEventContext`, `SearchByIdRequest`, `NaotuConfig`, `ExactPackage`, `ResponsiveColumnSizes`, `UpdateQueue`, `DeleteChannelMembershipCommandInput`, `CardFooterProps`, `WindowRefService`, `CheckpointProps`, `ElementHandleForTag`, `CollectionState`, `FastTag`, `AndroidProjectConfig`, `CallAdapter`, `d.CompilerBuildStart`, `NotificationHandler`, `requests.ListHealthChecksVantagePointsRequest`, `Type_Struct`, `GraphQLSchema`, `DialogBase`, `RouteContext`, `GestureEvent`, `ObjectBindingPattern`, `QualifiedName`, `Semigroupoid2`, `HandlerExecutionContext`, `StylesProps`, `ElementCore`, `LuaComment`, `ErrorItem`, `AccountDevice`, `IBudgieNode`, `BooruCredentials`, `IGameMessage`, `EstreeNode`, `AuctionView`, `GetAccountInfoRequest`, `EncryptedWalletHandler`, `CannonPhysicsComponent`, `ListApplicationsResponse`, `ESLMediaRule`, `GraphRbacManagementClient`, `ThermostatMode`, `WindowInfo`, `OpenSearchDashboardsRequest`, `DocString`, `TextureDataType`, `UserCredential`, `FIRDataSnapshot`, `GoEngineState`, `InstanceProps`, `restify.Response`, `CloudSchedulerClient`, `EntityDbMetadata`, `Parslet`, `ClaimDTO`, `GanttViewDate`, `IDotEnv`, `ConfigStructShape`, `React.ReactPortal`, `GraphQLNamedOutputType`, `FlattenInterpolation`, `MicrosoftComputeExtensionsVirtualMachinesExtensionsProperties`, `LLVMContext`, `IL10nsStrings`, `MapGroup`, `JQuery.Event`, `CatsService`, `KeyValueChangeRecord_`, `ServerItem`, `DSpaceObject`, `IDatabaseDataSource`, `CustomRule`, `StepsProps`, `AxiosInstance`, `ParticleArgs`, `DeleteDomainCommandInput`, `GetColumnWidthFn`, `TruncatableService`, `GtkElement`, `NumberOperands`, `PackageUrlResolver`, `requests.ListUsersRequest`, `GfxSamplerP_WebGPU`, `JSONProtocol`, `OrderPair`, `ISeedPhraseStore`, `PIXI.Text`, `PatternMappingNode`, `StepDetailsExposedState`, `TinyDateType`, `EntityType`, `ShallowRenderer`, `TypeSet`, `UpdateApplicationCommandOutput`, `EntityTypeDecl`, `BusInstance`, `FetchFunction`, `NetworkManagementClient`, `BrowserFeatureKey`, `IpcRenderer`, `WsProvider`, `ITestBillingGroup`, `Shared.SubscriberFactory`, `TSTypeLiteral`, `RneFunctionComponent`, `BlockFriendsRequest`, `POISearchParams`, `SelectionArea`, `QueryListProps`, `L2Creature`, `DiagnosticInfo`, `CreateClusterCommand`, `PrinterType`, `MockTextChannel`, `MessageStatusService`, `ApplicationTheme`, `TitleCollection`, `Persist`, `RenderStatistics`, `Attempt`, `VersionComponent`, `EndpointConfig`, `MerchantGameWinningEntity`, `Shared.TokenRange`, `UnitsImpl`, `MerchantMenuOrderEntity`, `ScatterProgram`, `OutputChannelLogger`, `DetectorCallback`, `PickPoint`, `DemandDTO`, `HTMLImageSource`, `IConnectionFormSubmitData`, `SModelIndex`, `Acc`, `PredicateType`, `DataPacket`, `TermAggregationOptions`, `NotifierService`, `AlertTableItem`, `ElementCreationOptions`, `GetDedicatedIpCommandInput`, `requests.ListPackagesRequest`, `ArgumentTypes`, `IController.IFunction`, `FileWithPath`, `ILoadbalancer`, `TransactionDetail`, `PluginConfig`, `ScrollToService`, `LoginUriApi`, `InternalLabConfiguration`, `ENDAttributeValue`, `NavigatorDelegate`, `AgencyApiResponse`, `IUi`, `ISegSpan`, `CompareAtom`, `PolygonFadingParameters`, `protos.common.SignaturePolicy`, `LogState`, `MarketCreatedInfo`, `InputEventKey`, `FeeAmount`, `BitmapDrawable`, `CommitInfo`, `MetadataCache`, `DataDefinition`, `PlacementConstraint`, `ProtocolFile`, `IEventInfo`, `ISnapshotContents`, `BaseDocumentView`, `TokenValue`, `CSSToken`, `UnionOf`, `ReactInstance`, `ChainStore`, `DebugConfiguration`, `PaneOptions`, `RRTypeWindow`, `UntypedProduct`, `RunnableTask`, `IsLocalScreenSharingActiveChangedListener`, `HyperModelingDecorator`, `SpacedRepetitionSettingsDelegate`, `IDData`, `Path4`, `ChildrenType`, `OpenEditorNode`, `Android`, `Count`, `HttpClientConfig`, `SubType`, `InstanceData`, `ScriptParsedEvent`, `TileGrid`, `PluginDependency`, `SessionStorageService`, `DeleteUtterancesCommandInput`, `XFilter`, `DeauthenticationResult`, `DiagnosticSeverityOverridesMap`, `TextStyleDefinition`, `VNodeStyle`, `MarketsAccount`, `TrackType`, `CreateAddLinkOptions`, `AsyncAction`, `IHand`, `KeyRingSelectablesStore`, `GX.Attr`, `FunctionAppRuntimeSettings`, `GetResultType`, `ts.ScriptKind`, `BlockContext`, `Disk`, `TETemplate`, `NetworkStatusEvent`, `SystemManager`, `Subscribers`, `tEthereumAddress`, `StackReference`, `SchemeObjectsByLayers`, `ParsedIniData`, `Padawan`, `TiledProperty`, `BindingOrAssignmentPattern`, `InstanceOptions`, `ClientRegistry`, `MachineContext`, `ListenerEntry`, `Typed`, `PurchaseOfferingCommandInput`, `StoredChannel`, `MosString128`, `SBDraft2CommandInputParameterModel`, `RoleTuple`, `InstantiatedContractTreeItem`, `AutocompleteRenderInputParams`, `LineTypes.MessageOptions`, `GoogleAppsScript.Spreadsheet.Sheet`, `ILoadbalance`, `GraphQLClient`, `OutPacketBase`, `TransformOutput`, `DataRepository`, `React.FocusEventHandler`, `LineStyle`, `FaunaNumber`, `JSystemFileReaderHelper`, `ApplicationStatus`, `CreateInputCommandInput`, `RecordedDisplayData`, `MROpts`, `IPointCloudTreeNode`, `TocService`, `ZonesManagerProps`, `StateStorageEngine`, `SackChunk`, `ResourceLocation`, `RouteEntry`, `Resizable`, `Stacks`, `SagaGeneratorWithReturn`, `Expand`, `UpdateOneOptions`, `_this`, `ScreenConfigWithParent`, `NodeWithPosition`, `ToJsonOutput`, `ICalendarEvent`, `FooId`, `IPos`, `TcpPacket`, `KeyAction`, `React.PointerEvent`, `TheiaURI`, `SelectorSpec`, `requests.ListRecommendationsRequest`, `LessOptions`, `ScreenDto`, `MetaState`, `NoteType`, `Transfer`, `ModelSchema`, `ClassInterpreter`, `UnaryExpression`, `XYZAnyValues`, `GenericRetryStrategyOptions`, `STPSetupIntent`, `FakeImporter`, `Monorepo`, `DragDropData`, `Protocol.Network.ResponseReceivedExtraInfoEvent`, `ChapterRow`, `SendRequestConfig`, `Types.RawMessage`, `_N`, `MemDown`, `RegistryRuleType`, `Comma`, `VersionCheckTTL`, `LitCallback`, `IamStatement`, `HtmlElementNode`, `IAuthHeader`, `SubEntityType`, `S3DestinationConfiguration`, `DisplayPartsSymbolWriter`, `VariableDeclaration`, `ServiceConfiguration`, `RenderSprite`, `CheckPrivileges`, `BeaconProxy`, `SyntheticEvent`, `NotificationConfiguration`, `TinyPgParams`, `Key4`, `QuerySort`, `SyncedBackupModel`, `IRGBColor`, `Spectator`, `RangeImpl`, `Cobranca`, `Fiddle`, `Effects`, `Config.ProjectConfig`, `ApproxResult`, `DescribeDatasetResponse`, `W`, `PointCloudOctreeGeometry`, `XmlTimestampsCommandInput`, `_ChildType`, `EditCategoryDto`, `NetworkModel`, `KibanaFeature`, `HasuraModuleConfig`, `IndexPatternsService`, `TestVisitor`, `Controlled`, `TagState`, `IOperation`, `Kind`, `PingProbeProtocol`, `SentryCli`, `ProjectConfigChangedEvent`, `AbstractSyntaxTree`, `Prisma`, `RoutingState`, `AutocompleteContext`, `BlockDoc`, `ISimpleConfigFile`, `SqlBuilder`, `album`, `IDashboard`, `KeyValuePair`, `ChildAppFinalConfig`, `SearchCommandInput`, `SearchSessionsMgmtAPI`, `IChangelog`, `Codeblock`, `DBTProjectContainer`, `TimeSheetService`, `PropertyPair`, `ISpawnOptions`, `Calculator`, `FormatTimeInWordsPipe`, `ConditionalExpression`, `AxesProps`, `IMatcher`, `QueryBinder`, `GameContent`, `CollateralizerContract`, `M.Middleware`, `Images.Dimensions`, `OpenGraph`, `LiveList`, `RealtimeController`, `EventAdapter`, `YAMLDocument`, `TemplateLiteral`, `ControlService`, `Firebase`, `CustomFormGroup`, `IEdgeAD`, `ContextErrorMessageProps`, `EventContext`, `ScriptingDefinitionStub`, `DMMF.Document`, `References`, `GestureDelegate`, `DebugProtocol.ContinueArguments`, `NDframe`, `Evaluated`, `IWarehouse`, `SafetyNetConfig`, `IMeasurementEvent`, `SystemUserApi`, `DAL.KEY_W`, `ParamType`, `DAL.DEVICE_ID_TOUCH_SENSOR`, `EntityData`, `AudioParam`, `IEncoderModel`, `IHSL`, `ParseIconsOpts`, `StorageTier`, `TypeScriptEmbeddedSource`, `OutputSchemaField`, `DebugProtocol.SetBreakpointsResponse`, `JumpyWidget`, `JSONRPC`, `Self`, `WebSocketLink`, `AlternateSymbolNameMap`, `Route53`, `GherkinType`, `NetworkLoadBalancer`, `GenericCompressor`, `JsonDocsUsage`, `ArenaNodeInline`, `estypes.MgetResponseItem`, `RunSpec`, `PortfolioOverviewView`, `DriveItem`, `VirtualNetworkPeering`, `IRequestHandler`, `ColumnSeries`, `StopPipelineExecutionCommandInput`, `SimNode`, `HalfBond`, `StartServicesAccessor`, `TReferences`, `ParsedPath`, `PickerColumn`, `UploadRequest`, `SimpleChoiceGameState`, `ConfigurationParams`, `Address4`, `Swagger2Schema`, `DomainsListOptionalParams`, `DokiSticker`, `ReducerHandler`, `SyncValue`, `CallEndReason`, `TokenFetcher`, `DescribeClustersCommandInput`, `MetaService`, `core.LifecycleSettings`, `UICommand`, `PedersenParams`, `CreateThemeCommandInput`, `TypeCache`, `ValidateFilterKueryNode`, `TransactionsResponse`, `QueryContext`, `SidebarTitleProps`, `RippleGlobalOptions`, `HasUniqueIdentifier`, `IEcsServerGroupCommandResult`, `AppFileStatus`, `IImport`, `ts.TryStatement`, `PrimedCase`, `DejaTreeListComponent`, `Selected`, `Geom`, `MemoryStore`, `ComponentCompilerMethod`, `OasSchema`, `SnakePlayer`, `AsyncOptions`, `AreaState`, `EnforceNonEmptyRecord`, `ResumeData`, `MOscPulse`, `VillainService`, `InstallOptions`, `UserInfoStore`, `LineColPos`, `PointSeries`, `Framebuffer2D`, `SearchEmbeddableFactory`, `SetupObjects`, `View.Mail`, `SVGImageElement`, `IconifyIconName`, `TVector`, `FunctionDef`, `JsonSourceFile`, `RemoteParticipantState`, `IResolveWebpackConfigOptions`, `WebRtcTransport`, `FeatureCollection`, `GeneratedReport`, `TypeTarget`, `UIPageViewController`, `DataTypesInput`, `Electron.Menu`, `SpaceMembershipProps`, `TDDraw`, `TotemFile`, `NodeTypeMetricCapacity`, `MThumbnail`, `PlanetComponentRef`, `HttpResponseOptions`, `VariableDeclarationContext`, `android.webkit.WebView`, `NoShrinkArray`, `ContainerClient`, `InitialValues`, `Iterator`, `RouteLocationNormalizedLoaded`, `MapBrowserEvent`, `ICredentials`, `IStaticWebAppWizardContext`, `CrochetActivation`, `d.CompilerEventName`, `TestDataObject`, `Handles`, `RotationManager`, `IndexKey`, `AclEntry`, `SpecDefinitionsService`, `AuthPluginPackage`, `DockerOptions`, `Keybinding`, `P10`, `QueryBodyType`, `PoolClientState`, `Fr`, `ToolsService`, `TsAutocompleteComponent`, `ContinuousDomainFocus`, `UploadTaskSnapshot`, `GitError`, `BuildParams`, `StringWriter`, `ISafeFont`, `AMap.Map`, `ColorMap`, `DfsResult`, `ParsedLock`, `AccountPagination`, `angu.Value`, `DragulaService`, `IKEffector`, `ClusterExplorerNode`, `SchemaFactory`, `TerraformVars`, `ProgramState`, `CollaboratorService`, `ICredentialDataDecryptedObject`, `PanelConfigProps`, `OrgDataSource`, `Matrix33`, `ImplicationProofItem`, `Edge`, `FieldsTree`, `TextDecoder`, `UrlSerializer`, `IDinoRequestEndProps`, `TextAreaProps`, `OpenSearchDashboardsDatatableColumnMeta`, `HdBitcoinCashPayments`, `ICanvasRenderingContext`, `knex`, `DataProvider`, `StringScannerOutput`, `CallbackResult`, `vscode.TextDocumentChangeEvent`, `ScriptVM`, `ValueScopeName`, `NamedBinding`, `IOdspTokens`, `Template`, `EVENT`, `ResolvedConceptAtomTypeEntry`, `IExtensionPlugin`, `FileUploader`, `LoopBackAuth`, `SharedModel`, `NamedVariableMap`, `XTermColorTheme`, `HumidityControlSetpointType`, `ApiAdapter`, `ConfigManager`, `TLinkCallback`, `RenderOption`, `PagedAsyncIterableIterator`, `PaginatedTiles`, `PublicVocabulary`, `Projection`, `DayPlannerSettings`, `StacksMessageType`, `DefaultChangeAnalyzer`, `GroupsService`, `NamedFragments`, `Divider`, `SocialTokenV0`, `requests.ListResourceTypesRequest`, `Models.AccessTier`, `ExtensionContext`, `ObjectSchema`, `SonarQubeApiScm`, `BUNDLE_TYPE`, `commandInterface`, `GridEntry`, `Datetime`, `QListWidgetItem`, `EncryptedWalletsStore`, `DirectiveDef`, `TMenuOption`, `AutoScalingPolicy`, `Witness`, `DebugStateLegend`, `WalkContext`, `AuthenticationState`, `VariableType`, `IQuestionToolboxItem`, `GraphRequest`, `PopupPositionConfig`, `ExtendedOptions`, `Interpret`, `EnqueuedTask`, `ChatAdapter`, `ts.NamedDeclaration`, `Percussion`, `SortEnd`, `MetadataKey`, `IEntityOptions`, `SyncModule`, `SortOrderType`, `FakeSurveyDialog`, `CreateApplicationVersionCommandInput`, `ConnectionGroup`, `DeleteBucketCommandInput`, `CspConfigType`, `EvolvingArrayType`, `ApiResultCallback`, `backend_util.Conv3DInfo`, `ThySlideContainerComponent`, `PublishCommandInput`, `IssueType`, `requests.ListVmClusterNetworksRequest`, `yubo.MessageService`, `FilePathKey`, `ServiceState`, `P2PRequest`, `DescribeClustersResponse`, `TCountData`, `LiteralNode`, `FileOpItem`, `V1Scale`, `DataOptions`, `ChangeTracker`, `ChartOptions`, `PlaylistWithLoadingState`, `EnumValue`, `ModalRef`, `AppNode`, `SuiTabHeader`, `OnceTask`, `NEOONEDataProvider`, `OrderStatusState`, `SelectItemValue`, `SafeString`, `TestChangesetSequence`, `ServerObject`, `OPaths`, `Ganache`, `estypes.QueryDslQueryContainer`, `BBOX`, `AndExpression`, `SiteConfigResource`, `UICollectionView`, `ExceptionListClient`, `AllDestinations`, `App.ui.INotifications`, `EvaluateMid`, `SendData`, `Discord.Client`, `CryptoProvider`, `CodeSpec`, `GossipError`, `GeneralCallbackResult`, `TickPositionsArray`, `SettingsV11`, `AstRoot`, `LonLatArray`, `GetConfigFn`, `RecipientElement`, `ThingsPage`, `RenderParams`, `IgnoreDiagnosticResult`, `Package.Package`, `requests.ListInstanceAgentCommandsRequest`, `EmojiParseOptions`, `ControllerOptions`, `DomainInfo`, `ParameterReflection`, `ClientIdentity`, `LURLGroup`, `ProjectType`, `FormattedEntry`, `IProductTranslatable`, `WaveShaper`, `UserEntity`, `Specifier`, `BBoxObject`, `MeshBasicMaterial`, `PluginOption`, `SummaryObject`, `ILoginState`, `ISubscriptionContext`, `TConfig`, `ICellMarker`, `MiLayerData`, `nodes.RuleSet`, `GeneralSettings`, `androidx.fragment.app.Fragment`, `PrettierConfig`, `ServiceName`, `RootType`, `ArmSaveConfigs`, `ts.FunctionDeclaration`, `OnTabSelectedlistener`, `AnyChildren`, `MatchFilter`, `V1Job`, `planner.Planner`, `MessageReadListener`, `TimestampInMillis`, `IExportMapMetadata`, `ComponentEvent`, `IMergeBlock`, `BookData`, `ListingData`, `AppwriteProjectConfiguration`, `ExpressConnection`, `InputLayerArgs`, `ProductVariantPriceService`, `MessageListener`, `HardRedirectService`, `AfterGenesisBlockApplyContext`, `LuaParse`, `ArrayBuilderSegment`, `BlitzPage`, `PathConfigMap`, `Concourse`, `NitroState`, `WaveProperties`, `ListHealthChecksVantagePointsRequest`, `ShapeStyle`, `InjectContext`, `tfl.SymbolicTensor`, `MappingObject`, `RouteName`, `Restriction`, `DescribeEngineDefaultClusterParametersCommandInput`, `SagaReturnType`, `DoubleLinkedListNode`, `TypedArray`, `commonmark.Node`, `HttpConnection`, `SpineAnimation`, `TraverseCallbackType`, `Shape2DSW`, `VConsoleNetworkRequestItem`, `TypeDictionaryInfo`, `ReferencingColumnBuilder`, `DAVAccount`, `AnnotationOptions`, `SummaryData`, `GroupByPipe`, `GetWebhookParams`, `Contactable`, `KdNode`, `SubmissionCcLicence`, `OnboardingPage`, `ISignalMessage`, `AnnotationLevel`, `Recipient`, `SpyData`, `Buffers`, `CanvasGraphic`, `TensorInfo`, `ToneOscillatorNode`, `LinkData`, `paper.Path`, `PLSQLCompletionDefinition`, `ModuleOptionsWithValidateFalse`, `DeregisterInstanceCommandInput`, `MdcSnackbarRef`, `NetworkDiagnosticChangedEventArgs`, `TRequestWithUser`, `PullFromStorageInfo`, `Cumulative`, `ItemRenderer`, `SyntheticPerformanceBudget`, `LuxonDateTime`, `IMatchWarriorResult`, `Bone`, `ComponentConfig`, `AxisEdge`, `MigrationData`, `Real`, `TokenCategory`, `TmdbTvResult`, `ReactQueryMethodMap`, `RootToken`, `ComponentController`, `EAdvancedSortMethod`, `DeviceManifest`, `apid.ReserveSaveOption`, `UpdateProjectRequest`, `DeviceProps`, `OcsHttpError`, `SecurityQuestionStore`, `DescriptorValue`, `JoinPoint`, `NzUploadFile`, `ScanPaginator`, `ScriptStub`, `MacroTask`, `Token.Token`, `React.VFC`, `BotResponseService`, `ThemeData`, `ILoggerColorParams`, `NoArgListener`, `EnvPaths`, `BundleResult`, `DMMF.Model`, `CastNode`, `RequestBodyParser`, `SwimLane`, `RTCPFB`, `CoinMap`, `TypescriptMember`, `FullConfiguration`, `RuleWithFlags`, `UIEvent`, `Exec`, `DailyRotateFile`, `ForeignKeyModelInterface`, `SenseEditor`, `IndexProperty`, `IExecOptions`, `IndividualChange`, `SagaConfig`, `DomainEntry`, `Transcoder`, `RarityLevel`, `PermissionData`, `ConstructorOrField`, `PlaceholderContent`, `TEmitted`, `KeyLike`, `JSXNode`, `SimpleRange`, `StringDict`, `ExternalAuthenticateModel`, `Fence`, `SortDirectionNumeric`, `RegisteredServiceAttributeReleasePolicy`, `ConfirmDialog`, `PlanningResult`, `ContentLocation`, `ImmutableSelectorNode`, `FeatherProps`, `DocInfo`, `GXMaterialBuilder`, `eventWithTime`, `TableNode`, `FbFormPermission`, `ChartType`, `CacheQueryOptions`, `EvaluationStats`, `DiffError`, `ClippingPlane`, `OrderByItemNode`, `id`, `DeleteTagsCommandInput`, `ClassTypeFlags`, `AsyncGenerator`, `PersianDate`, `ClientId`, `Proto.FileLocationRequestArgs`, `Config.IConfig`, `SearchCallback`, `Draft.EditorState`, `RejectOnNotFound`, `RemoteEngine`, `BinarySensorCCReport`, `SharedStreetsReference`, `UrlGeneratorInternal`, `HTTPRequest`, `FullType`, `StatsCollector`, `TimeRange`, `TouchEventHandler`, `_.Iso`, `EnvsRaw`, `TaskInput`, `SupportedExchange`, `AttentionLevel`, `PointSet`, `ParseField`, `ResourceHash`, `TransmartNegationConstraint`, `Player`, `LocalGatewayTreeItem`, `GamepadEvent`, `UsersEntity`, `RowRenderTreeType`, `EndpointOperationCommandInput`, `SetTree`, `Labels`, `ITriggerEvent`, `SystemMessageProps`, `ListParams`, `Localization`, `TreemapPoint`, `SendEmailJsonDto`, `ReadonlySet`, `NodeDetails`, `FileAvailability`, `ParsingState`, `esbuild.BuildOptions`, `StyledLabelProps`, `Model1`, `ImageMatrix`, `xyTYpe`, `StyleScope`, `JSDocTypedefTag`, `TranslationBundle`, `UpdateDatabaseResponse`, `STPCardBrand`, `StudentFeedback`, `d.CompilerRequestResponse`, `TrackModel`, `CountableExpectation`, `PlayerProps`, `PathVal`, `BuffData`, `Lab`, `ListPartsCommandInput`, `IJetURL`, `TransactionReceiptsEventInfo`, `HSD_Archive`, `PickingCollisionVO`, `SignatureResult`, `Fn0`, `OpenYoloWithTimeoutApi`, `HttpTestingController`, `ServerEngine`, `IValidationResult`, `roleMenuInterface`, `DebugSessionCustomEvent`, `WrapperArray`, `MDCTextFieldInputAdapter`, `Hull`, `EmbedOptions`, `requests.ListExternalContainerDatabasesRequest`, `TransactionOpts`, `MimeParserNode`, `SiteData`, `DocumentUnderstandingServiceClient`, `Filename`, `AbiRange`, `ReduxActionWithPayload`, `MDCListAdapter`, `IWizard`, `FormHook`, `Event_PropertiesEntry`, `DiagramState`, `SegmentedBarItem`, `DashboardSavedObject`, `GLclampf`, `ITextProps`, `ITx`, `AuthenticationVirtualMachine`, `LogicalWhereExpr`, `guildDoc`, `StyleSetEvaluator`, `NSError`, `SpritesStateRecord`, `DefaultGuiState`, `ChangedElementsDb`, `YamlNode`, `MetamaskPolkadotSnap`, `PositionConfig`, `Tester`, `FileSystemProvider`, `UnitsProvider`, `IContextualMenuItemStyles`, `AVRPortConfig`, `DescribeDomainCommandInput`, `ResultList`, `OpenAPI.PathItem`, `AutomationHelper`, `TypeChecker`, `AuthFacade`, `IPageChangeEvent`, `ReadableStreamReader`, `InputSearchExpressionGroup`, `HandlerInfo`, `CeloTxObject`, `RelationshipService`, `IAutocompleteSelectCellEditorParameters`, `ActionQueue`, `MigrateDeploy`, `cc.Event.EventTouch`, `ConstructorParameters`, `NodeContentTree`, `HelpObj`, `ElementWrapper`, `TxOut`, `DubboTcpTransport`, `SpriteComponent`, `TestExecutionContext`, `MutationContext`, `DeployArgs`, `TabularData`, `CspDirectives`, `ExpressionValueError`, `LabelProps`, `UserMetadatumModel`, `MeasureUnitType`, `SegNode`, `EntityStateRecord`, `DatamodelEnum`, `ContentWidget`, `ResourceData`, `WhereClauseContext`, `Optimizer2`, `BatchCertificateTransfer`, `NgPackagrBuilderOptions`, `EncodedManagedModel`, `SQLStatement`, `LiveAtlasPlayer`, `BasicAction`, `XmlSchema`, `Spec`, `Translation`, `GPUProgram`, `SafeBlock`, `InternalStore`, `SimulationInfo`, `PrefixUnaryOperator`, `BrushScope`, `JavaRecord`, `SelectedCriteriaType`, `ResolveSubscriptionFn`, `SpawnFlags`, `ClassWeight`, `AudioVideoFacade`, `PSTDescriptorItem`, `RelayerRequest`, `TileLoader`, `ListClustersRequest`, `InitialStylingValues`, `ResourceLoader`, `CmsStorageEntry`, `GleeMessage`, `Slate`, `sdk.PushAudioInputStream`, `ProcessingContext`, `ESLintProgram`, `SlideLayout`, `GridView`, `LogRecord`, `RTCDataChannelParameters`, `ICSSInJSStyle`, `d.FsWriteResults`, `Ports`, `RemoteConsole`, `LineAndCharacter`, `DiagnosticRelatedInformation`, `StepperContext`, `AlertDescriptionProps`, `OrganizationalUnitPath`, `ThemeResolver`, `CSSBlocksJSXAnalyzer`, `IOperator`, `ElementEntity`, `Refresher`, `CurrentState`, `DependOnFileCondition`, `GetSuccess`, `CopyAuthOptions`, `IMessageListenerWrapper`, `WebdriverIOConfig`, `ExpressionAstNode`, `GeneralOptions`, `RectGraphicsOptions`, `UpdateProfileParams`, `TimeValues`, `HeaderData`, `IPackageInfo`, `PathAndExtension`, `UseMediaState`, `FieldDescription`, `MalNode`, `BroadcastChannel`, `Word`, `DeploymentHandler`, `TreemapSeriesType`, `IUtilityStoreState`, `TsInputComponent`, `PortModel`, `AnnotationVisitor`, `IFilterListRow`, `github.GitHub`, `SimpleTextSymbol`, `android.os.Parcelable`, `Attribute`, `FileShare`, `WalletLinkRelayAbstract`, `IHillResult`, `SchedulerLike`, `OnPreRoutingToolkit`, `DocumentationContext`, `TransferMode`, `MonitoringData`, `AuthClientRepository`, `RequestOpts`, `RemoveTagsFromResourceCommand`, `SetCombinationType`, `PaletteOutput`, `TypePoint`, `FormSubmissionErrors`, `ICellx`, `Events.activate`, `CSharpClass`, `UpdateBillingParams`, `freedom.RTCPeerConnection.RTCConfiguration`, `AuthCode`, `IConvertContext`, `SVGTextElement`, `PipeConnection`, `PaymentParams`, `AstNodeContent`, `PhotoSize`, `BindingFilter`, `L.LatLng`, `EnhancedReducerResult`, `FeederDetails`, `ISourceFileReference`, `ExportSpecifier`, `BlogPost`, `CountStatisticSummary`, `SeasonRequest`, `IBinding`, `TagTree`, `ParameterValueList`, `LanguageState`, `ActionReturn`, `ExtendedPostFrontMatter`, `ResetPasswordInput`, `CmsModelPlugin`, `Publication`, `ApolloLink`, `MockAttr`, `GPUBufferUsageFlags`, `NotificationIOS`, `files.Location`, `RequestUploadService`, `RoleMapping`, `AcceptableType`, `ResolutionKindSpecificLoader`, `DokiThemeConfig`, `PerModuleNameCache`, `SnapshotListParams`, `IListInfo`, `BackblazeB2Bucket`, `PackageManifest`, `types.Output`, `ThreadConnection`, `WindowsManager`, `theia.WorkspaceFolder`, `InlinableCode`, `IMOSStoryAction`, `Framework`, `ThyOverlayTrigger`, `PlanItem`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_codeberta_MT4TS_en_5.5.0_3.0_1725311282884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_codeberta_MT4TS_en_5.5.0_3.0_1725311282884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("roberta_ner_codeberta_MT4TS","en") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("roberta_ner_codeberta_MT4TS","en") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_codeberta_MT4TS|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|452.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/kevinjesse/codeberta-MT4TS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_codeberta_MT4TS_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_codeberta_MT4TS_pipeline_en.md
new file mode 100644
index 00000000000000..9e16a2fea74190
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_codeberta_MT4TS_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_ner_codeberta_MT4TS_pipeline pipeline RoBertaForTokenClassification from kevinjesse
+author: John Snow Labs
+name: roberta_ner_codeberta_MT4TS_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_codeberta_MT4TS_pipeline` is a English model originally trained by kevinjesse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_codeberta_MT4TS_pipeline_en_5.5.0_3.0_1725311306267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_codeberta_MT4TS_pipeline_en_5.5.0_3.0_1725311306267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_ner_codeberta_MT4TS_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_ner_codeberta_MT4TS_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_codeberta_MT4TS_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|452.3 MB|
+
+## References
+
+https://huggingface.co/kevinjesse/codeberta-MT4TS
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_graphpolygot_MT4TS_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_graphpolygot_MT4TS_pipeline_en.md
new file mode 100644
index 00000000000000..5391a5d41b379a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_graphpolygot_MT4TS_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_ner_graphpolygot_MT4TS_pipeline pipeline RoBertaForTokenClassification from kevinjesse
+author: John Snow Labs
+name: roberta_ner_graphpolygot_MT4TS_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_graphpolygot_MT4TS_pipeline` is a English model originally trained by kevinjesse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_graphpolygot_MT4TS_pipeline_en_5.5.0_3.0_1725312029324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_graphpolygot_MT4TS_pipeline_en_5.5.0_3.0_1725312029324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_ner_graphpolygot_MT4TS_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_ner_graphpolygot_MT4TS_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_graphpolygot_MT4TS_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|607.7 MB|
+
+## References
+
+https://huggingface.co/kevinjesse/graphpolygot-MT4TS
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_xx.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_xx.md
new file mode 100644
index 00000000000000..b8dd8ba3c32e21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english RoBertaForTokenClassification from StivenLancheros
+author: John Snow Labs
+name: roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english
+date: 2024-09-02
+tags: [xx, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english` is a Multilingual model originally trained by StivenLancheros.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_xx_5.5.0_3.0_1725311053935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english_xx_5.5.0_3.0_1725311053935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|438.8 MB|
+
+## References
+
+https://huggingface.co/StivenLancheros/roberta-base-biomedical-clinical-es-finetuned-ner-CRAFT_AugmentedTransfer_EN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_visquad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_visquad_pipeline_en.md
new file mode 100644
index 00000000000000..b3f30e2da74fda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_base_squad2_finetuned_visquad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_base_squad2_finetuned_visquad_pipeline pipeline RoBertaForQuestionAnswering from khoanvm
+author: John Snow Labs
+name: roberta_qa_base_squad2_finetuned_visquad_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_squad2_finetuned_visquad_pipeline` is a English model originally trained by khoanvm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_finetuned_visquad_pipeline_en_5.5.0_3.0_1725251956401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_finetuned_visquad_pipeline_en_5.5.0_3.0_1725251956401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_base_squad2_finetuned_visquad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_base_squad2_finetuned_visquad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_base_squad2_finetuned_visquad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/khoanvm/roberta-base-squad2-finetuned-visquad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..f64b7dfe95400c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from miamiya
+author: John Snow Labs
+name: roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline` is a English model originally trained by miamiya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline_en_5.5.0_3.0_1725251728196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline_en_5.5.0_3.0_1725251728196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_miamiya_base_squad2_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+https://huggingface.co/miamiya/roberta-base-squad2-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_movie_roberta_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_movie_roberta_squad_pipeline_en.md
new file mode 100644
index 00000000000000..f0c44d696e832c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_movie_roberta_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_movie_roberta_squad_pipeline pipeline RoBertaForQuestionAnswering from thatdramebaazguy
+author: John Snow Labs
+name: roberta_qa_movie_roberta_squad_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_movie_roberta_squad_pipeline` is a English model originally trained by thatdramebaazguy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_movie_roberta_squad_pipeline_en_5.5.0_3.0_1725251706092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_movie_roberta_squad_pipeline_en_5.5.0_3.0_1725251706092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_movie_roberta_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_movie_roberta_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_movie_roberta_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/thatdramebaazguy/movie-roberta-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_FT_newsqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_FT_newsqa_pipeline_en.md
new file mode 100644
index 00000000000000..452aa9ba71a412
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_FT_newsqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_FT_newsqa_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_roberta_FT_newsqa_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_FT_newsqa_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_FT_newsqa_pipeline_en_5.5.0_3.0_1725252539260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_FT_newsqa_pipeline_en_5.5.0_3.0_1725252539260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_FT_newsqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_FT_newsqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_FT_newsqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|457.8 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/roberta_FT_newsqa
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline_en.md
new file mode 100644
index 00000000000000..c7b57000a73ee4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline_en_5.5.0_3.0_1725252307794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline_en_5.5.0_3.0_1725252307794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|424.3 MB|
+
+## References
+
+https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-16-finetuned-squad-seed-42
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-securebert_our_data_en.md b/docs/_posts/ahmedlone127/2024-09-02-securebert_our_data_en.md
new file mode 100644
index 00000000000000..3d03fee7023292
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-securebert_our_data_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English securebert_our_data RoBertaForTokenClassification from anonymouspd
+author: John Snow Labs
+name: securebert_our_data
+date: 2024-09-02
+tags: [roberta, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_our_data` is a English model originally trained by anonymouspd.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_our_data_en_5.5.0_3.0_1725311270283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_our_data_en_5.5.0_3.0_1725311270283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+    
+tokenizer = Tokenizer() \
+        .setInputCols(["document"]) \
+        .setOutputCol("token")
+        
+    
+tokenClassifier = RoBertaForTokenClassification.pretrained("securebert_our_data","en") \
+            .setInputCols(["document","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val tokenizer = Tokenizer() \
+        .setInputCols(Array("document")) \
+        .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification  
+    .pretrained("securebert_our_data", "en")
+    .setInputCols(Array("document","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|securebert_our_data|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/anonymouspd/SecureBERT-our-data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-securebert_our_data_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-securebert_our_data_pipeline_en.md
new file mode 100644
index 00000000000000..6b527045bd1812
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-securebert_our_data_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English securebert_our_data_pipeline pipeline RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: securebert_our_data_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_our_data_pipeline` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_our_data_pipeline_en_5.5.0_3.0_1725311293289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_our_data_pipeline_en_5.5.0_3.0_1725311293289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("securebert_our_data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("securebert_our_data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|securebert_our_data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/SecureBERT-our-data
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_arabertv02_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_arabertv02_pipeline_ar.md
new file mode 100644
index 00000000000000..c8f9be0efc891b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_large_arabertv02_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_bert_large_arabertv02_pipeline pipeline BertSentenceEmbeddings from aubmindlab
+author: John Snow Labs
+name: sent_bert_large_arabertv02_pipeline
+date: 2024-09-02
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_arabertv02_pipeline` is a Arabic model originally trained by aubmindlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv02_pipeline_ar_5.5.0_3.0_1725274313232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv02_pipeline_ar_5.5.0_3.0_1725274313232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_large_arabertv02_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_large_arabertv02_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_arabertv02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/aubmindlab/bert-large-arabertv02
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_bert_review_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_review_en.md
new file mode 100644
index 00000000000000..9ace2e4e19ebf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_bert_review_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_review BertSentenceEmbeddings from activebus
+author: John Snow Labs
+name: sent_bert_review
+date: 2024-09-02
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_review` is a English model originally trained by activebus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_review_en_5.5.0_3.0_1725273854168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_review_en_5.5.0_3.0_1725273854168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_review","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_review","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_review|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|258.5 MB|
+
+## References
+
+https://huggingface.co/activebus/BERT_Review
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_biomednlp_biomedbert_base_uncased_abstract_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_biomednlp_biomedbert_base_uncased_abstract_en.md
new file mode 100644
index 00000000000000..9f8959be256d0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_biomednlp_biomedbert_base_uncased_abstract_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_biomednlp_biomedbert_base_uncased_abstract BertSentenceEmbeddings from microsoft
+author: John Snow Labs
+name: sent_biomednlp_biomedbert_base_uncased_abstract
+date: 2024-09-02
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biomednlp_biomedbert_base_uncased_abstract` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biomednlp_biomedbert_base_uncased_abstract_en_5.5.0_3.0_1725274481880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biomednlp_biomedbert_base_uncased_abstract_en_5.5.0_3.0_1725274481880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_biomednlp_biomedbert_base_uncased_abstract","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_biomednlp_biomedbert_base_uncased_abstract","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biomednlp_biomedbert_base_uncased_abstract|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_custom_legalbert_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_custom_legalbert_en.md
new file mode 100644
index 00000000000000..376d2f1ed8958e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_custom_legalbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_custom_legalbert BertSentenceEmbeddings from casehold
+author: John Snow Labs
+name: sent_custom_legalbert
+date: 2024-09-02
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_custom_legalbert` is a English model originally trained by casehold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_custom_legalbert_en_5.5.0_3.0_1725273267578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_custom_legalbert_en_5.5.0_3.0_1725273267578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_custom_legalbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_custom_legalbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_custom_legalbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|411.6 MB|
+
+## References
+
+https://huggingface.co/casehold/custom-legalbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_custom_legalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_custom_legalbert_pipeline_en.md
new file mode 100644
index 00000000000000..2ce785dc609652
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_custom_legalbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_custom_legalbert_pipeline pipeline BertSentenceEmbeddings from casehold
+author: John Snow Labs
+name: sent_custom_legalbert_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_custom_legalbert_pipeline` is a English model originally trained by casehold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_custom_legalbert_pipeline_en_5.5.0_3.0_1725273295373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_custom_legalbert_pipeline_en_5.5.0_3.0_1725273295373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_custom_legalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_custom_legalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_custom_legalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.2 MB|
+
+## References
+
+https://huggingface.co/casehold/custom-legalbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_gysbert_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_gysbert_v2_en.md
new file mode 100644
index 00000000000000..38437b6b7e2ba9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_gysbert_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_gysbert_v2 BertSentenceEmbeddings from emanjavacas
+author: John Snow Labs
+name: sent_gysbert_v2
+date: 2024-09-02
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gysbert_v2` is a English model originally trained by emanjavacas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gysbert_v2_en_5.5.0_3.0_1725273408395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gysbert_v2_en_5.5.0_3.0_1725273408395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_gysbert_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_gysbert_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gysbert_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/emanjavacas/GysBERT-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_gysbert_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_gysbert_v2_pipeline_en.md
new file mode 100644
index 00000000000000..f4f6736e612c8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_gysbert_v2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_gysbert_v2_pipeline pipeline BertSentenceEmbeddings from emanjavacas
+author: John Snow Labs
+name: sent_gysbert_v2_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gysbert_v2_pipeline` is a English model originally trained by emanjavacas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gysbert_v2_pipeline_en_5.5.0_3.0_1725273430251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gysbert_v2_pipeline_en_5.5.0_3.0_1725273430251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_gysbert_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_gysbert_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gysbert_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.6 MB|
+
+## References
+
+https://huggingface.co/emanjavacas/GysBERT-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_sikuroberta_zh.md b/docs/_posts/ahmedlone127/2024-09-02-sent_sikuroberta_zh.md
new file mode 100644
index 00000000000000..1dbc1f9dcf40a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_sikuroberta_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese sent_sikuroberta BertSentenceEmbeddings from SIKU-BERT
+author: John Snow Labs
+name: sent_sikuroberta
+date: 2024-09-02
+tags: [zh, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_sikuroberta` is a Chinese model originally trained by SIKU-BERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_sikuroberta_zh_5.5.0_3.0_1725274356908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_sikuroberta_zh_5.5.0_3.0_1725274356908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_sikuroberta","zh") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_sikuroberta","zh") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_sikuroberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|zh|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/SIKU-BERT/sikuroberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_splade_cocondenser_ensembledistil_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_splade_cocondenser_ensembledistil_en.md
new file mode 100644
index 00000000000000..8e82fbc37d144d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_splade_cocondenser_ensembledistil_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_splade_cocondenser_ensembledistil BertSentenceEmbeddings from naver
+author: John Snow Labs
+name: sent_splade_cocondenser_ensembledistil
+date: 2024-09-02
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_splade_cocondenser_ensembledistil` is a English model originally trained by naver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_splade_cocondenser_ensembledistil_en_5.5.0_3.0_1725273576136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_splade_cocondenser_ensembledistil_en_5.5.0_3.0_1725273576136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_splade_cocondenser_ensembledistil","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_splade_cocondenser_ensembledistil","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_splade_cocondenser_ensembledistil|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/naver/splade-cocondenser-ensembledistil
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sentence_transformers_e5_large_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-sentence_transformers_e5_large_v2_pipeline_en.md
new file mode 100644
index 00000000000000..1e36c12419d8a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sentence_transformers_e5_large_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sentence_transformers_e5_large_v2_pipeline pipeline E5Embeddings from embaas
+author: John Snow Labs
+name: sentence_transformers_e5_large_v2_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_e5_large_v2_pipeline` is a English model originally trained by embaas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_e5_large_v2_pipeline_en_5.5.0_3.0_1725260535990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_e5_large_v2_pipeline_en_5.5.0_3.0_1725260535990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentence_transformers_e5_large_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentence_transformers_e5_large_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentence_transformers_e5_large_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.2 MB|
+
+## References
+
+https://huggingface.co/embaas/sentence-transformers-e5-large-v2
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-setfit_model_labelfaithful_epochs2_en.md b/docs/_posts/ahmedlone127/2024-09-02-setfit_model_labelfaithful_epochs2_en.md
new file mode 100644
index 00000000000000..fda91fc87af4fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-setfit_model_labelfaithful_epochs2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English setfit_model_labelfaithful_epochs2 MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_labelfaithful_epochs2
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_labelfaithful_epochs2` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_labelfaithful_epochs2_en_5.5.0_3.0_1725280361517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_labelfaithful_epochs2_en_5.5.0_3.0_1725280361517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("setfit_model_labelfaithful_epochs2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("setfit_model_labelfaithful_epochs2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_labelfaithful_epochs2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit_model_labelfaithful_epochs2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_large_stsb200_en.md b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_large_stsb200_en.md
new file mode 100644
index 00000000000000..cca729230c0284
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sitexsometre_camembert_large_stsb200_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sitexsometre_camembert_large_stsb200 CamemBertForSequenceClassification from Kigo1974
+author: John Snow Labs
+name: sitexsometre_camembert_large_stsb200
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_large_stsb200` is a English model originally trained by Kigo1974.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_large_stsb200_en_5.5.0_3.0_1725298612181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_large_stsb200_en_5.5.0_3.0_1725298612181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_large_stsb200","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_large_stsb200", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sitexsometre_camembert_large_stsb200|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|805.5 MB|
+
+## References
+
+https://huggingface.co/Kigo1974/sitexsometre-camembert-large-stsb200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sloberta_pipeline_sl.md b/docs/_posts/ahmedlone127/2024-09-02-sloberta_pipeline_sl.md
new file mode 100644
index 00000000000000..04342f480fd3dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sloberta_pipeline_sl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Slovenian sloberta_pipeline pipeline CamemBertEmbeddings from EMBEDDIA
+author: John Snow Labs
+name: sloberta_pipeline
+date: 2024-09-02
+tags: [sl, open_source, pipeline, onnx]
+task: Embeddings
+language: sl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sloberta_pipeline` is a Slovenian model originally trained by EMBEDDIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sloberta_pipeline_sl_5.5.0_3.0_1725296484117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sloberta_pipeline_sl_5.5.0_3.0_1725296484117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sloberta_pipeline", lang = "sl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sloberta_pipeline", lang = "sl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sloberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sl|
+|Size:|263.5 MB|
+
+## References
+
+https://huggingface.co/EMBEDDIA/sloberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-slovene_law_roberta_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-slovene_law_roberta_5_pipeline_en.md
new file mode 100644
index 00000000000000..4322176137dbdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-slovene_law_roberta_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English slovene_law_roberta_5_pipeline pipeline RoBertaForQuestionAnswering from aseljayasooriya
+author: John Snow Labs
+name: slovene_law_roberta_5_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovene_law_roberta_5_pipeline` is a English model originally trained by aseljayasooriya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovene_law_roberta_5_pipeline_en_5.5.0_3.0_1725252197350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovene_law_roberta_5_pipeline_en_5.5.0_3.0_1725252197350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slovene_law_roberta_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slovene_law_roberta_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slovene_law_roberta_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.7 MB|
+
+## References
+
+https://huggingface.co/aseljayasooriya/sl-law-roberta-5
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_1000_en.md b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_1000_en.md
new file mode 100644
index 00000000000000..14d16fb7a513ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_1000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_arabic_1000 MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_arabic_1000
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_arabic_1000` is a English model originally trained by danfeg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_1000_en_5.5.0_3.0_1725280944445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_1000_en_5.5.0_3.0_1725280944445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_arabic_1000","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_arabic_1000","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_arabic_1000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-AR-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_500_en.md b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_500_en.md
new file mode 100644
index 00000000000000..830a7e21de535f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_500_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_arabic_500 MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_arabic_500
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_arabic_500` is a English model originally trained by danfeg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_500_en_5.5.0_3.0_1725313962665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_500_en_5.5.0_3.0_1725313962665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_arabic_500","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_arabic_500","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_arabic_500|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-AR-500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_500_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_500_pipeline_en.md
new file mode 100644
index 00000000000000..c53c080d07149d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_all_mpnet_finetuned_arabic_500_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_arabic_500_pipeline pipeline MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_arabic_500_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_arabic_500_pipeline` is a English model originally trained by danfeg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_500_pipeline_en_5.5.0_3.0_1725313983912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_500_pipeline_en_5.5.0_3.0_1725313983912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("southern_sotho_all_mpnet_finetuned_arabic_500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("southern_sotho_all_mpnet_finetuned_arabic_500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_arabic_500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-AR-500
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_v3_test_mpnet_base_allnli_stsb_en.md b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_v3_test_mpnet_base_allnli_stsb_en.md
new file mode 100644
index 00000000000000..bb10a11ae650a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-southern_sotho_v3_test_mpnet_base_allnli_stsb_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English southern_sotho_v3_test_mpnet_base_allnli_stsb MPNetEmbeddings from tomaarsen
+author: John Snow Labs
+name: southern_sotho_v3_test_mpnet_base_allnli_stsb
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_v3_test_mpnet_base_allnli_stsb` is a English model originally trained by tomaarsen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_v3_test_mpnet_base_allnli_stsb_en_5.5.0_3.0_1725313670876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_v3_test_mpnet_base_allnli_stsb_en_5.5.0_3.0_1725313670876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("southern_sotho_v3_test_mpnet_base_allnli_stsb","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("southern_sotho_v3_test_mpnet_base_allnli_stsb","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_v3_test_mpnet_base_allnli_stsb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|399.5 MB|
+
+## References
+
+https://huggingface.co/tomaarsen/st-v3-test-mpnet-base-allnli-stsb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-spanberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-spanberta_pipeline_en.md
new file mode 100644
index 00000000000000..5df6ae5d2e423a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-spanberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spanberta_pipeline pipeline RoBertaEmbeddings from chriskhanhtran
+author: John Snow Labs
+name: spanberta_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanberta_pipeline` is a English model originally trained by chriskhanhtran.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanberta_pipeline_en_5.5.0_3.0_1725265211134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanberta_pipeline_en_5.5.0_3.0_1725265211134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("spanberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spanberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spanberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+https://huggingface.co/chriskhanhtran/spanberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-squeezebert_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-02-squeezebert_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..59933a284c8be6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-squeezebert_finetuned_squadv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English squeezebert_finetuned_squadv2 BertForQuestionAnswering from mrm8488
+author: John Snow Labs
+name: squeezebert_finetuned_squadv2
+date: 2024-09-02
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squeezebert_finetuned_squadv2` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squeezebert_finetuned_squadv2_en_5.5.0_3.0_1725312530609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squeezebert_finetuned_squadv2_en_5.5.0_3.0_1725312530609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("squeezebert_finetuned_squadv2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("squeezebert_finetuned_squadv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squeezebert_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|186.4 MB|
+
+## References
+
+https://huggingface.co/mrm8488/squeezebert-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-stress_prediction_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-stress_prediction_pipeline_en.md
new file mode 100644
index 00000000000000..f8197314b1feac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-stress_prediction_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English stress_prediction_pipeline pipeline DistilBertForSequenceClassification from jnyx74
+author: John Snow Labs
+name: stress_prediction_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stress_prediction_pipeline` is a English model originally trained by jnyx74.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stress_prediction_pipeline_en_5.5.0_3.0_1725292147776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stress_prediction_pipeline_en_5.5.0_3.0_1725292147776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("stress_prediction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("stress_prediction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stress_prediction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jnyx74/stress-prediction
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline_en.md
new file mode 100644
index 00000000000000..ae1932624b7dc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline pipeline BertForSequenceClassification from Katsiaryna
+author: John Snow Labs
+name: stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline` is a English model originally trained by Katsiaryna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline_en_5.5.0_3.0_1725293733827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline_en_5.5.0_3.0_1725293733827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stsb_tinybert_l_4_finetuned_auc_151221_top3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|54.2 MB|
+
+## References
+
+https://huggingface.co/Katsiaryna/stsb-TinyBERT-L-4-finetuned_auc_151221-top3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sumathi_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-02-sumathi_camembert_en.md
new file mode 100644
index 00000000000000..ca5611ff24c311
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sumathi_camembert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sumathi_camembert CamemBertEmbeddings from SumathiS
+author: John Snow Labs
+name: sumathi_camembert
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sumathi_camembert` is a English model originally trained by SumathiS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sumathi_camembert_en_5.5.0_3.0_1725300116904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sumathi_camembert_en_5.5.0_3.0_1725300116904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("sumathi_camembert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("sumathi_camembert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sumathi_camembert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/SumathiS/sumathi_camembert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-syntrans_spanish_english_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-syntrans_spanish_english_v2_en.md
new file mode 100644
index 00000000000000..87887fe7b7d4af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-syntrans_spanish_english_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English syntrans_spanish_english_v2 MarianTransformer from lkoppens
+author: John Snow Labs
+name: syntrans_spanish_english_v2
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`syntrans_spanish_english_v2` is a English model originally trained by lkoppens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/syntrans_spanish_english_v2_en_5.5.0_3.0_1725295646814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/syntrans_spanish_english_v2_en_5.5.0_3.0_1725295646814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("syntrans_spanish_english_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("syntrans_spanish_english_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|syntrans_spanish_english_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.3 MB|
+
+## References
+
+https://huggingface.co/lkoppens/syntrans-es-en-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline_en.md
new file mode 100644
index 00000000000000..d75c0cc2663459
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline pipeline DeBertaForSequenceClassification from BenjaminOcampo
+author: John Snow Labs
+name: task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline` is a English model originally trained by BenjaminOcampo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline_en_5.5.0_3.0_1725281641321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline_en_5.5.0_3.0_1725281641321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|task_subtle_task__model_deberta__aug_method_austroasiatic_languages_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|607.5 MB|
+
+## References
+
+https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-aav
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-tatar_en.md b/docs/_posts/ahmedlone127/2024-09-02-tatar_en.md
new file mode 100644
index 00000000000000..cec1756d65fca5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-tatar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tatar MarianTransformer from baobuiquang
+author: John Snow Labs
+name: tatar
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tatar` is a English model originally trained by baobuiquang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tatar_en_5.5.0_3.0_1725294657881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tatar_en_5.5.0_3.0_1725294657881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("tatar","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("tatar","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tatar|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|475.6 MB|
+
+## References
+
+https://huggingface.co/baobuiquang/TT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-test_model_2_en.md b/docs/_posts/ahmedlone127/2024-09-02-test_model_2_en.md
new file mode 100644
index 00000000000000..14c40d4f0371c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-test_model_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_model_2 CamemBertEmbeddings from Smail
+author: John Snow Labs
+name: test_model_2
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_2` is a English model originally trained by Smail.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_2_en_5.5.0_3.0_1725320473214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_2_en_5.5.0_3.0_1725320473214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("test_model_2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("test_model_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Smail/test-model-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-test_model_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-test_model_2_pipeline_en.md
new file mode 100644
index 00000000000000..aada42a441bd61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-test_model_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_model_2_pipeline pipeline CamemBertEmbeddings from Smail
+author: John Snow Labs
+name: test_model_2_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_2_pipeline` is a English model originally trained by Smail.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_2_pipeline_en_5.5.0_3.0_1725320550142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_2_pipeline_en_5.5.0_3.0_1725320550142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_model_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_model_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Smail/test-model-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-test_model_hasanmurad_en.md b/docs/_posts/ahmedlone127/2024-09-02-test_model_hasanmurad_en.md
new file mode 100644
index 00000000000000..8bb4840ba17e15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-test_model_hasanmurad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_model_hasanmurad CamemBertEmbeddings from Hasanmurad
+author: John Snow Labs
+name: test_model_hasanmurad
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_hasanmurad` is a English model originally trained by Hasanmurad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_hasanmurad_en_5.5.0_3.0_1725302219929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_hasanmurad_en_5.5.0_3.0_1725302219929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("test_model_hasanmurad","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("test_model_hasanmurad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_hasanmurad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Hasanmurad/test-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-testhelsinkimulenjpth02_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-testhelsinkimulenjpth02_pipeline_en.md
new file mode 100644
index 00000000000000..9e0a6518f66eb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-testhelsinkimulenjpth02_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English testhelsinkimulenjpth02_pipeline pipeline MarianTransformer from Shularp
+author: John Snow Labs
+name: testhelsinkimulenjpth02_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testhelsinkimulenjpth02_pipeline` is a English model originally trained by Shularp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testhelsinkimulenjpth02_pipeline_en_5.5.0_3.0_1725295863186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testhelsinkimulenjpth02_pipeline_en_5.5.0_3.0_1725295863186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("testhelsinkimulenjpth02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("testhelsinkimulenjpth02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testhelsinkimulenjpth02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.7 MB|
+
+## References
+
+https://huggingface.co/Shularp/TestHelsinkimulEnJpTh02
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-text_classification_model_multilingual_xx.md b/docs/_posts/ahmedlone127/2024-09-02-text_classification_model_multilingual_xx.md
new file mode 100644
index 00000000000000..2cb83475bf6bbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-text_classification_model_multilingual_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual text_classification_model_multilingual DistilBertForSequenceClassification from cwchang
+author: John Snow Labs
+name: text_classification_model_multilingual
+date: 2024-09-02
+tags: [xx, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_model_multilingual` is a Multilingual model originally trained by cwchang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_model_multilingual_xx_5.5.0_3.0_1725305752656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_model_multilingual_xx_5.5.0_3.0_1725305752656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("text_classification_model_multilingual","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("text_classification_model_multilingual", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_classification_model_multilingual|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|508.0 MB|
+
+## References
+
+https://huggingface.co/cwchang/text-classification-model-multilingual
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforsequenceclassification_en.md b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforsequenceclassification_en.md
new file mode 100644
index 00000000000000..8ac452a98b67ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-tiny_random_albertforsequenceclassification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tiny_random_albertforsequenceclassification AlbertForSequenceClassification from hf-tiny-model-private
+author: John Snow Labs
+name: tiny_random_albertforsequenceclassification
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_albertforsequenceclassification` is a English model originally trained by hf-tiny-model-private.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_albertforsequenceclassification_en_5.5.0_3.0_1725301745309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_albertforsequenceclassification_en_5.5.0_3.0_1725301745309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("tiny_random_albertforsequenceclassification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("tiny_random_albertforsequenceclassification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_random_albertforsequenceclassification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|15.2 MB|
+
+## References
+
+https://huggingface.co/hf-tiny-model-private/tiny-random-AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-toneanalysis_en.md b/docs/_posts/ahmedlone127/2024-09-02-toneanalysis_en.md
new file mode 100644
index 00000000000000..72220cb68e930b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-toneanalysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English toneanalysis DistilBertForSequenceClassification from Sadikshya
+author: John Snow Labs
+name: toneanalysis
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toneanalysis` is a English model originally trained by Sadikshya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toneanalysis_en_5.5.0_3.0_1725305519191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toneanalysis_en_5.5.0_3.0_1725305519191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("toneanalysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("toneanalysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toneanalysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/Sadikshya/ToneAnalysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-toneanalysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-toneanalysis_pipeline_en.md
new file mode 100644
index 00000000000000..495344092f10dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-toneanalysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English toneanalysis_pipeline pipeline DistilBertForSequenceClassification from Sadikshya
+author: John Snow Labs
+name: toneanalysis_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toneanalysis_pipeline` is a English model originally trained by Sadikshya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toneanalysis_pipeline_en_5.5.0_3.0_1725305537348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toneanalysis_pipeline_en_5.5.0_3.0_1725305537348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("toneanalysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("toneanalysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toneanalysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/Sadikshya/ToneAnalysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-traduttore_italian_english_2_en.md b/docs/_posts/ahmedlone127/2024-09-02-traduttore_italian_english_2_en.md
new file mode 100644
index 00000000000000..e5568a1e50ad49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-traduttore_italian_english_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English traduttore_italian_english_2 MarianTransformer from zaneas
+author: John Snow Labs
+name: traduttore_italian_english_2
+date: 2024-09-02
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`traduttore_italian_english_2` is a English model originally trained by zaneas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/traduttore_italian_english_2_en_5.5.0_3.0_1725294714601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/traduttore_italian_english_2_en_5.5.0_3.0_1725294714601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("traduttore_italian_english_2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("traduttore_italian_english_2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|traduttore_italian_english_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|625.0 MB|
+
+## References
+
+https://huggingface.co/zaneas/Traduttore_IT_EN_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-traffy_problem_predict_en.md b/docs/_posts/ahmedlone127/2024-09-02-traffy_problem_predict_en.md
new file mode 100644
index 00000000000000..b5d39be11d9c7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-traffy_problem_predict_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English traffy_problem_predict CamemBertForSequenceClassification from nlp-chula
+author: John Snow Labs
+name: traffy_problem_predict
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`traffy_problem_predict` is a English model originally trained by nlp-chula.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/traffy_problem_predict_en_5.5.0_3.0_1725299168600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/traffy_problem_predict_en_5.5.0_3.0_1725299168600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("traffy_problem_predict","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("traffy_problem_predict", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|traffy_problem_predict|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/nlp-chula/traffy-problem-predict
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-trainingarg_en.md b/docs/_posts/ahmedlone127/2024-09-02-trainingarg_en.md
new file mode 100644
index 00000000000000..e61b2da8acb012
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-trainingarg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trainingarg DistilBertForSequenceClassification from PiotrNaspinski
+author: John Snow Labs
+name: trainingarg
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainingarg` is a English model originally trained by PiotrNaspinski.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trainingarg_en_5.5.0_3.0_1725292282776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainingarg_en_5.5.0_3.0_1725292282776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("trainingarg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("trainingarg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainingarg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PiotrNaspinski/TrainingArg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-transformer_maltese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-transformer_maltese_pipeline_en.md
new file mode 100644
index 00000000000000..308df2d26c5784
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-transformer_maltese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English transformer_maltese_pipeline pipeline MarianTransformer from leenag
+author: John Snow Labs
+name: transformer_maltese_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transformer_maltese_pipeline` is a English model originally trained by leenag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transformer_maltese_pipeline_en_5.5.0_3.0_1725303951541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transformer_maltese_pipeline_en_5.5.0_3.0_1725303951541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("transformer_maltese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("transformer_maltese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transformer_maltese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.4 MB|
+
+## References
+
+https://huggingface.co/leenag/Transformer_MT
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-translate_model_v3_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-translate_model_v3_1_pipeline_en.md
new file mode 100644
index 00000000000000..f9af90d00d08a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-translate_model_v3_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English translate_model_v3_1_pipeline pipeline MarianTransformer from gshields
+author: John Snow Labs
+name: translate_model_v3_1_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translate_model_v3_1_pipeline` is a English model originally trained by gshields.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translate_model_v3_1_pipeline_en_5.5.0_3.0_1725303714770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translate_model_v3_1_pipeline_en_5.5.0_3.0_1725303714770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("translate_model_v3_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translate_model_v3_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translate_model_v3_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.6 MB|
+
+## References
+
+https://huggingface.co/gshields/translate_model_v3.1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-triple_20e_1000_fit_all_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-02-triple_20e_1000_fit_all_mpnet_base_v2_en.md
new file mode 100644
index 00000000000000..44701425fe16c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-triple_20e_1000_fit_all_mpnet_base_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English triple_20e_1000_fit_all_mpnet_base_v2 MPNetEmbeddings from satyroffrost
+author: John Snow Labs
+name: triple_20e_1000_fit_all_mpnet_base_v2
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`triple_20e_1000_fit_all_mpnet_base_v2` is a English model originally trained by satyroffrost.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/triple_20e_1000_fit_all_mpnet_base_v2_en_5.5.0_3.0_1725313538728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/triple_20e_1000_fit_all_mpnet_base_v2_en_5.5.0_3.0_1725313538728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("triple_20e_1000_fit_all_mpnet_base_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("triple_20e_1000_fit_all_mpnet_base_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|triple_20e_1000_fit_all_mpnet_base_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/satyroffrost/triple-20e-1000-fit-all-mpnet-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-tweets_sentiment_model_60k_samples_en.md b/docs/_posts/ahmedlone127/2024-09-02-tweets_sentiment_model_60k_samples_en.md
new file mode 100644
index 00000000000000..8450992d2d6834
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-tweets_sentiment_model_60k_samples_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tweets_sentiment_model_60k_samples DistilBertForSequenceClassification from ivanscorral
+author: John Snow Labs
+name: tweets_sentiment_model_60k_samples
+date: 2024-09-02
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweets_sentiment_model_60k_samples` is a English model originally trained by ivanscorral.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweets_sentiment_model_60k_samples_en_5.5.0_3.0_1725305873180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweets_sentiment_model_60k_samples_en_5.5.0_3.0_1725305873180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("tweets_sentiment_model_60k_samples","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("tweets_sentiment_model_60k_samples", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweets_sentiment_model_60k_samples|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ivanscorral/tweets-sentiment-model-60k-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-ukr_roberta_base_pipeline_uk.md b/docs/_posts/ahmedlone127/2024-09-02-ukr_roberta_base_pipeline_uk.md
new file mode 100644
index 00000000000000..c9d623ff170323
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-ukr_roberta_base_pipeline_uk.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Ukrainian ukr_roberta_base_pipeline pipeline RoBertaEmbeddings from youscan
+author: John Snow Labs
+name: ukr_roberta_base_pipeline
+date: 2024-09-02
+tags: [uk, open_source, pipeline, onnx]
+task: Embeddings
+language: uk
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ukr_roberta_base_pipeline` is a Ukrainian model originally trained by youscan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ukr_roberta_base_pipeline_uk_5.5.0_3.0_1725264760220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ukr_roberta_base_pipeline_uk_5.5.0_3.0_1725264760220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ukr_roberta_base_pipeline", lang = "uk")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ukr_roberta_base_pipeline", lang = "uk")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ukr_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|uk|
+|Size:|471.3 MB|
+
+## References
+
+https://huggingface.co/youscan/ukr-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-umberto_commoncrawl_cased_v1_it.md b/docs/_posts/ahmedlone127/2024-09-02-umberto_commoncrawl_cased_v1_it.md
new file mode 100644
index 00000000000000..fc74d85e5fe6e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-umberto_commoncrawl_cased_v1_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian umberto_commoncrawl_cased_v1 CamemBertEmbeddings from Musixmatch
+author: John Snow Labs
+name: umberto_commoncrawl_cased_v1
+date: 2024-09-02
+tags: [it, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`umberto_commoncrawl_cased_v1` is a Italian model originally trained by Musixmatch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/umberto_commoncrawl_cased_v1_it_5.5.0_3.0_1725319795937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/umberto_commoncrawl_cased_v1_it_5.5.0_3.0_1725319795937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("umberto_commoncrawl_cased_v1","it") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("umberto_commoncrawl_cased_v1","it") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|umberto_commoncrawl_cased_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|it|
+|Size:|263.1 MB|
+
+## References
+
+https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-umberto_wikipedia_uncased_v1_it.md b/docs/_posts/ahmedlone127/2024-09-02-umberto_wikipedia_uncased_v1_it.md
new file mode 100644
index 00000000000000..d2a1a5e17b6c03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-umberto_wikipedia_uncased_v1_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian umberto_wikipedia_uncased_v1 CamemBertEmbeddings from Musixmatch
+author: John Snow Labs
+name: umberto_wikipedia_uncased_v1
+date: 2024-09-02
+tags: [it, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`umberto_wikipedia_uncased_v1` is a Italian model originally trained by Musixmatch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/umberto_wikipedia_uncased_v1_it_5.5.0_3.0_1725319983387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/umberto_wikipedia_uncased_v1_it_5.5.0_3.0_1725319983387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("umberto_wikipedia_uncased_v1","it") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("umberto_wikipedia_uncased_v1","it") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|umberto_wikipedia_uncased_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|it|
+|Size:|262.7 MB|
+
+## References
+
+https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-upsc_classification_model_v1_en.md b/docs/_posts/ahmedlone127/2024-09-02-upsc_classification_model_v1_en.md
new file mode 100644
index 00000000000000..d6cdc77edd72a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-upsc_classification_model_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English upsc_classification_model_v1 MPNetEmbeddings from kowshik
+author: John Snow Labs
+name: upsc_classification_model_v1
+date: 2024-09-02
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`upsc_classification_model_v1` is a English model originally trained by kowshik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/upsc_classification_model_v1_en_5.5.0_3.0_1725313822986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/upsc_classification_model_v1_en_5.5.0_3.0_1725313822986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("upsc_classification_model_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("upsc_classification_model_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|upsc_classification_model_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/kowshik/upsc-classification-model-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-urdish_roberta_base_sentiment_ur.md b/docs/_posts/ahmedlone127/2024-09-02-urdish_roberta_base_sentiment_ur.md
new file mode 100644
index 00000000000000..e5013d9b8876f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-urdish_roberta_base_sentiment_ur.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Urdu urdish_roberta_base_sentiment RoBertaForSequenceClassification from dataranch
+author: John Snow Labs
+name: urdish_roberta_base_sentiment
+date: 2024-09-02
+tags: [ur, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: ur
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`urdish_roberta_base_sentiment` is a Urdu model originally trained by dataranch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/urdish_roberta_base_sentiment_ur_5.5.0_3.0_1725277874263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/urdish_roberta_base_sentiment_ur_5.5.0_3.0_1725277874263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("urdish_roberta_base_sentiment","ur") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("urdish_roberta_base_sentiment", "ur")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|urdish_roberta_base_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ur|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/dataranch/urdish-roberta-base-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-vila_roberta_large_s2vl_internal_en.md b/docs/_posts/ahmedlone127/2024-09-02-vila_roberta_large_s2vl_internal_en.md
new file mode 100644
index 00000000000000..20727b4082d100
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-vila_roberta_large_s2vl_internal_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vila_roberta_large_s2vl_internal RoBertaForTokenClassification from allenai
+author: John Snow Labs
+name: vila_roberta_large_s2vl_internal
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vila_roberta_large_s2vl_internal` is a English model originally trained by allenai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vila_roberta_large_s2vl_internal_en_5.5.0_3.0_1725310840298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vila_roberta_large_s2vl_internal_en_5.5.0_3.0_1725310840298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("vila_roberta_large_s2vl_internal","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("vila_roberta_large_s2vl_internal", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vila_roberta_large_s2vl_internal|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/allenai/vila-roberta-large-s2vl-internal
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-vila_roberta_large_s2vl_internal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-vila_roberta_large_s2vl_internal_pipeline_en.md
new file mode 100644
index 00000000000000..168ecd3fda5afd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-vila_roberta_large_s2vl_internal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vila_roberta_large_s2vl_internal_pipeline pipeline RoBertaForTokenClassification from allenai
+author: John Snow Labs
+name: vila_roberta_large_s2vl_internal_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vila_roberta_large_s2vl_internal_pipeline` is a English model originally trained by allenai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vila_roberta_large_s2vl_internal_pipeline_en_5.5.0_3.0_1725310912419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vila_roberta_large_s2vl_internal_pipeline_en_5.5.0_3.0_1725310912419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vila_roberta_large_s2vl_internal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vila_roberta_large_s2vl_internal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vila_roberta_large_s2vl_internal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/allenai/vila-roberta-large-s2vl-internal
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_base_arabic_quran_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_arabic_quran_en.md
new file mode 100644
index 00000000000000..19d2691005a659
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_base_arabic_quran_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_base_arabic_quran WhisperForCTC from tarteel-ai
+author: John Snow Labs
+name: whisper_base_arabic_quran
+date: 2024-09-02
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_arabic_quran` is a English model originally trained by tarteel-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_arabic_quran_en_5.5.0_3.0_1725249487731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_arabic_quran_en_5.5.0_3.0_1725249487731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_base_arabic_quran","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_base_arabic_quran", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_arabic_quran|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|643.1 MB|
+
+## References
+
+https://huggingface.co/tarteel-ai/whisper-base-ar-quran
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_medium_portuguese_jlondonobo_pt.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_medium_portuguese_jlondonobo_pt.md
new file mode 100644
index 00000000000000..1608a5f35a51b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_medium_portuguese_jlondonobo_pt.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Portuguese whisper_medium_portuguese_jlondonobo WhisperForCTC from jlondonobo
+author: John Snow Labs
+name: whisper_medium_portuguese_jlondonobo
+date: 2024-09-02
+tags: [pt, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_medium_portuguese_jlondonobo` is a Portuguese model originally trained by jlondonobo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_medium_portuguese_jlondonobo_pt_5.5.0_3.0_1725251079765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_medium_portuguese_jlondonobo_pt_5.5.0_3.0_1725251079765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_medium_portuguese_jlondonobo","pt") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_medium_portuguese_jlondonobo", "pt")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_medium_portuguese_jlondonobo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|pt|
+|Size:|4.8 GB|
+
+## References
+
+https://huggingface.co/jlondonobo/whisper-medium-pt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_chinese_base_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_chinese_base_en.md
new file mode 100644
index 00000000000000..d67cf1eddfadf1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_chinese_base_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_small_chinese_base WhisperForCTC from Jingmiao
+author: John Snow Labs
+name: whisper_small_chinese_base
+date: 2024-09-02
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_chinese_base` is a English model originally trained by Jingmiao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_base_en_5.5.0_3.0_1725287656943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_base_en_5.5.0_3.0_1725287656943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_chinese_base","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_chinese_base", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_chinese_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Jingmiao/whisper-small-chinese_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_english_jenrish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_english_jenrish_pipeline_en.md
new file mode 100644
index 00000000000000..4c0b77e8fb5a6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_english_jenrish_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_small_english_jenrish_pipeline pipeline WhisperForCTC from jenrish
+author: John Snow Labs
+name: whisper_small_english_jenrish_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_english_jenrish_pipeline` is a English model originally trained by jenrish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_english_jenrish_pipeline_en_5.5.0_3.0_1725289685283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_english_jenrish_pipeline_en_5.5.0_3.0_1725289685283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_english_jenrish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_english_jenrish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_english_jenrish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/jenrish/whisper-small-en
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_small_thai_film6912_pipeline_th.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_thai_film6912_pipeline_th.md
new file mode 100644
index 00000000000000..ece91d6d862d20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_small_thai_film6912_pipeline_th.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Thai whisper_small_thai_film6912_pipeline pipeline WhisperForCTC from FILM6912
+author: John Snow Labs
+name: whisper_small_thai_film6912_pipeline
+date: 2024-09-02
+tags: [th, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_thai_film6912_pipeline` is a Thai model originally trained by FILM6912.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_thai_film6912_pipeline_th_5.5.0_3.0_1725289850134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_thai_film6912_pipeline_th_5.5.0_3.0_1725289850134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_thai_film6912_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_thai_film6912_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_thai_film6912_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/FILM6912/Whisper-small-thai
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_tiny_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_tiny_pipeline_xx.md
new file mode 100644
index 00000000000000..f724a7935c02f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_tiny_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual whisper_tiny_pipeline pipeline WhisperForCTC from openai
+author: John Snow Labs
+name: whisper_tiny_pipeline
+date: 2024-09-02
+tags: [xx, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_pipeline` is a Multilingual model originally trained by openai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_pipeline_xx_5.5.0_3.0_1725286705729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_pipeline_xx_5.5.0_3.0_1725286705729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tiny_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|242.9 MB|
+
+## References
+
+https://huggingface.co/openai/whisper-tiny
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-whisper_tiny_xx.md b/docs/_posts/ahmedlone127/2024-09-02-whisper_tiny_xx.md
new file mode 100644
index 00000000000000..92fc4ffe400245
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-whisper_tiny_xx.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Multilingual whisper_tiny WhisperForCTC from openai
+author: John Snow Labs
+name: whisper_tiny
+date: 2024-09-02
+tags: [xx, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny` is a Multilingual model originally trained by openai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_xx_5.5.0_3.0_1725286637306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_xx_5.5.0_3.0_1725286637306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny","xx") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny", "xx")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|xx|
+|Size:|242.8 MB|
+
+## References
+
+https://huggingface.co/openai/whisper-tiny
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_synth_data_gpt4turbo_1_en.md b/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_synth_data_gpt4turbo_1_en.md
new file mode 100644
index 00000000000000..fb484ee5d9db2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-wsd_myriade_synth_data_gpt4turbo_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English wsd_myriade_synth_data_gpt4turbo_1 CamemBertForTokenClassification from gguichard
+author: John Snow Labs
+name: wsd_myriade_synth_data_gpt4turbo_1
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wsd_myriade_synth_data_gpt4turbo_1` is a English model originally trained by gguichard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wsd_myriade_synth_data_gpt4turbo_1_en_5.5.0_3.0_1725266415940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wsd_myriade_synth_data_gpt4turbo_1_en_5.5.0_3.0_1725266415940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("wsd_myriade_synth_data_gpt4turbo_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("wsd_myriade_synth_data_gpt4turbo_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wsd_myriade_synth_data_gpt4turbo_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/gguichard/wsd_myriade_synth_data_gpt4turbo_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_robert_finetune_model_vn_ver2_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_robert_finetune_model_vn_ver2_en.md
new file mode 100644
index 00000000000000..c80912fc61fa73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_robert_finetune_model_vn_ver2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_robert_finetune_model_vn_ver2 XlmRoBertaForTokenClassification from zhangwenzhe
+author: John Snow Labs
+name: xlm_robert_finetune_model_vn_ver2
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_robert_finetune_model_vn_ver2` is a English model originally trained by zhangwenzhe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_robert_finetune_model_vn_ver2_en_5.5.0_3.0_1725316213145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_robert_finetune_model_vn_ver2_en_5.5.0_3.0_1725316213145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_robert_finetune_model_vn_ver2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_robert_finetune_model_vn_ver2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_robert_finetune_model_vn_ver2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|771.9 MB|
+
+## References
+
+https://huggingface.co/zhangwenzhe/XLM-Robert-finetune-model-VN-ver2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_aiekek_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_aiekek_en.md
new file mode 100644
index 00000000000000..a560b80ed4e858
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_aiekek_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_aiekek XlmRoBertaForTokenClassification from AIEKEK
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_aiekek
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_aiekek` is a English model originally trained by AIEKEK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_aiekek_en_5.5.0_3.0_1725321423199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_aiekek_en_5.5.0_3.0_1725321423199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_aiekek","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_aiekek", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_aiekek|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/AIEKEK/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline_en.md
new file mode 100644
index 00000000000000..77d5fbc9a2906e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline pipeline XlmRoBertaForTokenClassification from clboetticher-school
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline` is a English model originally trained by clboetticher-school.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline_en_5.5.0_3.0_1725317685775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline_en_5.5.0_3.0_1725317685775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_clboetticher_school_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/clboetticher-school/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline_en.md
new file mode 100644
index 00000000000000..4d6f346af2b989
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline pipeline XlmRoBertaForTokenClassification from AlanHou
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline` is a English model originally trained by AlanHou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline_en_5.5.0_3.0_1725308035597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline_en_5.5.0_3.0_1725308035597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_alanhou_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/AlanHou/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline_en.md
new file mode 100644
index 00000000000000..04914ecb47f09b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline pipeline XlmRoBertaForTokenClassification from feic36
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline` is a English model originally trained by feic36.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline_en_5.5.0_3.0_1725316655535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline_en_5.5.0_3.0_1725316655535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_feic36_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/feic36/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_k3nneth_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_k3nneth_en.md
new file mode 100644
index 00000000000000..b8440c14103345
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_k3nneth_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_k3nneth XlmRoBertaForTokenClassification from k3nneth
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_k3nneth
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_k3nneth` is a English model originally trained by k3nneth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_k3nneth_en_5.5.0_3.0_1725317292108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_k3nneth_en_5.5.0_3.0_1725317292108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_k3nneth","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_k3nneth", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_k3nneth|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/k3nneth/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline_en.md
new file mode 100644
index 00000000000000..d16e1fc9a8488e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline pipeline XlmRoBertaForTokenClassification from k3nneth
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline` is a English model originally trained by k3nneth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline_en_5.5.0_3.0_1725317360835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline_en_5.5.0_3.0_1725317360835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_k3nneth_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/k3nneth/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline_en.md
new file mode 100644
index 00000000000000..2966445d5787c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline pipeline XlmRoBertaForTokenClassification from g22tk021
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline` is a English model originally trained by g22tk021.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline_en_5.5.0_3.0_1725316772720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline_en_5.5.0_3.0_1725316772720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_g22tk021_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/g22tk021/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_maxfrax_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_maxfrax_en.md
new file mode 100644
index 00000000000000..93485527a2305c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_maxfrax_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_maxfrax XlmRoBertaForTokenClassification from maxfrax
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_maxfrax
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_maxfrax` is a English model originally trained by maxfrax.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_maxfrax_en_5.5.0_3.0_1725317055341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_maxfrax_en_5.5.0_3.0_1725317055341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_maxfrax","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_maxfrax", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_maxfrax|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/maxfrax/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_noveled_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_noveled_en.md
new file mode 100644
index 00000000000000..38524770d2dc91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_noveled_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_noveled XlmRoBertaForTokenClassification from Noveled
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_noveled
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_noveled` is a English model originally trained by Noveled.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_noveled_en_5.5.0_3.0_1725316784992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_noveled_en_5.5.0_3.0_1725316784992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_noveled","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_noveled", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_noveled|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|832.0 MB|
+
+## References
+
+https://huggingface.co/Noveled/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_scionk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_scionk_pipeline_en.md
new file mode 100644
index 00000000000000..11f7d869742cae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_scionk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_scionk_pipeline pipeline XlmRoBertaForTokenClassification from scionk
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_scionk_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_scionk_pipeline` is a English model originally trained by scionk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_scionk_pipeline_en_5.5.0_3.0_1725307801696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_scionk_pipeline_en_5.5.0_3.0_1725307801696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_scionk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_scionk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_scionk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.0 MB|
+
+## References
+
+https://huggingface.co/scionk/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_xrchen11_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_xrchen11_en.md
new file mode 100644
index 00000000000000..81d406df53a30c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_xrchen11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_xrchen11 XlmRoBertaForTokenClassification from xrchen11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_xrchen11
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_xrchen11` is a English model originally trained by xrchen11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_xrchen11_en_5.5.0_3.0_1725317148879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_xrchen11_en_5.5.0_3.0_1725317148879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_xrchen11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_xrchen11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_xrchen11|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/xrchen11/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline_en.md
new file mode 100644
index 00000000000000..5fc0909d5a935d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline pipeline XlmRoBertaForTokenClassification from xrchen11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline
+date: 2024-09-02
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline` is a English model originally trained by xrchen11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline_en_5.5.0_3.0_1725317237076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline_en_5.5.0_3.0_1725317237076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_xrchen11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/xrchen11/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_Part_1_XLM_Model_E1_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_Part_1_XLM_Model_E1_en.md
new file mode 100644
index 00000000000000..605a509ac52083
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_Part_1_XLM_Model_E1_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from horsbug98)
+author: John Snow Labs
+name: xlm_roberta_qa_Part_1_XLM_Model_E1
+date: 2024-09-02
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `Part_1_XLM_Model_E1` is a English model originally trained by `horsbug98`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_Part_1_XLM_Model_E1_en_5.5.0_3.0_1725255031126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_Part_1_XLM_Model_E1_en_5.5.0_3.0_1725255031126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_Part_1_XLM_Model_E1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_Part_1_XLM_Model_E1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.tydiqa.xlm_roberta.by_horsbug98").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_Part_1_XLM_Model_E1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|877.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/horsbug98/Part_1_XLM_Model_E1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_chamorro_xlm_r_ch.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_chamorro_xlm_r_ch.md
new file mode 100644
index 00000000000000..5888656f615ba3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_addi_chamorro_xlm_r_ch.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Chamorro xlm_roberta_qa_addi_chamorro_xlm_r XlmRoBertaForQuestionAnswering from Gantenbein
+author: John Snow Labs
+name: xlm_roberta_qa_addi_chamorro_xlm_r
+date: 2024-09-02
+tags: [ch, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: ch
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_addi_chamorro_xlm_r` is a Chamorro model originally trained by Gantenbein.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_chamorro_xlm_r_ch_5.5.0_3.0_1725253993154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_chamorro_xlm_r_ch_5.5.0_3.0_1725253993154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_addi_chamorro_xlm_r","ch") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_addi_chamorro_xlm_r", "ch")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_addi_chamorro_xlm_r|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ch|
+|Size:|776.3 MB|
+
+## References
+
+https://huggingface.co/Gantenbein/ADDI-CH-XLM-R
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_en.md
new file mode 100644
index 00000000000000..f19009209a1427
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from teacookies)
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465522
+date: 2024-09-02
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-base-squad2-24465522` is a English model originally trained by `teacookies`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_en_5.5.0_3.0_1725253957048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465522_en_5.5.0_3.0_1725253957048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465522","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465522","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.xlm_roberta.base_24465522.by_teacookies").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465522|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|887.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465522
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_arabic_pipeline_ar.md
new file mode 100644
index 00000000000000..634d6a6f8519a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_arabic_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic xlm_roberta_qa_xlm_roberta_base_arabic_pipeline pipeline XlmRoBertaForQuestionAnswering from bhavikardeshna
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_arabic_pipeline
+date: 2024-09-02
+tags: [ar, open_source, pipeline, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_arabic_pipeline` is a Arabic model originally trained by bhavikardeshna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_arabic_pipeline_ar_5.5.0_3.0_1725235460988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_arabic_pipeline_ar_5.5.0_3.0_1725235460988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_arabic_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_arabic_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|884.1 MB|
+
+## References
+
+https://huggingface.co/bhavikardeshna/xlm-roberta-base-arabic
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_en.md
new file mode 100644
index 00000000000000..9018bb0827edda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlm_roberta_qa_xlm_roberta_base_squad2_distilled_en.md
@@ -0,0 +1,116 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from deepset)
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_squad2_distilled
+date: 2024-09-02
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-squad2-distilled` is a English model originally trained by `deepset`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_squad2_distilled_en_5.5.0_3.0_1725255029196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_squad2_distilled_en_5.5.0_3.0_1725255029196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_squad2_distilled","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_xlm_roberta_base_squad2_distilled","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.xlm_roberta.distilled_base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_squad2_distilled|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/deepset/xlm-roberta-base-squad2-distilled
+- https://www.linkedin.com/company/deepset-ai/
+- https://twitter.com/deepset_ai
+- http://www.deepset.ai/jobs
+- https://haystack.deepset.ai/community/join
+- https://github.com/deepset-ai/haystack/
+- https://github.com/deepset-ai/FARM
+- https://deepset.ai/germanquad
+- https://deepset.ai
+- https://deepset.ai/german-bert
+- https://github.com/deepset-ai/haystack/discussions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_trained_panx_english_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_trained_panx_english_en.md
new file mode 100644
index 00000000000000..453d2e622f0eeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlmr_base_trained_panx_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_base_trained_panx_english XlmRoBertaForTokenClassification from DeepaPeri
+author: John Snow Labs
+name: xlmr_base_trained_panx_english
+date: 2024-09-02
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_trained_panx_english` is a English model originally trained by DeepaPeri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_trained_panx_english_en_5.5.0_3.0_1725316002867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_trained_panx_english_en_5.5.0_3.0_1725316002867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlmr_base_trained_panx_english","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_base_trained_panx_english", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_trained_panx_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|797.4 MB|
+
+## References
+
+https://huggingface.co/DeepaPeri/XLMR-BASE-TRAINED-PANX-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_akshat_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_akshat_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..41cfafefe0644d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_akshat_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from Akshat)
+author: John Snow Labs
+name: xlmroberta_ner_akshat_base_finetuned_panx
+date: 2024-09-02
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `Akshat`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_akshat_base_finetuned_panx_de_5.5.0_3.0_1725309324445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_akshat_base_finetuned_panx_de_5.5.0_3.0_1725309324445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_akshat_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_akshat_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_akshat_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Akshat/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_akshat_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_akshat_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..4892377dfe90d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_akshat_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_akshat_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from Akshat
+author: John Snow Labs
+name: xlmroberta_ner_akshat_base_finetuned_panx_pipeline
+date: 2024-09-02
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_akshat_base_finetuned_panx_pipeline` is a German model originally trained by Akshat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_akshat_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725309391718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_akshat_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725309391718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_akshat_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_akshat_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_akshat_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.4 MB|
+
+## References
+
+https://huggingface.co/Akshat/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_wnut2017_en.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_wnut2017_en.md
new file mode 100644
index 00000000000000..3ccb81bb24c7fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_base_wnut2017_en.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: English XLMRobertaForTokenClassification Base Cased model (from tner)
+author: John Snow Labs
+name: xlmroberta_ner_base_wnut2017
+date: 2024-09-02
+tags: [en, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-wnut2017` is a English model originally trained by `tner`.
+
+## Predicted Entities
+
+`product`, `corporation`, `group`, `work of art`, `person`, `location`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_wnut2017_en_5.5.0_3.0_1725308489113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_wnut2017_en_5.5.0_3.0_1725308489113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_wnut2017","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_wnut2017","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.ner.xlmr_roberta.wnut2017.base.by_tner").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_wnut2017|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|786.5 MB|
+
+## References
+
+References
+
+- https://huggingface.co/tner/xlm-roberta-base-wnut2017
+- https://github.com/asahi417/tner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..8deb49dedf3799
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from lijingxin
+author: John Snow Labs
+name: xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline
+date: 2024-09-02
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline` is a German model originally trained by lijingxin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725309125091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725309125091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_lijingxin_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/lijingxin/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_venturaville_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_venturaville_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..2ad9e61884ea41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_venturaville_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_venturaville_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from venturaville
+author: John Snow Labs
+name: xlmroberta_ner_venturaville_base_finetuned_panx_pipeline
+date: 2024-09-02
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_venturaville_base_finetuned_panx_pipeline` is a German model originally trained by venturaville.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_venturaville_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725309327666.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_venturaville_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725309327666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_venturaville_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_venturaville_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_venturaville_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/venturaville/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_xml_roberta_base_finetuned_panx_fr.md b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_xml_roberta_base_finetuned_panx_fr.md
new file mode 100644
index 00000000000000..43295c7ff07e51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-xlmroberta_ner_xml_roberta_base_finetuned_panx_fr.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: French XLMRobertaForTokenClassification Base Cased model (from olpa)
+author: John Snow Labs
+name: xlmroberta_ner_xml_roberta_base_finetuned_panx
+date: 2024-09-02
+tags: [fr, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xml-roberta-base-finetuned-panx-fr` is a French model originally trained by `olpa`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xml_roberta_base_finetuned_panx_fr_5.5.0_3.0_1725308727904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xml_roberta_base_finetuned_panx_fr_5.5.0_3.0_1725308727904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xml_roberta_base_finetuned_panx","fr") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xml_roberta_base_finetuned_panx","fr")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("fr.ner.xlmr_roberta.xtreme.base_finetuned.by_olpa").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xml_roberta_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|fr|
+|Size:|840.9 MB|
+
+## References
+
+References
+
+- https://huggingface.co/olpa/xml-roberta-base-finetuned-panx-fr
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-2020_q2_75p_filtered_2_en.md b/docs/_posts/ahmedlone127/2024-09-03-2020_q2_75p_filtered_2_en.md
new file mode 100644
index 00000000000000..360fda45317ad1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-2020_q2_75p_filtered_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2020_q2_75p_filtered_2 RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_75p_filtered_2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_75p_filtered_2` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_75p_filtered_2_en_5.5.0_3.0_1725382445019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_75p_filtered_2_en_5.5.0_3.0_1725382445019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("2020_q2_75p_filtered_2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("2020_q2_75p_filtered_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_75p_filtered_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|463.2 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-75p-filtered_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-2020_q2_75p_filtered_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-2020_q2_75p_filtered_2_pipeline_en.md
new file mode 100644
index 00000000000000..6bf3771eea2468
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-2020_q2_75p_filtered_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 2020_q2_75p_filtered_2_pipeline pipeline RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_75p_filtered_2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_75p_filtered_2_pipeline` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_75p_filtered_2_pipeline_en_5.5.0_3.0_1725382478620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_75p_filtered_2_pipeline_en_5.5.0_3.0_1725382478620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2020_q2_75p_filtered_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2020_q2_75p_filtered_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_75p_filtered_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.2 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-75p-filtered_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-2020_q3_25p_filtered_en.md b/docs/_posts/ahmedlone127/2024-09-03-2020_q3_25p_filtered_en.md
new file mode 100644
index 00000000000000..2d0d9e0f6a4779
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-2020_q3_25p_filtered_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2020_q3_25p_filtered RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q3_25p_filtered
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q3_25p_filtered` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q3_25p_filtered_en_5.5.0_3.0_1725381967330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q3_25p_filtered_en_5.5.0_3.0_1725381967330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("2020_q3_25p_filtered","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("2020_q3_25p_filtered","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q3_25p_filtered|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q3-25p-filtered
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-2020_q3_25p_filtered_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-2020_q3_25p_filtered_pipeline_en.md
new file mode 100644
index 00000000000000..4a24247b0ad9e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-2020_q3_25p_filtered_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 2020_q3_25p_filtered_pipeline pipeline RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q3_25p_filtered_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q3_25p_filtered_pipeline` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q3_25p_filtered_pipeline_en_5.5.0_3.0_1725381991970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q3_25p_filtered_pipeline_en_5.5.0_3.0_1725381991970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2020_q3_25p_filtered_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2020_q3_25p_filtered_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q3_25p_filtered_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q3-25p-filtered
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-230215_lxcd_nmt_korean_english_v1_en.md b/docs/_posts/ahmedlone127/2024-09-03-230215_lxcd_nmt_korean_english_v1_en.md
new file mode 100644
index 00000000000000..b4de904daad0de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-230215_lxcd_nmt_korean_english_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 230215_lxcd_nmt_korean_english_v1 MarianTransformer from Kyungill
+author: John Snow Labs
+name: 230215_lxcd_nmt_korean_english_v1
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`230215_lxcd_nmt_korean_english_v1` is a English model originally trained by Kyungill.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/230215_lxcd_nmt_korean_english_v1_en_5.5.0_3.0_1725345699421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/230215_lxcd_nmt_korean_english_v1_en_5.5.0_3.0_1725345699421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("230215_lxcd_nmt_korean_english_v1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("230215_lxcd_nmt_korean_english_v1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|230215_lxcd_nmt_korean_english_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.3 MB|
+
+## References
+
+https://huggingface.co/Kyungill/230215-LXCD_NMT_ko-en_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-230215_lxcd_nmt_korean_english_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-230215_lxcd_nmt_korean_english_v1_pipeline_en.md
new file mode 100644
index 00000000000000..e685f57bc1bfea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-230215_lxcd_nmt_korean_english_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 230215_lxcd_nmt_korean_english_v1_pipeline pipeline MarianTransformer from Kyungill
+author: John Snow Labs
+name: 230215_lxcd_nmt_korean_english_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`230215_lxcd_nmt_korean_english_v1_pipeline` is a English model originally trained by Kyungill.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/230215_lxcd_nmt_korean_english_v1_pipeline_en_5.5.0_3.0_1725345726880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/230215_lxcd_nmt_korean_english_v1_pipeline_en_5.5.0_3.0_1725345726880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("230215_lxcd_nmt_korean_english_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("230215_lxcd_nmt_korean_english_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|230215_lxcd_nmt_korean_english_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|539.9 MB|
+
+## References
+
+https://huggingface.co/Kyungill/230215-LXCD_NMT_ko-en_v1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en.md b/docs/_posts/ahmedlone127/2024-09-03-2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en.md
new file mode 100644
index 00000000000000..11cdd259228a04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic XlmRoBertaEmbeddings from JEdward7777
+author: John Snow Labs
+name: 2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic` is a English model originally trained by JEdward7777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en_5.5.0_3.0_1725342643497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en_5.5.0_3.0_1725342643497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/JEdward7777/2-finetuned-xlm-r-masakhaner-swa-whole-word-phonetic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-accu_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-accu_0_pipeline_en.md
new file mode 100644
index 00000000000000..b9cac4b2f6aa19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-accu_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English accu_0_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: accu_0_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`accu_0_pipeline` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/accu_0_pipeline_en_5.5.0_3.0_1725369417308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/accu_0_pipeline_en_5.5.0_3.0_1725369417308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("accu_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("accu_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|accu_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Accu_0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-adn_setfit_model_en.md b/docs/_posts/ahmedlone127/2024-09-03-adn_setfit_model_en.md
new file mode 100644
index 00000000000000..e5d4a98f32245a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-adn_setfit_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English adn_setfit_model MPNetEmbeddings from Arnaudmkonan
+author: John Snow Labs
+name: adn_setfit_model
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adn_setfit_model` is a English model originally trained by Arnaudmkonan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adn_setfit_model_en_5.5.0_3.0_1725350629397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adn_setfit_model_en_5.5.0_3.0_1725350629397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("adn_setfit_model","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("adn_setfit_model","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adn_setfit_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Arnaudmkonan/adn-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-adn_setfit_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-adn_setfit_model_pipeline_en.md
new file mode 100644
index 00000000000000..56e31a85c62cdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-adn_setfit_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English adn_setfit_model_pipeline pipeline MPNetEmbeddings from Arnaudmkonan
+author: John Snow Labs
+name: adn_setfit_model_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adn_setfit_model_pipeline` is a English model originally trained by Arnaudmkonan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adn_setfit_model_pipeline_en_5.5.0_3.0_1725350649183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adn_setfit_model_pipeline_en_5.5.0_3.0_1725350649183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("adn_setfit_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adn_setfit_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adn_setfit_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Arnaudmkonan/adn-setfit-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_base_kinyarwanda_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_base_kinyarwanda_finetuned_en.md
new file mode 100644
index 00000000000000..22083d195504d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_base_kinyarwanda_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afro_xlmr_base_kinyarwanda_finetuned XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: afro_xlmr_base_kinyarwanda_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_base_kinyarwanda_finetuned` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_kinyarwanda_finetuned_en_5.5.0_3.0_1725399348335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_kinyarwanda_finetuned_en_5.5.0_3.0_1725399348335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_base_kinyarwanda_finetuned","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_base_kinyarwanda_finetuned","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_base_kinyarwanda_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-base-kinyarwanda-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_base_kinyarwanda_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_base_kinyarwanda_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..56e376a43a5eba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_base_kinyarwanda_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afro_xlmr_base_kinyarwanda_finetuned_pipeline pipeline XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: afro_xlmr_base_kinyarwanda_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_base_kinyarwanda_finetuned_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_kinyarwanda_finetuned_pipeline_en_5.5.0_3.0_1725399402100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_kinyarwanda_finetuned_pipeline_en_5.5.0_3.0_1725399402100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afro_xlmr_base_kinyarwanda_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afro_xlmr_base_kinyarwanda_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_base_kinyarwanda_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-base-kinyarwanda-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_mini_finetuned_kintweetsc_en.md b/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_mini_finetuned_kintweetsc_en.md
new file mode 100644
index 00000000000000..082fabc4d5c51c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_mini_finetuned_kintweetsc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afro_xlmr_mini_finetuned_kintweetsc XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: afro_xlmr_mini_finetuned_kintweetsc
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_mini_finetuned_kintweetsc` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_kintweetsc_en_5.5.0_3.0_1725399949239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_kintweetsc_en_5.5.0_3.0_1725399949239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_mini_finetuned_kintweetsc","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_mini_finetuned_kintweetsc","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_mini_finetuned_kintweetsc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|443.1 MB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-mini-finetuned-kintweetsC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_mini_finetuned_kintweetsc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_mini_finetuned_kintweetsc_pipeline_en.md
new file mode 100644
index 00000000000000..7618c354bb6adb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-afro_xlmr_mini_finetuned_kintweetsc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afro_xlmr_mini_finetuned_kintweetsc_pipeline pipeline XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: afro_xlmr_mini_finetuned_kintweetsc_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_mini_finetuned_kintweetsc_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_kintweetsc_pipeline_en_5.5.0_3.0_1725399972241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_kintweetsc_pipeline_en_5.5.0_3.0_1725399972241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afro_xlmr_mini_finetuned_kintweetsc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afro_xlmr_mini_finetuned_kintweetsc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_mini_finetuned_kintweetsc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|443.1 MB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-mini-finetuned-kintweetsC
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ag_nli_dets_sentence_similarity_v4_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-ag_nli_dets_sentence_similarity_v4_pipeline_xx.md
new file mode 100644
index 00000000000000..a113b815ae74a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ag_nli_dets_sentence_similarity_v4_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual ag_nli_dets_sentence_similarity_v4_pipeline pipeline CamemBertForSequenceClassification from abbasgolestani
+author: John Snow Labs
+name: ag_nli_dets_sentence_similarity_v4_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ag_nli_dets_sentence_similarity_v4_pipeline` is a Multilingual model originally trained by abbasgolestani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ag_nli_dets_sentence_similarity_v4_pipeline_xx_5.5.0_3.0_1725378146145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ag_nli_dets_sentence_similarity_v4_pipeline_xx_5.5.0_3.0_1725378146145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ag_nli_dets_sentence_similarity_v4_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ag_nli_dets_sentence_similarity_v4_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ag_nli_dets_sentence_similarity_v4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/abbasgolestani/ag-nli-DeTS-sentence-similarity-v4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ag_nli_dets_sentence_similarity_v4_xx.md b/docs/_posts/ahmedlone127/2024-09-03-ag_nli_dets_sentence_similarity_v4_xx.md
new file mode 100644
index 00000000000000..ab6dda7ea2434b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ag_nli_dets_sentence_similarity_v4_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual ag_nli_dets_sentence_similarity_v4 CamemBertForSequenceClassification from abbasgolestani
+author: John Snow Labs
+name: ag_nli_dets_sentence_similarity_v4
+date: 2024-09-03
+tags: [xx, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ag_nli_dets_sentence_similarity_v4` is a Multilingual model originally trained by abbasgolestani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ag_nli_dets_sentence_similarity_v4_xx_5.5.0_3.0_1725378078940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ag_nli_dets_sentence_similarity_v4_xx_5.5.0_3.0_1725378078940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("ag_nli_dets_sentence_similarity_v4","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("ag_nli_dets_sentence_similarity_v4", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ag_nli_dets_sentence_similarity_v4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/abbasgolestani/ag-nli-DeTS-sentence-similarity-v4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_alberta_en.md b/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_alberta_en.md
new file mode 100644
index 00000000000000..084ac71115b611
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_alberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ai_hackathon_alberta AlbertForSequenceClassification from Darshan03
+author: John Snow Labs
+name: ai_hackathon_alberta
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_hackathon_alberta` is a English model originally trained by Darshan03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_hackathon_alberta_en_5.5.0_3.0_1725385805227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_hackathon_alberta_en_5.5.0_3.0_1725385805227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("ai_hackathon_alberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("ai_hackathon_alberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_hackathon_alberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/Darshan03/AI-Hackathon-Alberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_alberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_alberta_pipeline_en.md
new file mode 100644
index 00000000000000..e6545bf5040f45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_alberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ai_hackathon_alberta_pipeline pipeline AlbertForSequenceClassification from Darshan03
+author: John Snow Labs
+name: ai_hackathon_alberta_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_hackathon_alberta_pipeline` is a English model originally trained by Darshan03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_hackathon_alberta_pipeline_en_5.5.0_3.0_1725385807618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_hackathon_alberta_pipeline_en_5.5.0_3.0_1725385807618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ai_hackathon_alberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_hackathon_alberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_hackathon_alberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/Darshan03/AI-Hackathon-Alberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..9131646ad8ab6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ai_hackathon_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ai_hackathon_distilbert_pipeline pipeline DistilBertForSequenceClassification from Darshan03
+author: John Snow Labs
+name: ai_hackathon_distilbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_hackathon_distilbert_pipeline` is a English model originally trained by Darshan03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_hackathon_distilbert_pipeline_en_5.5.0_3.0_1725330181370.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_hackathon_distilbert_pipeline_en_5.5.0_3.0_1725330181370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ai_hackathon_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_hackathon_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_hackathon_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Darshan03/AI-Hackathon-DistilBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-aigc_detector_env1_en.md b/docs/_posts/ahmedlone127/2024-09-03-aigc_detector_env1_en.md
new file mode 100644
index 00000000000000..479ed600142f97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-aigc_detector_env1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English aigc_detector_env1 RoBertaForSequenceClassification from yuchuantian
+author: John Snow Labs
+name: aigc_detector_env1
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aigc_detector_env1` is a English model originally trained by yuchuantian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aigc_detector_env1_en_5.5.0_3.0_1725337342904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aigc_detector_env1_en_5.5.0_3.0_1725337342904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("aigc_detector_env1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("aigc_detector_env1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aigc_detector_env1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|462.6 MB|
+
+## References
+
+https://huggingface.co/yuchuantian/AIGC_detector_env1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_k_fold_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_k_fold_2_pipeline_en.md
new file mode 100644
index 00000000000000..3fd294b24cf2ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_qa_2_k_fold_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English albert_base_qa_2_k_fold_2_pipeline pipeline AlbertForQuestionAnswering from mateiaass
+author: John Snow Labs
+name: albert_base_qa_2_k_fold_2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_2_k_fold_2_pipeline` is a English model originally trained by mateiaass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_2_pipeline_en_5.5.0_3.0_1725341908442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_2_k_fold_2_pipeline_en_5.5.0_3.0_1725341908442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_qa_2_k_fold_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_qa_2_k_fold_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_qa_2_k_fold_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/mateiaass/albert-base-qa-2-k-fold-2
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_v2_mrpc_textattack_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_v2_mrpc_textattack_en.md
new file mode 100644
index 00000000000000..a68241dc359d17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_v2_mrpc_textattack_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_mrpc_textattack AlbertForSequenceClassification from textattack
+author: John Snow Labs
+name: albert_base_v2_mrpc_textattack
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_mrpc_textattack` is a English model originally trained by textattack.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_mrpc_textattack_en_5.5.0_3.0_1725385916235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_mrpc_textattack_en_5.5.0_3.0_1725385916235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_base_v2_mrpc_textattack","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_base_v2_mrpc_textattack", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_mrpc_textattack|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/textattack/albert-base-v2-MRPC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-albert_base_v2_mrpc_textattack_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-albert_base_v2_mrpc_textattack_pipeline_en.md
new file mode 100644
index 00000000000000..4397cd01a6409a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-albert_base_v2_mrpc_textattack_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_v2_mrpc_textattack_pipeline pipeline AlbertForSequenceClassification from textattack
+author: John Snow Labs
+name: albert_base_v2_mrpc_textattack_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_mrpc_textattack_pipeline` is a English model originally trained by textattack.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_mrpc_textattack_pipeline_en_5.5.0_3.0_1725385918776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_mrpc_textattack_pipeline_en_5.5.0_3.0_1725385918776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_v2_mrpc_textattack_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_v2_mrpc_textattack_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_mrpc_textattack_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/textattack/albert-base-v2-MRPC
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_eclass_gart_labor_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_eclass_gart_labor_pipeline_en.md
new file mode 100644
index 00000000000000..e532bb312c295f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_eclass_gart_labor_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_eclass_gart_labor_pipeline pipeline MPNetEmbeddings from gart-labor
+author: John Snow Labs
+name: all_mpnet_base_v2_eclass_gart_labor_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_eclass_gart_labor_pipeline` is a English model originally trained by gart-labor.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_eclass_gart_labor_pipeline_en_5.5.0_3.0_1725350694555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_eclass_gart_labor_pipeline_en_5.5.0_3.0_1725350694555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_eclass_gart_labor_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_eclass_gart_labor_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_eclass_gart_labor_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/gart-labor/all-mpnet-base-v2-eclass
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3_en.md b/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3_en.md
new file mode 100644
index 00000000000000..d29de03703c8a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3 MPNetEmbeddings from luiz-and-robert-thesis
+author: John Snow Labs
+name: all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3` is a English model originally trained by luiz-and-robert-thesis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3_en_5.5.0_3.0_1725351024454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3_en_5.5.0_3.0_1725351024454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_lr_2e_7_margin_1_epoch_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/luiz-and-robert-thesis/all-mpnet-base-v2-lr-2e-7-margin-1-epoch-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_southern_sotho_out_sim_en.md b/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_southern_sotho_out_sim_en.md
new file mode 100644
index 00000000000000..6ed3f24971912b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_southern_sotho_out_sim_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_southern_sotho_out_sim MPNetEmbeddings from laiking
+author: John Snow Labs
+name: all_mpnet_base_v2_southern_sotho_out_sim
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_southern_sotho_out_sim` is a English model originally trained by laiking.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_southern_sotho_out_sim_en_5.5.0_3.0_1725350866895.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_southern_sotho_out_sim_en_5.5.0_3.0_1725350866895.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_southern_sotho_out_sim","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_southern_sotho_out_sim","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_southern_sotho_out_sim|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/laiking/all-mpnet-base-v2-st-out-sim
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_sts_juanignaciosolerno_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_sts_juanignaciosolerno_pipeline_en.md
new file mode 100644
index 00000000000000..4b1c3eefa44336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-all_mpnet_base_v2_sts_juanignaciosolerno_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_sts_juanignaciosolerno_pipeline pipeline MPNetEmbeddings from JuanIgnacioSolerno
+author: John Snow Labs
+name: all_mpnet_base_v2_sts_juanignaciosolerno_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_sts_juanignaciosolerno_pipeline` is a English model originally trained by JuanIgnacioSolerno.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_sts_juanignaciosolerno_pipeline_en_5.5.0_3.0_1725350271202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_sts_juanignaciosolerno_pipeline_en_5.5.0_3.0_1725350271202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_sts_juanignaciosolerno_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_sts_juanignaciosolerno_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_sts_juanignaciosolerno_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/JuanIgnacioSolerno/all-mpnet-base-v2-sts
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-amf_illoc_force_intent_recognition_en.md b/docs/_posts/ahmedlone127/2024-09-03-amf_illoc_force_intent_recognition_en.md
new file mode 100644
index 00000000000000..c1b96064a586ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-amf_illoc_force_intent_recognition_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English amf_illoc_force_intent_recognition RoBertaForSequenceClassification from Godfrey2712
+author: John Snow Labs
+name: amf_illoc_force_intent_recognition
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amf_illoc_force_intent_recognition` is a English model originally trained by Godfrey2712.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amf_illoc_force_intent_recognition_en_5.5.0_3.0_1725369021571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amf_illoc_force_intent_recognition_en_5.5.0_3.0_1725369021571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("amf_illoc_force_intent_recognition","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("amf_illoc_force_intent_recognition", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amf_illoc_force_intent_recognition|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Godfrey2712/amf_illoc_force_intent_recognition
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-amf_illoc_force_intent_recognition_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-amf_illoc_force_intent_recognition_pipeline_en.md
new file mode 100644
index 00000000000000..7404a5f3264169
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-amf_illoc_force_intent_recognition_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English amf_illoc_force_intent_recognition_pipeline pipeline RoBertaForSequenceClassification from Godfrey2712
+author: John Snow Labs
+name: amf_illoc_force_intent_recognition_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amf_illoc_force_intent_recognition_pipeline` is a English model originally trained by Godfrey2712.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amf_illoc_force_intent_recognition_pipeline_en_5.5.0_3.0_1725369117537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amf_illoc_force_intent_recognition_pipeline_en_5.5.0_3.0_1725369117537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("amf_illoc_force_intent_recognition_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("amf_illoc_force_intent_recognition_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amf_illoc_force_intent_recognition_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Godfrey2712/amf_illoc_force_intent_recognition
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_alignment_en.md b/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_alignment_en.md
new file mode 100644
index 00000000000000..15bc382b57ed85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_alignment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ancient_greek_to_1453_alignment XlmRoBertaEmbeddings from UGARIT
+author: John Snow Labs
+name: ancient_greek_to_1453_alignment
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ancient_greek_to_1453_alignment` is a English model originally trained by UGARIT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ancient_greek_to_1453_alignment_en_5.5.0_3.0_1725343639633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ancient_greek_to_1453_alignment_en_5.5.0_3.0_1725343639633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("ancient_greek_to_1453_alignment","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("ancient_greek_to_1453_alignment","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ancient_greek_to_1453_alignment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/UGARIT/grc-alignment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_ner_xlmr_en.md b/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_ner_xlmr_en.md
new file mode 100644
index 00000000000000..6b722d61c3aefc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_ner_xlmr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ancient_greek_to_1453_ner_xlmr XlmRoBertaForTokenClassification from UGARIT
+author: John Snow Labs
+name: ancient_greek_to_1453_ner_xlmr
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ancient_greek_to_1453_ner_xlmr` is a English model originally trained by UGARIT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ancient_greek_to_1453_ner_xlmr_en_5.5.0_3.0_1725372552872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ancient_greek_to_1453_ner_xlmr_en_5.5.0_3.0_1725372552872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("ancient_greek_to_1453_ner_xlmr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ancient_greek_to_1453_ner_xlmr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ancient_greek_to_1453_ner_xlmr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/UGARIT/grc-ner-xlmr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_ner_xlmr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_ner_xlmr_pipeline_en.md
new file mode 100644
index 00000000000000..87ee473e40dd1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ancient_greek_to_1453_ner_xlmr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ancient_greek_to_1453_ner_xlmr_pipeline pipeline XlmRoBertaForTokenClassification from UGARIT
+author: John Snow Labs
+name: ancient_greek_to_1453_ner_xlmr_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ancient_greek_to_1453_ner_xlmr_pipeline` is a English model originally trained by UGARIT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ancient_greek_to_1453_ner_xlmr_pipeline_en_5.5.0_3.0_1725372615429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ancient_greek_to_1453_ner_xlmr_pipeline_en_5.5.0_3.0_1725372615429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ancient_greek_to_1453_ner_xlmr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ancient_greek_to_1453_ner_xlmr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ancient_greek_to_1453_ner_xlmr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/UGARIT/grc-ner-xlmr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-angela_shuffle_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-angela_shuffle_test_pipeline_en.md
new file mode 100644
index 00000000000000..75013195ed90f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-angela_shuffle_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English angela_shuffle_test_pipeline pipeline XlmRoBertaForTokenClassification from azhang1212
+author: John Snow Labs
+name: angela_shuffle_test_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`angela_shuffle_test_pipeline` is a English model originally trained by azhang1212.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/angela_shuffle_test_pipeline_en_5.5.0_3.0_1725322085519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/angela_shuffle_test_pipeline_en_5.5.0_3.0_1725322085519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("angela_shuffle_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("angela_shuffle_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|angela_shuffle_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/azhang1212/angela_shuffle_test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-annual_report_translation_indonesian_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-annual_report_translation_indonesian_english_en.md
new file mode 100644
index 00000000000000..9c3d18550f4e72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-annual_report_translation_indonesian_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English annual_report_translation_indonesian_english MarianTransformer from wolfrage89
+author: John Snow Labs
+name: annual_report_translation_indonesian_english
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`annual_report_translation_indonesian_english` is a English model originally trained by wolfrage89.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/annual_report_translation_indonesian_english_en_5.5.0_3.0_1725346450128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/annual_report_translation_indonesian_english_en_5.5.0_3.0_1725346450128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("annual_report_translation_indonesian_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("annual_report_translation_indonesian_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|annual_report_translation_indonesian_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|480.1 MB|
+
+## References
+
+https://huggingface.co/wolfrage89/annual_report_translation_id_en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-annual_report_translation_indonesian_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-annual_report_translation_indonesian_english_pipeline_en.md
new file mode 100644
index 00000000000000..4b404c46783fdc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-annual_report_translation_indonesian_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English annual_report_translation_indonesian_english_pipeline pipeline MarianTransformer from wolfrage89
+author: John Snow Labs
+name: annual_report_translation_indonesian_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`annual_report_translation_indonesian_english_pipeline` is a English model originally trained by wolfrage89.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/annual_report_translation_indonesian_english_pipeline_en_5.5.0_3.0_1725346474559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/annual_report_translation_indonesian_english_pipeline_en_5.5.0_3.0_1725346474559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("annual_report_translation_indonesian_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("annual_report_translation_indonesian_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|annual_report_translation_indonesian_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|480.6 MB|
+
+## References
+
+https://huggingface.co/wolfrage89/annual_report_translation_id_en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-answer_equivalence_distilbert_zongxia_en.md b/docs/_posts/ahmedlone127/2024-09-03-answer_equivalence_distilbert_zongxia_en.md
new file mode 100644
index 00000000000000..dbe49fc1377950
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-answer_equivalence_distilbert_zongxia_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English answer_equivalence_distilbert_zongxia DistilBertForSequenceClassification from Zongxia
+author: John Snow Labs
+name: answer_equivalence_distilbert_zongxia
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_equivalence_distilbert_zongxia` is a English model originally trained by Zongxia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_equivalence_distilbert_zongxia_en_5.5.0_3.0_1725329994522.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_equivalence_distilbert_zongxia_en_5.5.0_3.0_1725329994522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("answer_equivalence_distilbert_zongxia","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("answer_equivalence_distilbert_zongxia", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|answer_equivalence_distilbert_zongxia|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Zongxia/answer_equivalence_distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-answer_equivalence_distilbert_zongxia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-answer_equivalence_distilbert_zongxia_pipeline_en.md
new file mode 100644
index 00000000000000..879b6a26adf608
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-answer_equivalence_distilbert_zongxia_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English answer_equivalence_distilbert_zongxia_pipeline pipeline DistilBertForSequenceClassification from Zongxia
+author: John Snow Labs
+name: answer_equivalence_distilbert_zongxia_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_equivalence_distilbert_zongxia_pipeline` is a English model originally trained by Zongxia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_equivalence_distilbert_zongxia_pipeline_en_5.5.0_3.0_1725330006926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_equivalence_distilbert_zongxia_pipeline_en_5.5.0_3.0_1725330006926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("answer_equivalence_distilbert_zongxia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("answer_equivalence_distilbert_zongxia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|answer_equivalence_distilbert_zongxia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Zongxia/answer_equivalence_distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-answer_finder_v1_l_multilingual_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-answer_finder_v1_l_multilingual_pipeline_xx.md
new file mode 100644
index 00000000000000..35690faba4820d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-answer_finder_v1_l_multilingual_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual answer_finder_v1_l_multilingual_pipeline pipeline BertForQuestionAnswering from sinequa
+author: John Snow Labs
+name: answer_finder_v1_l_multilingual_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_finder_v1_l_multilingual_pipeline` is a Multilingual model originally trained by sinequa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_finder_v1_l_multilingual_pipeline_xx_5.5.0_3.0_1725351815672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_finder_v1_l_multilingual_pipeline_xx_5.5.0_3.0_1725351815672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("answer_finder_v1_l_multilingual_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("answer_finder_v1_l_multilingual_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|answer_finder_v1_l_multilingual_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|464.4 MB|
+
+## References
+
+https://huggingface.co/sinequa/answer-finder-v1-L-multilingual
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-answer_finder_v1_l_multilingual_xx.md b/docs/_posts/ahmedlone127/2024-09-03-answer_finder_v1_l_multilingual_xx.md
new file mode 100644
index 00000000000000..f898d49bfd9321
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-answer_finder_v1_l_multilingual_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual answer_finder_v1_l_multilingual BertForQuestionAnswering from sinequa
+author: John Snow Labs
+name: answer_finder_v1_l_multilingual
+date: 2024-09-03
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_finder_v1_l_multilingual` is a Multilingual model originally trained by sinequa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_finder_v1_l_multilingual_xx_5.5.0_3.0_1725351792284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_finder_v1_l_multilingual_xx_5.5.0_3.0_1725351792284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("answer_finder_v1_l_multilingual","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("answer_finder_v1_l_multilingual", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|answer_finder_v1_l_multilingual|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|464.4 MB|
+
+## References
+
+https://huggingface.co/sinequa/answer-finder-v1-L-multilingual
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-antisemitism_model_jikeli_en.md b/docs/_posts/ahmedlone127/2024-09-03-antisemitism_model_jikeli_en.md
new file mode 100644
index 00000000000000..00bc7afb949eaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-antisemitism_model_jikeli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English antisemitism_model_jikeli DistilBertForSequenceClassification from mivry
+author: John Snow Labs
+name: antisemitism_model_jikeli
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`antisemitism_model_jikeli` is a English model originally trained by mivry.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/antisemitism_model_jikeli_en_5.5.0_3.0_1725330080547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/antisemitism_model_jikeli_en_5.5.0_3.0_1725330080547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("antisemitism_model_jikeli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("antisemitism_model_jikeli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|antisemitism_model_jikeli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mivry/antisemitism_model_jikeli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-antisemitism_model_jikeli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-antisemitism_model_jikeli_pipeline_en.md
new file mode 100644
index 00000000000000..17de6159ae2e25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-antisemitism_model_jikeli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English antisemitism_model_jikeli_pipeline pipeline DistilBertForSequenceClassification from mivry
+author: John Snow Labs
+name: antisemitism_model_jikeli_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`antisemitism_model_jikeli_pipeline` is a English model originally trained by mivry.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/antisemitism_model_jikeli_pipeline_en_5.5.0_3.0_1725330092502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/antisemitism_model_jikeli_pipeline_en_5.5.0_3.0_1725330092502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("antisemitism_model_jikeli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("antisemitism_model_jikeli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|antisemitism_model_jikeli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mivry/antisemitism_model_jikeli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-atbat_prediction_en.md b/docs/_posts/ahmedlone127/2024-09-03-atbat_prediction_en.md
new file mode 100644
index 00000000000000..2bdf92d2d4b05e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-atbat_prediction_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English atbat_prediction DistilBertForSequenceClassification from marklicata
+author: John Snow Labs
+name: atbat_prediction
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atbat_prediction` is a English model originally trained by marklicata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atbat_prediction_en_5.5.0_3.0_1725394128039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atbat_prediction_en_5.5.0_3.0_1725394128039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("atbat_prediction","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("atbat_prediction", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atbat_prediction|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/marklicata/atbat_prediction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-atbat_prediction_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-atbat_prediction_pipeline_en.md
new file mode 100644
index 00000000000000..c88bb549deb0c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-atbat_prediction_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English atbat_prediction_pipeline pipeline DistilBertForSequenceClassification from marklicata
+author: John Snow Labs
+name: atbat_prediction_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atbat_prediction_pipeline` is a English model originally trained by marklicata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atbat_prediction_pipeline_en_5.5.0_3.0_1725394141742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atbat_prediction_pipeline_en_5.5.0_3.0_1725394141742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("atbat_prediction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("atbat_prediction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atbat_prediction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/marklicata/atbat_prediction
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-autonlp_feedback1_479512837_en.md b/docs/_posts/ahmedlone127/2024-09-03-autonlp_feedback1_479512837_en.md
new file mode 100644
index 00000000000000..bf3ebfe9baba8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-autonlp_feedback1_479512837_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autonlp_feedback1_479512837 XlmRoBertaForSequenceClassification from Anamika
+author: John Snow Labs
+name: autonlp_feedback1_479512837
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autonlp_feedback1_479512837` is a English model originally trained by Anamika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autonlp_feedback1_479512837_en_5.5.0_3.0_1725396619864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autonlp_feedback1_479512837_en_5.5.0_3.0_1725396619864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("autonlp_feedback1_479512837","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("autonlp_feedback1_479512837", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autonlp_feedback1_479512837|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Anamika/autonlp-Feedback1-479512837
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-autonlp_feedback1_479512837_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-autonlp_feedback1_479512837_pipeline_en.md
new file mode 100644
index 00000000000000..46133f55b6db01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-autonlp_feedback1_479512837_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autonlp_feedback1_479512837_pipeline pipeline XlmRoBertaForSequenceClassification from Anamika
+author: John Snow Labs
+name: autonlp_feedback1_479512837_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autonlp_feedback1_479512837_pipeline` is a English model originally trained by Anamika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autonlp_feedback1_479512837_pipeline_en_5.5.0_3.0_1725396677732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autonlp_feedback1_479512837_pipeline_en_5.5.0_3.0_1725396677732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autonlp_feedback1_479512837_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autonlp_feedback1_479512837_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autonlp_feedback1_479512837_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Anamika/autonlp-Feedback1-479512837
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-autotrain_cekbert_44792112732_en.md b/docs/_posts/ahmedlone127/2024-09-03-autotrain_cekbert_44792112732_en.md
new file mode 100644
index 00000000000000..54a14aad0f5ff7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-autotrain_cekbert_44792112732_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English autotrain_cekbert_44792112732 BertForQuestionAnswering from reyhanAfri
+author: John Snow Labs
+name: autotrain_cekbert_44792112732
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_cekbert_44792112732` is a English model originally trained by reyhanAfri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_cekbert_44792112732_en_5.5.0_3.0_1725351492351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_cekbert_44792112732_en_5.5.0_3.0_1725351492351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("autotrain_cekbert_44792112732","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("autotrain_cekbert_44792112732", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_cekbert_44792112732|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|41.9 MB|
+
+## References
+
+https://huggingface.co/reyhanAfri/autotrain-cekbert-44792112732
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-autotrain_cekbert_44792112732_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-autotrain_cekbert_44792112732_pipeline_en.md
new file mode 100644
index 00000000000000..9b797e270554e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-autotrain_cekbert_44792112732_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_cekbert_44792112732_pipeline pipeline BertForQuestionAnswering from reyhanAfri
+author: John Snow Labs
+name: autotrain_cekbert_44792112732_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_cekbert_44792112732_pipeline` is a English model originally trained by reyhanAfri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_cekbert_44792112732_pipeline_en_5.5.0_3.0_1725351494665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_cekbert_44792112732_pipeline_en_5.5.0_3.0_1725351494665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_cekbert_44792112732_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_cekbert_44792112732_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_cekbert_44792112732_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|41.9 MB|
+
+## References
+
+https://huggingface.co/reyhanAfri/autotrain-cekbert-44792112732
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-autotrain_myowndata_training_en.md b/docs/_posts/ahmedlone127/2024-09-03-autotrain_myowndata_training_en.md
new file mode 100644
index 00000000000000..16c06ff2f3de0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-autotrain_myowndata_training_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_myowndata_training MPNetForSequenceClassification from nithya90tth
+author: John Snow Labs
+name: autotrain_myowndata_training
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_myowndata_training` is a English model originally trained by nithya90tth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_myowndata_training_en_5.5.0_3.0_1725386760755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_myowndata_training_en_5.5.0_3.0_1725386760755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("autotrain_myowndata_training","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("autotrain_myowndata_training", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_myowndata_training|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/nithya90tth/autotrain-myowndata-training
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_3196789879_en.md b/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_3196789879_en.md
new file mode 100644
index 00000000000000..978df2157a1313
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_3196789879_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_okr_iptal_3196789879 XlmRoBertaForSequenceClassification from ekincanozcelik
+author: John Snow Labs
+name: autotrain_okr_iptal_3196789879
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_3196789879` is a English model originally trained by ekincanozcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_3196789879_en_5.5.0_3.0_1725395665022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_3196789879_en_5.5.0_3.0_1725395665022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_3196789879","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_3196789879", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_okr_iptal_3196789879|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|777.0 MB|
+
+## References
+
+https://huggingface.co/ekincanozcelik/autotrain-okr_iptal-3196789879
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_v4_48282117445_en.md b/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_v4_48282117445_en.md
new file mode 100644
index 00000000000000..0dfb95ed30e5dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-autotrain_okr_iptal_v4_48282117445_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_okr_iptal_v4_48282117445 XlmRoBertaForSequenceClassification from ekincanozcelik
+author: John Snow Labs
+name: autotrain_okr_iptal_v4_48282117445
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_v4_48282117445` is a English model originally trained by ekincanozcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v4_48282117445_en_5.5.0_3.0_1725328886551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v4_48282117445_en_5.5.0_3.0_1725328886551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_v4_48282117445","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_v4_48282117445", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_okr_iptal_v4_48282117445|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|778.4 MB|
+
+## References
+
+https://huggingface.co/ekincanozcelik/autotrain-okr_iptal_v4-48282117445
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-baai_bge_large_english_v1_5_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-baai_bge_large_english_v1_5_fine_tuned_pipeline_en.md
new file mode 100644
index 00000000000000..4f86d1f6958a75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-baai_bge_large_english_v1_5_fine_tuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English baai_bge_large_english_v1_5_fine_tuned_pipeline pipeline BGEEmbeddings from rjnClarke
+author: John Snow Labs
+name: baai_bge_large_english_v1_5_fine_tuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_large_english_v1_5_fine_tuned_pipeline` is a English model originally trained by rjnClarke.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_pipeline_en_5.5.0_3.0_1725357314932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_pipeline_en_5.5.0_3.0_1725357314932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("baai_bge_large_english_v1_5_fine_tuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("baai_bge_large_english_v1_5_fine_tuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_large_english_v1_5_fine_tuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/rjnClarke/BAAI-bge-large-en-v1.5-fine-tuned
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-03-babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad_en.md
new file mode 100644
index 00000000000000..27b836e1f2ffaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad` is a English model originally trained by lielbin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad_en_5.5.0_3.0_1725370409243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad_en_5.5.0_3.0_1725370409243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_wikipedia_french1_25m_wikipedia1_1_25m_with_masking_seed3_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|32.0 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa-wikipedia_french1.25M_wikipedia1_1.25M-with-Masking-seed3-finetuned-SQuAD
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bangla_writting_style_correction_model_en.md b/docs/_posts/ahmedlone127/2024-09-03-bangla_writting_style_correction_model_en.md
new file mode 100644
index 00000000000000..e35b90caac953c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bangla_writting_style_correction_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bangla_writting_style_correction_model MarianTransformer from shahidul034
+author: John Snow Labs
+name: bangla_writting_style_correction_model
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bangla_writting_style_correction_model` is a English model originally trained by shahidul034.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bangla_writting_style_correction_model_en_5.5.0_3.0_1725403760800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bangla_writting_style_correction_model_en_5.5.0_3.0_1725403760800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("bangla_writting_style_correction_model","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("bangla_writting_style_correction_model","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bangla_writting_style_correction_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|530.5 MB|
+
+## References
+
+https://huggingface.co/shahidul034/Bangla_writting_style_correction_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bangla_writting_style_correction_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bangla_writting_style_correction_model_pipeline_en.md
new file mode 100644
index 00000000000000..1720b3393b44af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bangla_writting_style_correction_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bangla_writting_style_correction_model_pipeline pipeline MarianTransformer from shahidul034
+author: John Snow Labs
+name: bangla_writting_style_correction_model_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bangla_writting_style_correction_model_pipeline` is a English model originally trained by shahidul034.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bangla_writting_style_correction_model_pipeline_en_5.5.0_3.0_1725403793906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bangla_writting_style_correction_model_pipeline_en_5.5.0_3.0_1725403793906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bangla_writting_style_correction_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bangla_writting_style_correction_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bangla_writting_style_correction_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|531.0 MB|
+
+## References
+
+https://huggingface.co/shahidul034/Bangla_writting_style_correction_model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-batchalltripletloss_job_title_en.md b/docs/_posts/ahmedlone127/2024-09-03-batchalltripletloss_job_title_en.md
new file mode 100644
index 00000000000000..9e84b6c92b98a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-batchalltripletloss_job_title_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English batchalltripletloss_job_title MPNetEmbeddings from marianodo
+author: John Snow Labs
+name: batchalltripletloss_job_title
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batchalltripletloss_job_title` is a English model originally trained by marianodo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batchalltripletloss_job_title_en_5.5.0_3.0_1725350892033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batchalltripletloss_job_title_en_5.5.0_3.0_1725350892033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("batchalltripletloss_job_title","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("batchalltripletloss_job_title","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batchalltripletloss_job_title|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/marianodo/BatchAllTripletLoss-job-title
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-batchalltripletloss_job_title_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-batchalltripletloss_job_title_pipeline_en.md
new file mode 100644
index 00000000000000..95a3eeef653d94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-batchalltripletloss_job_title_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batchalltripletloss_job_title_pipeline pipeline MPNetEmbeddings from marianodo
+author: John Snow Labs
+name: batchalltripletloss_job_title_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batchalltripletloss_job_title_pipeline` is a English model originally trained by marianodo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batchalltripletloss_job_title_pipeline_en_5.5.0_3.0_1725350912935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batchalltripletloss_job_title_pipeline_en_5.5.0_3.0_1725350912935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batchalltripletloss_job_title_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batchalltripletloss_job_title_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batchalltripletloss_job_title_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/marianodo/BatchAllTripletLoss-job-title
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bengali_tonga_tonga_islands_english_translation_bn.md b/docs/_posts/ahmedlone127/2024-09-03-bengali_tonga_tonga_islands_english_translation_bn.md
new file mode 100644
index 00000000000000..d8c98e35182ac6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bengali_tonga_tonga_islands_english_translation_bn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Bengali bengali_tonga_tonga_islands_english_translation MarianTransformer from shihab17
+author: John Snow Labs
+name: bengali_tonga_tonga_islands_english_translation
+date: 2024-09-03
+tags: [bn, open_source, onnx, translation, marian]
+task: Translation
+language: bn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bengali_tonga_tonga_islands_english_translation` is a Bengali model originally trained by shihab17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bengali_tonga_tonga_islands_english_translation_bn_5.5.0_3.0_1725404122875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bengali_tonga_tonga_islands_english_translation_bn_5.5.0_3.0_1725404122875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("bengali_tonga_tonga_islands_english_translation","bn") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("bengali_tonga_tonga_islands_english_translation","bn") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bengali_tonga_tonga_islands_english_translation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|bn|
+|Size:|532.6 MB|
+
+## References
+
+https://huggingface.co/shihab17/bn-to-en-translation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bengali_tonga_tonga_islands_english_translation_pipeline_bn.md b/docs/_posts/ahmedlone127/2024-09-03-bengali_tonga_tonga_islands_english_translation_pipeline_bn.md
new file mode 100644
index 00000000000000..20ab82ff081b77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bengali_tonga_tonga_islands_english_translation_pipeline_bn.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Bengali bengali_tonga_tonga_islands_english_translation_pipeline pipeline MarianTransformer from shihab17
+author: John Snow Labs
+name: bengali_tonga_tonga_islands_english_translation_pipeline
+date: 2024-09-03
+tags: [bn, open_source, pipeline, onnx]
+task: Translation
+language: bn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bengali_tonga_tonga_islands_english_translation_pipeline` is a Bengali model originally trained by shihab17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bengali_tonga_tonga_islands_english_translation_pipeline_bn_5.5.0_3.0_1725404151820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bengali_tonga_tonga_islands_english_translation_pipeline_bn_5.5.0_3.0_1725404151820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bengali_tonga_tonga_islands_english_translation_pipeline", lang = "bn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bengali_tonga_tonga_islands_english_translation_pipeline", lang = "bn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bengali_tonga_tonga_islands_english_translation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bn|
+|Size:|533.1 MB|
+
+## References
+
+https://huggingface.co/shihab17/bn-to-en-translation
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bernice_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-bernice_pipeline_xx.md
new file mode 100644
index 00000000000000..2ec6d8f62ca56e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bernice_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual bernice_pipeline pipeline XlmRoBertaEmbeddings from jhu-clsp
+author: John Snow Labs
+name: bernice_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bernice_pipeline` is a Multilingual model originally trained by jhu-clsp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bernice_pipeline_xx_5.5.0_3.0_1725391193898.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bernice_pipeline_xx_5.5.0_3.0_1725391193898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bernice_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bernice_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bernice_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|654.7 MB|
+
+## References
+
+https://huggingface.co/jhu-clsp/bernice
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bernice_xx.md b/docs/_posts/ahmedlone127/2024-09-03-bernice_xx.md
new file mode 100644
index 00000000000000..ed36752f3e638f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bernice_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual bernice XlmRoBertaEmbeddings from jhu-clsp
+author: John Snow Labs
+name: bernice
+date: 2024-09-03
+tags: [xx, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bernice` is a Multilingual model originally trained by jhu-clsp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bernice_xx_5.5.0_3.0_1725390992156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bernice_xx_5.5.0_3.0_1725390992156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("bernice","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("bernice","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bernice|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|xx|
+|Size:|654.7 MB|
+
+## References
+
+https://huggingface.co/jhu-clsp/bernice
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_base_cased_google_bert_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_base_cased_google_bert_en.md
new file mode 100644
index 00000000000000..d2f61d88d65194
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_base_cased_google_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_google_bert BertEmbeddings from google-bert
+author: John Snow Labs
+name: bert_base_cased_google_bert
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_google_bert` is a English model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_google_bert_en_5.5.0_3.0_1725407119569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_google_bert_en_5.5.0_3.0_1725407119569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_google_bert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_google_bert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_google_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_base_cased_google_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_base_cased_google_bert_pipeline_en.md
new file mode 100644
index 00000000000000..87853cf37143d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_base_cased_google_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_google_bert_pipeline pipeline BertEmbeddings from google-bert
+author: John Snow Labs
+name: bert_base_cased_google_bert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_google_bert_pipeline` is a English model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_google_bert_pipeline_en_5.5.0_3.0_1725407141671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_google_bert_pipeline_en_5.5.0_3.0_1725407141671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_google_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_google_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_google_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_base_german_cased_de.md b/docs/_posts/ahmedlone127/2024-09-03-bert_base_german_cased_de.md
new file mode 100644
index 00000000000000..6e2836fa8b7de9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_base_german_cased_de.md
@@ -0,0 +1,80 @@
+---
+layout: model
+title: German BERT Base Cased Model
+author: John Snow Labs
+name: bert_base_german_cased
+date: 2024-09-03
+tags: [open_source, embeddings, bert, german, de, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+The source data for the model consists of a recent Wikipedia dump, EU Bookshop corpus, Open Subtitles, CommonCrawl, ParaCrawl and News Crawl. This results in a dataset with a size of 16GB and 2,350,234,427 tokens. The model is trained with an initial sequence length of 512 subwords and was performed for 1.5M steps.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_de_5.5.0_3.0_1725407036679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_de_5.5.0_3.0_1725407036679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+embeddings = BertEmbeddings.pretrained("bert_base_german_cased", "de") \
+.setInputCols("sentence", "token") \
+.setOutputCol("embeddings")
+nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, embeddings])
+```
+```scala
+val embeddings = BertEmbeddings.pretrained("bert_base_german_cased", "de")
+.setInputCols("sentence", "token")
+.setOutputCol("embeddings")
+val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings))
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.embed.bert").predict("""Put your text here.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|de|
+|Size:|406.9 MB|
+
+## Benchmarking
+
+```bash
+
+For results on downstream tasks like NER or PoS tagging, please refer to
+[this repository](https://github.com/stefan-it/fine-tuned-berts-seq).
+```
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_base_german_cased_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-bert_base_german_cased_pipeline_de.md
new file mode 100644
index 00000000000000..4256a5ba104e93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_base_german_cased_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German bert_base_german_cased_pipeline pipeline BertEmbeddings from google-bert
+author: John Snow Labs
+name: bert_base_german_cased_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_pipeline` is a German model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_pipeline_de_5.5.0_3.0_1725407061767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_pipeline_de_5.5.0_3.0_1725407061767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_german_cased_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_german_cased_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-german-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_base_smiles_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_base_smiles_en.md
new file mode 100644
index 00000000000000..d22548f89e18d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_base_smiles_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_smiles BertEmbeddings from unikei
+author: John Snow Labs
+name: bert_base_smiles
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_smiles` is a English model originally trained by unikei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_smiles_en_5.5.0_3.0_1725407006019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_smiles_en_5.5.0_3.0_1725407006019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_smiles","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_smiles","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_smiles|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.3 MB|
+
+## References
+
+https://huggingface.co/unikei/bert-base-smiles
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_base_smiles_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_base_smiles_pipeline_en.md
new file mode 100644
index 00000000000000..76041d13b342a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_base_smiles_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_smiles_pipeline pipeline BertEmbeddings from unikei
+author: John Snow Labs
+name: bert_base_smiles_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_smiles_pipeline` is a English model originally trained by unikei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_smiles_pipeline_en_5.5.0_3.0_1725407028485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_smiles_pipeline_en_5.5.0_3.0_1725407028485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_smiles_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_smiles_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_smiles_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.3 MB|
+
+## References
+
+https://huggingface.co/unikei/bert-base-smiles
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_base_uncased_finetuned_squad_frozen_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_base_uncased_finetuned_squad_frozen_v1_pipeline_en.md
new file mode 100644
index 00000000000000..736ef7ce779e12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_base_uncased_finetuned_squad_frozen_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_frozen_v1_pipeline pipeline BertForQuestionAnswering from ericRosello
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_frozen_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_frozen_v1_pipeline` is a English model originally trained by ericRosello.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_frozen_v1_pipeline_en_5.5.0_3.0_1725352306253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_frozen_v1_pipeline_en_5.5.0_3.0_1725352306253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_squad_frozen_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_squad_frozen_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_frozen_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/ericRosello/bert-base-uncased-finetuned-squad-frozen-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_embeddings_legalbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_embeddings_legalbert_en.md
new file mode 100644
index 00000000000000..63e681d71b3f49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_embeddings_legalbert_en.md
@@ -0,0 +1,89 @@
+---
+layout: model
+title: English Legal BERT Embedding  Cased model
+author: John Snow Labs
+name: bert_embeddings_legalbert
+date: 2024-09-03
+tags: [en, open_source, embeddings, bert, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BERT Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `legalbert` is a English model originally trained by `zlucia`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_embeddings_legalbert_en_5.5.0_3.0_1725406768549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_embeddings_legalbert_en_5.5.0_3.0_1725406768549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+  
+embeddings = BertEmbeddings.pretrained("bert_embeddings_legalbert","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("embeddings")
+    
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.embed.legalbert.legal.by_zlucia").predict("""I love Spark NLP""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_embeddings_legalbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+References
+
+- https://huggingface.co/zlucia/legalbert
+- https://case.law/
+- https://arxiv.org/abs/2104.08671
+- https://github.com/reglab/casehold
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_embeddings_legalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_embeddings_legalbert_pipeline_en.md
new file mode 100644
index 00000000000000..803c665e10a1e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_embeddings_legalbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_embeddings_legalbert_pipeline pipeline BertEmbeddings from zlucia
+author: John Snow Labs
+name: bert_embeddings_legalbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_embeddings_legalbert_pipeline` is a English model originally trained by zlucia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_embeddings_legalbert_pipeline_en_5.5.0_3.0_1725406790199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_embeddings_legalbert_pipeline_en_5.5.0_3.0_1725406790199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_embeddings_legalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_embeddings_legalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_embeddings_legalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/zlucia/legalbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_finetuned_squad_min_seong_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_finetuned_squad_min_seong_en.md
new file mode 100644
index 00000000000000..b40e2a2cc5da6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_finetuned_squad_min_seong_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_min_seong BertForQuestionAnswering from min-seong
+author: John Snow Labs
+name: bert_finetuned_squad_min_seong
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_min_seong` is a English model originally trained by min-seong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_min_seong_en_5.5.0_3.0_1725351917700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_min_seong_en_5.5.0_3.0_1725351917700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_min_seong","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_min_seong", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_min_seong|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/min-seong/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_finetuned_squad_min_seong_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_finetuned_squad_min_seong_pipeline_en.md
new file mode 100644
index 00000000000000..b4e4d7243b76f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_finetuned_squad_min_seong_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_min_seong_pipeline pipeline BertForQuestionAnswering from min-seong
+author: John Snow Labs
+name: bert_finetuned_squad_min_seong_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_min_seong_pipeline` is a English model originally trained by min-seong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_min_seong_pipeline_en_5.5.0_3.0_1725351937944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_min_seong_pipeline_en_5.5.0_3.0_1725351937944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_min_seong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_min_seong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_min_seong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/min-seong/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_qa_twmkn9_bert_base_uncased_squad2_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_qa_twmkn9_bert_base_uncased_squad2_en.md
new file mode 100644
index 00000000000000..f6ef48948158b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_qa_twmkn9_bert_base_uncased_squad2_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from twmkn9)
+author: John Snow Labs
+name: bert_qa_twmkn9_bert_base_uncased_squad2
+date: 2024-09-03
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-squad2` is a English model orginally trained by `twmkn9`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_twmkn9_bert_base_uncased_squad2_en_5.5.0_3.0_1725352016296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_twmkn9_bert_base_uncased_squad2_en_5.5.0_3.0_1725352016296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_twmkn9_bert_base_uncased_squad2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_twmkn9_bert_base_uncased_squad2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert.base_uncased.by_twmkn9").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_twmkn9_bert_base_uncased_squad2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/twmkn9/bert-base-uncased-squad2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_qa_twmkn9_bert_base_uncased_squad2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_qa_twmkn9_bert_base_uncased_squad2_pipeline_en.md
new file mode 100644
index 00000000000000..f952b0ad16b143
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_qa_twmkn9_bert_base_uncased_squad2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_qa_twmkn9_bert_base_uncased_squad2_pipeline pipeline BertForQuestionAnswering from twmkn9
+author: John Snow Labs
+name: bert_qa_twmkn9_bert_base_uncased_squad2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_twmkn9_bert_base_uncased_squad2_pipeline` is a English model originally trained by twmkn9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_twmkn9_bert_base_uncased_squad2_pipeline_en_5.5.0_3.0_1725352036921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_twmkn9_bert_base_uncased_squad2_pipeline_en_5.5.0_3.0_1725352036921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_qa_twmkn9_bert_base_uncased_squad2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_qa_twmkn9_bert_base_uncased_squad2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_twmkn9_bert_base_uncased_squad2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/twmkn9/bert-base-uncased-squad2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_text_classification_car_evaluation_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_text_classification_car_evaluation_en.md
new file mode 100644
index 00000000000000..705049251103c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_text_classification_car_evaluation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_text_classification_car_evaluation DistilBertForSequenceClassification from Henriquee
+author: John Snow Labs
+name: bert_text_classification_car_evaluation
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_text_classification_car_evaluation` is a English model originally trained by Henriquee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_text_classification_car_evaluation_en_5.5.0_3.0_1725394498948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_text_classification_car_evaluation_en_5.5.0_3.0_1725394498948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_text_classification_car_evaluation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_text_classification_car_evaluation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_text_classification_car_evaluation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Henriquee/bert-text-classification-car-evaluation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_text_classification_car_evaluation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_text_classification_car_evaluation_pipeline_en.md
new file mode 100644
index 00000000000000..c06f9ad083940d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_text_classification_car_evaluation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_text_classification_car_evaluation_pipeline pipeline DistilBertForSequenceClassification from Henriquee
+author: John Snow Labs
+name: bert_text_classification_car_evaluation_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_text_classification_car_evaluation_pipeline` is a English model originally trained by Henriquee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_text_classification_car_evaluation_pipeline_en_5.5.0_3.0_1725394512618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_text_classification_car_evaluation_pipeline_en_5.5.0_3.0_1725394512618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_text_classification_car_evaluation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_text_classification_car_evaluation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_text_classification_car_evaluation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Henriquee/bert-text-classification-car-evaluation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_tiny_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_tiny_uncased_en.md
new file mode 100644
index 00000000000000..cb83ef7627282a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_tiny_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_tiny_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_tiny_uncased
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_uncased_en_5.5.0_3.0_1725406953503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_uncased_en_5.5.0_3.0_1725406953503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_tiny_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_tiny_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-tiny-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bert_tiny_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bert_tiny_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..f9c4a810c7ab5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bert_tiny_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_tiny_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_tiny_uncased_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_uncased_pipeline_en_5.5.0_3.0_1725406954882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_uncased_pipeline_en_5.5.0_3.0_1725406954882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tiny_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tiny_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-tiny-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bertin_base_stepwise_es.md b/docs/_posts/ahmedlone127/2024-09-03-bertin_base_stepwise_es.md
new file mode 100644
index 00000000000000..b2b55f797b1f7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bertin_base_stepwise_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish bertin_base_stepwise RoBertaEmbeddings from bertin-project
+author: John Snow Labs
+name: bertin_base_stepwise
+date: 2024-09-03
+tags: [es, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertin_base_stepwise` is a Castilian, Spanish model originally trained by bertin-project.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertin_base_stepwise_es_5.5.0_3.0_1725381905974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertin_base_stepwise_es_5.5.0_3.0_1725381905974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("bertin_base_stepwise","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("bertin_base_stepwise","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertin_base_stepwise|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|es|
+|Size:|231.8 MB|
+
+## References
+
+https://huggingface.co/bertin-project/bertin-base-stepwise
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bertin_base_stepwise_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-bertin_base_stepwise_pipeline_es.md
new file mode 100644
index 00000000000000..d5274c6e9f5088
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bertin_base_stepwise_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish bertin_base_stepwise_pipeline pipeline RoBertaEmbeddings from bertin-project
+author: John Snow Labs
+name: bertin_base_stepwise_pipeline
+date: 2024-09-03
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertin_base_stepwise_pipeline` is a Castilian, Spanish model originally trained by bertin-project.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertin_base_stepwise_pipeline_es_5.5.0_3.0_1725381988218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertin_base_stepwise_pipeline_es_5.5.0_3.0_1725381988218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertin_base_stepwise_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertin_base_stepwise_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertin_base_stepwise_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|231.8 MB|
+
+## References
+
+https://huggingface.co/bertin-project/bertin-base-stepwise
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bertreach_ga.md b/docs/_posts/ahmedlone127/2024-09-03-bertreach_ga.md
new file mode 100644
index 00000000000000..0d7e69f2614169
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bertreach_ga.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Irish bertreach RoBertaEmbeddings from jimregan
+author: John Snow Labs
+name: bertreach
+date: 2024-09-03
+tags: [ga, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: ga
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertreach` is a Irish model originally trained by jimregan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertreach_ga_5.5.0_3.0_1725381823926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertreach_ga_5.5.0_3.0_1725381823926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("bertreach","ga") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("bertreach","ga") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertreach|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|ga|
+|Size:|311.5 MB|
+
+## References
+
+https://huggingface.co/jimregan/BERTreach
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bertreach_pipeline_ga.md b/docs/_posts/ahmedlone127/2024-09-03-bertreach_pipeline_ga.md
new file mode 100644
index 00000000000000..833eca91ce0c4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bertreach_pipeline_ga.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Irish bertreach_pipeline pipeline RoBertaEmbeddings from jimregan
+author: John Snow Labs
+name: bertreach_pipeline
+date: 2024-09-03
+tags: [ga, open_source, pipeline, onnx]
+task: Embeddings
+language: ga
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertreach_pipeline` is a Irish model originally trained by jimregan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertreach_pipeline_ga_5.5.0_3.0_1725381840933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertreach_pipeline_ga_5.5.0_3.0_1725381840933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertreach_pipeline", lang = "ga")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertreach_pipeline", lang = "ga")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertreach_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ga|
+|Size:|311.6 MB|
+
+## References
+
+https://huggingface.co/jimregan/BERTreach
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_all_nli_triplet_inrealm_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_all_nli_triplet_inrealm_en.md
new file mode 100644
index 00000000000000..17ce8f820e4bfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_all_nli_triplet_inrealm_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_all_nli_triplet_inrealm BGEEmbeddings from inrealm
+author: John Snow Labs
+name: bge_base_all_nli_triplet_inrealm
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_all_nli_triplet_inrealm` is a English model originally trained by inrealm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_all_nli_triplet_inrealm_en_5.5.0_3.0_1725357027726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_all_nli_triplet_inrealm_en_5.5.0_3.0_1725357027726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_all_nli_triplet_inrealm","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_all_nli_triplet_inrealm","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_all_nli_triplet_inrealm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|110.0 MB|
+
+## References
+
+https://huggingface.co/inrealm/bge-base-all-nli-triplet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_all_nli_triplet_inrealm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_all_nli_triplet_inrealm_pipeline_en.md
new file mode 100644
index 00000000000000..f55a48de0a07d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_all_nli_triplet_inrealm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_all_nli_triplet_inrealm_pipeline pipeline BGEEmbeddings from inrealm
+author: John Snow Labs
+name: bge_base_all_nli_triplet_inrealm_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_all_nli_triplet_inrealm_pipeline` is a English model originally trained by inrealm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_all_nli_triplet_inrealm_pipeline_en_5.5.0_3.0_1725357040679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_all_nli_triplet_inrealm_pipeline_en_5.5.0_3.0_1725357040679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_all_nli_triplet_inrealm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_all_nli_triplet_inrealm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_all_nli_triplet_inrealm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|110.0 MB|
+
+## References
+
+https://huggingface.co/inrealm/bge-base-all-nli-triplet
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_arabic_v1_5_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_arabic_v1_5_finetuned_en.md
new file mode 100644
index 00000000000000..9f34110113c6a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_arabic_v1_5_finetuned_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_arabic_v1_5_finetuned BGEEmbeddings from AhmedBadawy11
+author: John Snow Labs
+name: bge_base_arabic_v1_5_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_arabic_v1_5_finetuned` is a English model originally trained by AhmedBadawy11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_arabic_v1_5_finetuned_en_5.5.0_3.0_1725356612268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_arabic_v1_5_finetuned_en_5.5.0_3.0_1725356612268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_arabic_v1_5_finetuned","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_arabic_v1_5_finetuned","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_arabic_v1_5_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|380.7 MB|
+
+## References
+
+https://huggingface.co/AhmedBadawy11/bge-base-ar-v1.5-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_arabic_v1_5_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_arabic_v1_5_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..6e408252d14097
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_arabic_v1_5_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_arabic_v1_5_finetuned_pipeline pipeline BGEEmbeddings from AhmedBadawy11
+author: John Snow Labs
+name: bge_base_arabic_v1_5_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_arabic_v1_5_finetuned_pipeline` is a English model originally trained by AhmedBadawy11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_arabic_v1_5_finetuned_pipeline_en_5.5.0_3.0_1725356636193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_arabic_v1_5_finetuned_pipeline_en_5.5.0_3.0_1725356636193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_arabic_v1_5_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_arabic_v1_5_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_arabic_v1_5_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|380.7 MB|
+
+## References
+
+https://huggingface.co/AhmedBadawy11/bge-base-ar-v1.5-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_citi_dataset_detailed_6k_0_5k_e2_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_citi_dataset_detailed_6k_0_5k_e2_en.md
new file mode 100644
index 00000000000000..7cfcf65b6f5dc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_citi_dataset_detailed_6k_0_5k_e2_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_citi_dataset_detailed_6k_0_5k_e2 BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_citi_dataset_detailed_6k_0_5k_e2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_citi_dataset_detailed_6k_0_5k_e2` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_detailed_6k_0_5k_e2_en_5.5.0_3.0_1725356383015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_detailed_6k_0_5k_e2_en_5.5.0_3.0_1725356383015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_citi_dataset_detailed_6k_0_5k_e2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_citi_dataset_detailed_6k_0_5k_e2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_citi_dataset_detailed_6k_0_5k_e2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|390.7 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-citi-dataset-detailed-6k-0_5k-e2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline_en.md
new file mode 100644
index 00000000000000..9492d3359b2c32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline pipeline BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline_en_5.5.0_3.0_1725356410379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline_en_5.5.0_3.0_1725356410379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_citi_dataset_detailed_6k_0_5k_e2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|390.7 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-citi-dataset-detailed-6k-0_5k-e2
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_climate_fever_dataset_10k_2k_v1_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_climate_fever_dataset_10k_2k_v1_en.md
new file mode 100644
index 00000000000000..a9f6229fddd2c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_climate_fever_dataset_10k_2k_v1_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_climate_fever_dataset_10k_2k_v1 BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_climate_fever_dataset_10k_2k_v1
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_climate_fever_dataset_10k_2k_v1` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_climate_fever_dataset_10k_2k_v1_en_5.5.0_3.0_1725356377197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_climate_fever_dataset_10k_2k_v1_en_5.5.0_3.0_1725356377197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_climate_fever_dataset_10k_2k_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_climate_fever_dataset_10k_2k_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_climate_fever_dataset_10k_2k_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-climate_fever-dataset-10k-2k-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_climate_fever_dataset_10k_2k_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_climate_fever_dataset_10k_2k_v1_pipeline_en.md
new file mode 100644
index 00000000000000..054b4f7f64bff3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_climate_fever_dataset_10k_2k_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_climate_fever_dataset_10k_2k_v1_pipeline pipeline BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_climate_fever_dataset_10k_2k_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_climate_fever_dataset_10k_2k_v1_pipeline` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_climate_fever_dataset_10k_2k_v1_pipeline_en_5.5.0_3.0_1725356399411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_climate_fever_dataset_10k_2k_v1_pipeline_en_5.5.0_3.0_1725356399411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_climate_fever_dataset_10k_2k_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_climate_fever_dataset_10k_2k_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_climate_fever_dataset_10k_2k_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-climate_fever-dataset-10k-2k-v1
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_cristuf_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_cristuf_en.md
new file mode 100644
index 00000000000000..3dc406018105b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_cristuf_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_cristuf BGEEmbeddings from cristuf
+author: John Snow Labs
+name: bge_base_financial_matryoshka_cristuf
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_cristuf` is a English model originally trained by cristuf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_cristuf_en_5.5.0_3.0_1725356931406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_cristuf_en_5.5.0_3.0_1725356931406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_cristuf","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_cristuf","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_cristuf|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.0 MB|
+
+## References
+
+https://huggingface.co/cristuf/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_cristuf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_cristuf_pipeline_en.md
new file mode 100644
index 00000000000000..ff073f593230db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_cristuf_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_cristuf_pipeline pipeline BGEEmbeddings from cristuf
+author: John Snow Labs
+name: bge_base_financial_matryoshka_cristuf_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_cristuf_pipeline` is a English model originally trained by cristuf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_cristuf_pipeline_en_5.5.0_3.0_1725356960509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_cristuf_pipeline_en_5.5.0_3.0_1725356960509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_cristuf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_cristuf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_cristuf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.0 MB|
+
+## References
+
+https://huggingface.co/cristuf/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_dustyatx_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_dustyatx_pipeline_en.md
new file mode 100644
index 00000000000000..b268897b698130
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_dustyatx_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_dustyatx_pipeline pipeline BGEEmbeddings from dustyatx
+author: John Snow Labs
+name: bge_base_financial_matryoshka_dustyatx_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_dustyatx_pipeline` is a English model originally trained by dustyatx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_dustyatx_pipeline_en_5.5.0_3.0_1725356414116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_dustyatx_pipeline_en_5.5.0_3.0_1725356414116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_dustyatx_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_dustyatx_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_dustyatx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/dustyatx/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_rubyando59_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_rubyando59_en.md
new file mode 100644
index 00000000000000..59d31d238d63b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_rubyando59_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_rubyando59 BGEEmbeddings from Rubyando59
+author: John Snow Labs
+name: bge_base_financial_matryoshka_rubyando59
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_rubyando59` is a English model originally trained by Rubyando59.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_rubyando59_en_5.5.0_3.0_1725356980800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_rubyando59_en_5.5.0_3.0_1725356980800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_rubyando59","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_rubyando59","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_rubyando59|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/Rubyando59/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_rubyando59_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_rubyando59_pipeline_en.md
new file mode 100644
index 00000000000000..05dd10768ed1a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_rubyando59_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_rubyando59_pipeline pipeline BGEEmbeddings from Rubyando59
+author: John Snow Labs
+name: bge_base_financial_matryoshka_rubyando59_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_rubyando59_pipeline` is a English model originally trained by Rubyando59.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_rubyando59_pipeline_en_5.5.0_3.0_1725357006545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_rubyando59_pipeline_en_5.5.0_3.0_1725357006545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_rubyando59_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_rubyando59_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_rubyando59_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/Rubyando59/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_testing_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_testing_en.md
new file mode 100644
index 00000000000000..877c392bb0a8e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_testing_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_testing BGEEmbeddings from elsayovita
+author: John Snow Labs
+name: bge_base_financial_matryoshka_testing
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_testing` is a English model originally trained by elsayovita.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_testing_en_5.5.0_3.0_1725356749508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_testing_en_5.5.0_3.0_1725356749508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_testing","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_testing","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_testing|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.0 MB|
+
+## References
+
+https://huggingface.co/elsayovita/bge-base-financial-matryoshka-testing
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_testing_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_testing_pipeline_en.md
new file mode 100644
index 00000000000000..08cecdf69a3b69
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_financial_matryoshka_testing_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_testing_pipeline pipeline BGEEmbeddings from elsayovita
+author: John Snow Labs
+name: bge_base_financial_matryoshka_testing_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_testing_pipeline` is a English model originally trained by elsayovita.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_testing_pipeline_en_5.5.0_3.0_1725356777625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_testing_pipeline_en_5.5.0_3.0_1725356777625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_testing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_testing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_testing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/elsayovita/bge-base-financial-matryoshka-testing
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_raw_pdf_finetuned_vf1_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_raw_pdf_finetuned_vf1_en.md
new file mode 100644
index 00000000000000..89d0bb25cb195c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_raw_pdf_finetuned_vf1_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_raw_pdf_finetuned_vf1 BGEEmbeddings from kr-manish
+author: John Snow Labs
+name: bge_base_raw_pdf_finetuned_vf1
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_raw_pdf_finetuned_vf1` is a English model originally trained by kr-manish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_raw_pdf_finetuned_vf1_en_5.5.0_3.0_1725356593254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_raw_pdf_finetuned_vf1_en_5.5.0_3.0_1725356593254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_raw_pdf_finetuned_vf1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_raw_pdf_finetuned_vf1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_raw_pdf_finetuned_vf1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|376.6 MB|
+
+## References
+
+https://huggingface.co/kr-manish/bge-base-raw_pdf_finetuned_vf1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_raw_pdf_finetuned_vf1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_raw_pdf_finetuned_vf1_pipeline_en.md
new file mode 100644
index 00000000000000..1b6b892e6834ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_raw_pdf_finetuned_vf1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_raw_pdf_finetuned_vf1_pipeline pipeline BGEEmbeddings from kr-manish
+author: John Snow Labs
+name: bge_base_raw_pdf_finetuned_vf1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_raw_pdf_finetuned_vf1_pipeline` is a English model originally trained by kr-manish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_raw_pdf_finetuned_vf1_pipeline_en_5.5.0_3.0_1725356625742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_raw_pdf_finetuned_vf1_pipeline_en_5.5.0_3.0_1725356625742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_raw_pdf_finetuned_vf1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_raw_pdf_finetuned_vf1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_raw_pdf_finetuned_vf1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|376.6 MB|
+
+## References
+
+https://huggingface.co/kr-manish/bge-base-raw_pdf_finetuned_vf1
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v12_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v12_en.md
new file mode 100644
index 00000000000000..53944808e61f96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v12_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_securiti_dataset_1_v12 BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_securiti_dataset_1_v12
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v12` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v12_en_5.5.0_3.0_1725356954534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v12_en_5.5.0_3.0_1725356954534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v12","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v12","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_securiti_dataset_1_v12|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|381.4 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v12_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v12_pipeline_en.md
new file mode 100644
index 00000000000000..ddb09080a03234
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v12_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_securiti_dataset_1_v12_pipeline pipeline BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_securiti_dataset_1_v12_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v12_pipeline` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v12_pipeline_en_5.5.0_3.0_1725356986367.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v12_pipeline_en_5.5.0_3.0_1725356986367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_securiti_dataset_1_v12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|381.4 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v12
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v14_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v14_en.md
new file mode 100644
index 00000000000000..cf0165851f9b2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v14_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_securiti_dataset_1_v14 BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_securiti_dataset_1_v14
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v14` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v14_en_5.5.0_3.0_1725357000287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v14_en_5.5.0_3.0_1725357000287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v14","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v14","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_securiti_dataset_1_v14|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|388.5 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v14_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v14_pipeline_en.md
new file mode 100644
index 00000000000000..fc00164e222566
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v14_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_securiti_dataset_1_v14_pipeline pipeline BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_securiti_dataset_1_v14_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v14_pipeline` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v14_pipeline_en_5.5.0_3.0_1725357028329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v14_pipeline_en_5.5.0_3.0_1725357028329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_securiti_dataset_1_v14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_securiti_dataset_1_v14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_securiti_dataset_1_v14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|388.5 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v14
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v19_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v19_en.md
new file mode 100644
index 00000000000000..10aa32316c84e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_base_securiti_dataset_1_v19_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_securiti_dataset_1_v19 BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_securiti_dataset_1_v19
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_securiti_dataset_1_v19` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v19_en_5.5.0_3.0_1725357329758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_securiti_dataset_1_v19_en_5.5.0_3.0_1725357329758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v19","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_securiti_dataset_1_v19","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_securiti_dataset_1_v19|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|381.4 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-securiti-dataset-1-v19
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_finetuned_en.md
new file mode 100644
index 00000000000000..4795cfdb63d6f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_finetuned_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_finetuned BGEEmbeddings from phunguyenitvt
+author: John Snow Labs
+name: bge_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_finetuned` is a English model originally trained by phunguyenitvt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_finetuned_en_5.5.0_3.0_1725356727153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_finetuned_en_5.5.0_3.0_1725356727153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_finetuned","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_finetuned","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|374.4 MB|
+
+## References
+
+https://huggingface.co/phunguyenitvt/bge_finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..24f1e999ce426d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_finetuned_pipeline pipeline BGEEmbeddings from phunguyenitvt
+author: John Snow Labs
+name: bge_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_finetuned_pipeline` is a English model originally trained by phunguyenitvt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_finetuned_pipeline_en_5.5.0_3.0_1725356759618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_finetuned_pipeline_en_5.5.0_3.0_1725356759618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|374.4 MB|
+
+## References
+
+https://huggingface.co/phunguyenitvt/bge_finetuned
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_en.md
new file mode 100644
index 00000000000000..d3df141439cf2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test BGEEmbeddings from izayashiro
+author: John Snow Labs
+name: bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test` is a English model originally trained by izayashiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_en_5.5.0_3.0_1725356590086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_en_5.5.0_3.0_1725356590086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/izayashiro/bge-large-en-v1.5-hpc-lab-docs-fine-tuned-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline_en.md
new file mode 100644
index 00000000000000..30bf05cfe6d1ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline pipeline BGEEmbeddings from izayashiro
+author: John Snow Labs
+name: bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline` is a English model originally trained by izayashiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline_en_5.5.0_3.0_1725356663980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline_en_5.5.0_3.0_1725356663980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_large_english_v1_5_hpc_lab_docs_fine_tuned_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/izayashiro/bge-large-en-v1.5-hpc-lab-docs-fine-tuned-test
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_reranker_base_baai_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_reranker_base_baai_en.md
new file mode 100644
index 00000000000000..7cba62d1b612b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_reranker_base_baai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bge_reranker_base_baai XlmRoBertaForSequenceClassification from BAAI
+author: John Snow Labs
+name: bge_reranker_base_baai
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_reranker_base_baai` is a English model originally trained by BAAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_reranker_base_baai_en_5.5.0_3.0_1725327998430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_reranker_base_baai_en_5.5.0_3.0_1725327998430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bge_reranker_base_baai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bge_reranker_base_baai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_reranker_base_baai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|994.1 MB|
+
+## References
+
+https://huggingface.co/BAAI/bge-reranker-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_1epoch_batch32_step50_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_1epoch_batch32_step50_en.md
new file mode 100644
index 00000000000000..16eddab1e85a9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_1epoch_batch32_step50_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_bioasq_1epoch_batch32_step50 BGEEmbeddings from juanpablomesa
+author: John Snow Labs
+name: bge_small_bioasq_1epoch_batch32_step50
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_1epoch_batch32_step50` is a English model originally trained by juanpablomesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_step50_en_5.5.0_3.0_1725356856276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_step50_en_5.5.0_3.0_1725356856276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_1epoch_batch32_step50","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_1epoch_batch32_step50","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_bioasq_1epoch_batch32_step50|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|115.6 MB|
+
+## References
+
+https://huggingface.co/juanpablomesa/bge-small-bioasq-1epoch-batch32-step50
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_1epoch_batch32_step50_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_1epoch_batch32_step50_pipeline_en.md
new file mode 100644
index 00000000000000..26a8dde404b5c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_1epoch_batch32_step50_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_bioasq_1epoch_batch32_step50_pipeline pipeline BGEEmbeddings from juanpablomesa
+author: John Snow Labs
+name: bge_small_bioasq_1epoch_batch32_step50_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_1epoch_batch32_step50_pipeline` is a English model originally trained by juanpablomesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_step50_pipeline_en_5.5.0_3.0_1725356866253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_step50_pipeline_en_5.5.0_3.0_1725356866253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_bioasq_1epoch_batch32_step50_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_bioasq_1epoch_batch32_step50_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_bioasq_1epoch_batch32_step50_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|115.6 MB|
+
+## References
+
+https://huggingface.co/juanpablomesa/bge-small-bioasq-1epoch-batch32-step50
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_batch64_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_batch64_en.md
new file mode 100644
index 00000000000000..1c90ea6b2c4b40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_batch64_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_bioasq_batch64 BGEEmbeddings from juanpablomesa
+author: John Snow Labs
+name: bge_small_bioasq_batch64
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_batch64` is a English model originally trained by juanpablomesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_batch64_en_5.5.0_3.0_1725356502777.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_batch64_en_5.5.0_3.0_1725356502777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_batch64","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_batch64","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_bioasq_batch64|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|115.7 MB|
+
+## References
+
+https://huggingface.co/juanpablomesa/bge-small-bioasq-batch64
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_batch64_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_batch64_pipeline_en.md
new file mode 100644
index 00000000000000..2439cef8fefec2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_small_bioasq_batch64_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_bioasq_batch64_pipeline pipeline BGEEmbeddings from juanpablomesa
+author: John Snow Labs
+name: bge_small_bioasq_batch64_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_batch64_pipeline` is a English model originally trained by juanpablomesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_batch64_pipeline_en_5.5.0_3.0_1725356512882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_batch64_pipeline_en_5.5.0_3.0_1725356512882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_bioasq_batch64_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_bioasq_batch64_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_bioasq_batch64_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|115.7 MB|
+
+## References
+
+https://huggingface.co/juanpablomesa/bge-small-bioasq-batch64
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_preview_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_preview_en.md
new file mode 100644
index 00000000000000..08eaa797e3ec83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_preview_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_english_dcpr_tuned_preview BGEEmbeddings from sanyamjain0315
+author: John Snow Labs
+name: bge_small_english_dcpr_tuned_preview
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_dcpr_tuned_preview` is a English model originally trained by sanyamjain0315.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_preview_en_5.5.0_3.0_1725357328632.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_preview_en_5.5.0_3.0_1725357328632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_english_dcpr_tuned_preview","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_english_dcpr_tuned_preview","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_dcpr_tuned_preview|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|115.0 MB|
+
+## References
+
+https://huggingface.co/sanyamjain0315/bge-small-en-dcpr-tuned-preview
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_preview_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_preview_pipeline_en.md
new file mode 100644
index 00000000000000..4280cceeeacf07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_preview_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_english_dcpr_tuned_preview_pipeline pipeline BGEEmbeddings from sanyamjain0315
+author: John Snow Labs
+name: bge_small_english_dcpr_tuned_preview_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_dcpr_tuned_preview_pipeline` is a English model originally trained by sanyamjain0315.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_preview_pipeline_en_5.5.0_3.0_1725357337696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_preview_pipeline_en_5.5.0_3.0_1725357337696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_english_dcpr_tuned_preview_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_english_dcpr_tuned_preview_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_dcpr_tuned_preview_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|115.0 MB|
+
+## References
+
+https://huggingface.co/sanyamjain0315/bge-small-en-dcpr-tuned-preview
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_teachafy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_teachafy_pipeline_en.md
new file mode 100644
index 00000000000000..037bf959bc5ead
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_dcpr_tuned_teachafy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_english_dcpr_tuned_teachafy_pipeline pipeline BGEEmbeddings from Teachafy
+author: John Snow Labs
+name: bge_small_english_dcpr_tuned_teachafy_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_dcpr_tuned_teachafy_pipeline` is a English model originally trained by Teachafy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_teachafy_pipeline_en_5.5.0_3.0_1725356365820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_dcpr_tuned_teachafy_pipeline_en_5.5.0_3.0_1725356365820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_english_dcpr_tuned_teachafy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_english_dcpr_tuned_teachafy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_dcpr_tuned_teachafy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|115.2 MB|
+
+## References
+
+https://huggingface.co/Teachafy/bge-small-en-dcpr-tuned
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_v1_5_ft_orc_0813_en.md b/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_v1_5_ft_orc_0813_en.md
new file mode 100644
index 00000000000000..403080151243dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bge_small_english_v1_5_ft_orc_0813_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_english_v1_5_ft_orc_0813 BGEEmbeddings from magnifi
+author: John Snow Labs
+name: bge_small_english_v1_5_ft_orc_0813
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_ft_orc_0813` is a English model originally trained by magnifi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0813_en_5.5.0_3.0_1725357207124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0813_en_5.5.0_3.0_1725357207124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_ft_orc_0813","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_ft_orc_0813","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_ft_orc_0813|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|110.2 MB|
+
+## References
+
+https://huggingface.co/magnifi/bge-small-en-v1.5-ft-orc-0813
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bias_detection_d1v1de_en.md b/docs/_posts/ahmedlone127/2024-09-03-bias_detection_d1v1de_en.md
new file mode 100644
index 00000000000000..9bf8c2a5a8d7d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bias_detection_d1v1de_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bias_detection_d1v1de RoBertaForSequenceClassification from D1V1DE
+author: John Snow Labs
+name: bias_detection_d1v1de
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_detection_d1v1de` is a English model originally trained by D1V1DE.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_detection_d1v1de_en_5.5.0_3.0_1725402304682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_detection_d1v1de_en_5.5.0_3.0_1725402304682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("bias_detection_d1v1de","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("bias_detection_d1v1de", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_detection_d1v1de|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.7 MB|
+
+## References
+
+https://huggingface.co/D1V1DE/bias-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bias_detection_d1v1de_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bias_detection_d1v1de_pipeline_en.md
new file mode 100644
index 00000000000000..9ed0a634910714
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bias_detection_d1v1de_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bias_detection_d1v1de_pipeline pipeline RoBertaForSequenceClassification from D1V1DE
+author: John Snow Labs
+name: bias_detection_d1v1de_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_detection_d1v1de_pipeline` is a English model originally trained by D1V1DE.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_detection_d1v1de_pipeline_en_5.5.0_3.0_1725402321314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_detection_d1v1de_pipeline_en_5.5.0_3.0_1725402321314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bias_detection_d1v1de_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bias_detection_d1v1de_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_detection_d1v1de_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.7 MB|
+
+## References
+
+https://huggingface.co/D1V1DE/bias-detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-biomednlp_biomedbert_base_uncased_abstract_en.md b/docs/_posts/ahmedlone127/2024-09-03-biomednlp_biomedbert_base_uncased_abstract_en.md
new file mode 100644
index 00000000000000..b05c35d3cec05f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-biomednlp_biomedbert_base_uncased_abstract_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biomednlp_biomedbert_base_uncased_abstract BertEmbeddings from microsoft
+author: John Snow Labs
+name: biomednlp_biomedbert_base_uncased_abstract
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_biomedbert_base_uncased_abstract` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_base_uncased_abstract_en_5.5.0_3.0_1725407035600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_base_uncased_abstract_en_5.5.0_3.0_1725407035600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("biomednlp_biomedbert_base_uncased_abstract","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("biomednlp_biomedbert_base_uncased_abstract","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomednlp_biomedbert_base_uncased_abstract|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-biomednlp_biomedbert_base_uncased_abstract_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-biomednlp_biomedbert_base_uncased_abstract_pipeline_en.md
new file mode 100644
index 00000000000000..9956daa2551903
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-biomednlp_biomedbert_base_uncased_abstract_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biomednlp_biomedbert_base_uncased_abstract_pipeline pipeline BertEmbeddings from microsoft
+author: John Snow Labs
+name: biomednlp_biomedbert_base_uncased_abstract_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_biomedbert_base_uncased_abstract_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_base_uncased_abstract_pipeline_en_5.5.0_3.0_1725407061863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_base_uncased_abstract_pipeline_en_5.5.0_3.0_1725407061863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biomednlp_biomedbert_base_uncased_abstract_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biomednlp_biomedbert_base_uncased_abstract_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomednlp_biomedbert_base_uncased_abstract_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_en.md b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_en.md
new file mode 100644
index 00000000000000..33e133b9bd5028
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance MPNetEmbeddings from teven
+author: John Snow Labs
+name: bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance` is a English model originally trained by teven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_en_5.5.0_3.0_1725350168188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_en_5.5.0_3.0_1725350168188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/bi_all_bs320_vanilla_finetuned_WebNLG2020_relevance
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_en.md b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_en.md
new file mode 100644
index 00000000000000..63a530968ac817
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage MPNetEmbeddings from teven
+author: John Snow Labs
+name: bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage` is a English model originally trained by teven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_en_5.5.0_3.0_1725350340326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_en_5.5.0_3.0_1725350340326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/teven/bi_all-mpnet-base-v2_finetuned_WebNLG2020_data_coverage
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline_en.md
new file mode 100644
index 00000000000000..348fac46daab44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline pipeline MPNetEmbeddings from teven
+author: John Snow Labs
+name: bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline` is a English model originally trained by teven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline_en_5.5.0_3.0_1725350360286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline_en_5.5.0_3.0_1725350360286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bislama_all_mpnet_base_v2_finetuned_webnlg2020_data_coverage_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/teven/bi_all-mpnet-base-v2_finetuned_WebNLG2020_data_coverage
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en.md b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en.md
new file mode 100644
index 00000000000000..0292e942591531
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average MPNetEmbeddings from teven
+author: John Snow Labs
+name: bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average` is a English model originally trained by teven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en_5.5.0_3.0_1725350706997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en_5.5.0_3.0_1725350706997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bislama_all_mpnet_base_v2_finetuned_webnlg2020_metric_average|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/teven/bi_all-mpnet-base-v2_finetuned_WebNLG2020_metric_average
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bm_french_bm.md b/docs/_posts/ahmedlone127/2024-09-03-bm_french_bm.md
new file mode 100644
index 00000000000000..300874688d90fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bm_french_bm.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Bambara bm_french MarianTransformer from Ife
+author: John Snow Labs
+name: bm_french
+date: 2024-09-03
+tags: [bm, open_source, onnx, translation, marian]
+task: Translation
+language: bm
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bm_french` is a Bambara model originally trained by Ife.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bm_french_bm_5.5.0_3.0_1725346799375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bm_french_bm_5.5.0_3.0_1725346799375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("bm_french","bm") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("bm_french","bm") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bm_french|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|bm|
+|Size:|507.8 MB|
+
+## References
+
+https://huggingface.co/Ife/BM-FR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bookmebus_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-03-bookmebus_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..f3f1b070e1ebad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bookmebus_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bookmebus_sentiment_analysis XlmRoBertaForSequenceClassification from seanghay
+author: John Snow Labs
+name: bookmebus_sentiment_analysis
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bookmebus_sentiment_analysis` is a English model originally trained by seanghay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bookmebus_sentiment_analysis_en_5.5.0_3.0_1725327756073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bookmebus_sentiment_analysis_en_5.5.0_3.0_1725327756073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bookmebus_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bookmebus_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bookmebus_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|839.1 MB|
+
+## References
+
+https://huggingface.co/seanghay/bookmebus-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-brahmai_clip_v0_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-brahmai_clip_v0_1_en.md
new file mode 100644
index 00000000000000..a66365bd141490
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-brahmai_clip_v0_1_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English brahmai_clip_v0_1 CLIPForZeroShotClassification from brahmairesearch
+author: John Snow Labs
+name: brahmai_clip_v0_1
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brahmai_clip_v0_1` is a English model originally trained by brahmairesearch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brahmai_clip_v0_1_en_5.5.0_3.0_1725339200005.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brahmai_clip_v0_1_en_5.5.0_3.0_1725339200005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("brahmai_clip_v0_1","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("brahmai_clip_v0_1","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brahmai_clip_v0_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/brahmairesearch/brahmai-clip-v0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_en.md b/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_en.md
new file mode 100644
index 00000000000000..abb5d6a8c0caba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bsc_bio_ehr_spanish_combined_train_distemist_dev_ner RoBertaForTokenClassification from Rodrigo1771
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_combined_train_distemist_dev_ner
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_combined_train_distemist_dev_ner` is a English model originally trained by Rodrigo1771.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_en_5.5.0_3.0_1725383403655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_en_5.5.0_3.0_1725383403655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_combined_train_distemist_dev_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_combined_train_distemist_dev_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_combined_train_distemist_dev_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|440.5 MB|
+
+## References
+
+https://huggingface.co/Rodrigo1771/bsc-bio-ehr-es-combined-train-distemist-dev-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline_en.md
new file mode 100644
index 00000000000000..9607174e5678bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline pipeline RoBertaForTokenClassification from Rodrigo1771
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline` is a English model originally trained by Rodrigo1771.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline_en_5.5.0_3.0_1725383437232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline_en_5.5.0_3.0_1725383437232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_combined_train_distemist_dev_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|440.5 MB|
+
+## References
+
+https://huggingface.co/Rodrigo1771/bsc-bio-ehr-es-combined-train-distemist-dev-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_drugtemist_ner_en.md b/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_drugtemist_ner_en.md
new file mode 100644
index 00000000000000..1d588523a68255
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bsc_bio_ehr_spanish_drugtemist_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bsc_bio_ehr_spanish_drugtemist_ner RoBertaForTokenClassification from Rodrigo1771
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_drugtemist_ner
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_drugtemist_ner` is a English model originally trained by Rodrigo1771.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_drugtemist_ner_en_5.5.0_3.0_1725326472131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_drugtemist_ner_en_5.5.0_3.0_1725326472131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_drugtemist_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_drugtemist_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_drugtemist_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|440.4 MB|
+
+## References
+
+https://huggingface.co/Rodrigo1771/bsc-bio-ehr-es-drugtemist-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_yagina_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_yagina_en.md
new file mode 100644
index 00000000000000..5903ea0efa462a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_yagina_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_yagina DistilBertForSequenceClassification from YaGiNA
+author: John Snow Labs
+name: burmese_awesome_model_yagina
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_yagina` is a English model originally trained by YaGiNA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_yagina_en_5.5.0_3.0_1725394675197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_yagina_en_5.5.0_3.0_1725394675197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_yagina","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_yagina", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_yagina|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/YaGiNA/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_yagina_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_yagina_pipeline_en.md
new file mode 100644
index 00000000000000..c41bbd793cec2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_model_yagina_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_yagina_pipeline pipeline DistilBertForSequenceClassification from YaGiNA
+author: John Snow Labs
+name: burmese_awesome_model_yagina_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_yagina_pipeline` is a English model originally trained by YaGiNA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_yagina_pipeline_en_5.5.0_3.0_1725394688167.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_yagina_pipeline_en_5.5.0_3.0_1725394688167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_yagina_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_yagina_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_yagina_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/YaGiNA/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_4_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_4_en.md
new file mode 100644
index 00000000000000..6008021a9a4425
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_4 MPNetEmbeddings from lewtun
+author: John Snow Labs
+name: burmese_awesome_setfit_model_4
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_4` is a English model originally trained by lewtun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_4_en_5.5.0_3.0_1725350226556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_4_en_5.5.0_3.0_1725350226556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_4","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_4","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/lewtun/my-awesome-setfit-model-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_4_pipeline_en.md
new file mode 100644
index 00000000000000..5d6923d7850c11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_4_pipeline pipeline MPNetEmbeddings from lewtun
+author: John Snow Labs
+name: burmese_awesome_setfit_model_4_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_4_pipeline` is a English model originally trained by lewtun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_4_pipeline_en_5.5.0_3.0_1725350246933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_4_pipeline_en_5.5.0_3.0_1725350246933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_setfit_model_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/lewtun/my-awesome-setfit-model-4
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_epec254_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_epec254_en.md
new file mode 100644
index 00000000000000..7c6bf9ef4332bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_epec254_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_epec254 MPNetEmbeddings from epec254
+author: John Snow Labs
+name: burmese_awesome_setfit_model_epec254
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_epec254` is a English model originally trained by epec254.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_epec254_en_5.5.0_3.0_1725350367640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_epec254_en_5.5.0_3.0_1725350367640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_epec254","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_epec254","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_epec254|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/epec254/my-awesome-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_epec254_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_epec254_pipeline_en.md
new file mode 100644
index 00000000000000..c375357c9fe8aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_epec254_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_epec254_pipeline pipeline MPNetEmbeddings from epec254
+author: John Snow Labs
+name: burmese_awesome_setfit_model_epec254_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_epec254_pipeline` is a English model originally trained by epec254.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_epec254_pipeline_en_5.5.0_3.0_1725350388042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_epec254_pipeline_en_5.5.0_3.0_1725350388042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_setfit_model_epec254_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_epec254_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_epec254_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/epec254/my-awesome-setfit-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_saim5000_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_saim5000_en.md
new file mode 100644
index 00000000000000..848b74e8846e31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_saim5000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_saim5000 MPNetEmbeddings from Saim5000
+author: John Snow Labs
+name: burmese_awesome_setfit_model_saim5000
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_saim5000` is a English model originally trained by Saim5000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_saim5000_en_5.5.0_3.0_1725350125489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_saim5000_en_5.5.0_3.0_1725350125489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_saim5000","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_saim5000","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_saim5000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/Saim5000/my-awesome-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_saim5000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_saim5000_pipeline_en.md
new file mode 100644
index 00000000000000..90a80875138d38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_awesome_setfit_model_saim5000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_saim5000_pipeline pipeline MPNetEmbeddings from Saim5000
+author: John Snow Labs
+name: burmese_awesome_setfit_model_saim5000_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_saim5000_pipeline` is a English model originally trained by Saim5000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_saim5000_pipeline_en_5.5.0_3.0_1725350148153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_saim5000_pipeline_en_5.5.0_3.0_1725350148153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_setfit_model_saim5000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_saim5000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_saim5000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/Saim5000/my-awesome-setfit-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_distillbert_model_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_distillbert_model_en.md
new file mode 100644
index 00000000000000..444f34f79f4b0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_distillbert_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_distillbert_model DistilBertForSequenceClassification from allagmaroua
+author: John Snow Labs
+name: burmese_distillbert_model
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_distillbert_model` is a English model originally trained by allagmaroua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_distillbert_model_en_5.5.0_3.0_1725394365766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_distillbert_model_en_5.5.0_3.0_1725394365766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_distillbert_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_distillbert_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_distillbert_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/allagmaroua/my-distillbert-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_distillbert_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_distillbert_model_pipeline_en.md
new file mode 100644
index 00000000000000..cbae0ae06a734c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_distillbert_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_distillbert_model_pipeline pipeline DistilBertForSequenceClassification from allagmaroua
+author: John Snow Labs
+name: burmese_distillbert_model_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_distillbert_model_pipeline` is a English model originally trained by allagmaroua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_distillbert_model_pipeline_en_5.5.0_3.0_1725394379679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_distillbert_model_pipeline_en_5.5.0_3.0_1725394379679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_distillbert_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_distillbert_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_distillbert_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/allagmaroua/my-distillbert-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_fine_tuned_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_fine_tuned_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..26e70340ed52c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_fine_tuned_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_fine_tuned_distilbert_pipeline pipeline DistilBertForSequenceClassification from Benuehlinger
+author: John Snow Labs
+name: burmese_fine_tuned_distilbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_fine_tuned_distilbert_pipeline` is a English model originally trained by Benuehlinger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_fine_tuned_distilbert_pipeline_en_5.5.0_3.0_1725329660439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_fine_tuned_distilbert_pipeline_en_5.5.0_3.0_1725329660439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_fine_tuned_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_fine_tuned_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_fine_tuned_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Benuehlinger/my-fine-tuned-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_finetuned_emotion_distilbert_zakiravian_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_finetuned_emotion_distilbert_zakiravian_en.md
new file mode 100644
index 00000000000000..98ba59c66920f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_finetuned_emotion_distilbert_zakiravian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_finetuned_emotion_distilbert_zakiravian DistilBertForSequenceClassification from zakiravian
+author: John Snow Labs
+name: burmese_finetuned_emotion_distilbert_zakiravian
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_finetuned_emotion_distilbert_zakiravian` is a English model originally trained by zakiravian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_finetuned_emotion_distilbert_zakiravian_en_5.5.0_3.0_1725330026867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_finetuned_emotion_distilbert_zakiravian_en_5.5.0_3.0_1725330026867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_finetuned_emotion_distilbert_zakiravian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_finetuned_emotion_distilbert_zakiravian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_finetuned_emotion_distilbert_zakiravian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/zakiravian/my-finetuned-emotion-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_finetuned_emotion_distilbert_zakiravian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_finetuned_emotion_distilbert_zakiravian_pipeline_en.md
new file mode 100644
index 00000000000000..0517f972099f47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_finetuned_emotion_distilbert_zakiravian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_finetuned_emotion_distilbert_zakiravian_pipeline pipeline DistilBertForSequenceClassification from zakiravian
+author: John Snow Labs
+name: burmese_finetuned_emotion_distilbert_zakiravian_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_finetuned_emotion_distilbert_zakiravian_pipeline` is a English model originally trained by zakiravian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_finetuned_emotion_distilbert_zakiravian_pipeline_en_5.5.0_3.0_1725330041737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_finetuned_emotion_distilbert_zakiravian_pipeline_en_5.5.0_3.0_1725330041737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_finetuned_emotion_distilbert_zakiravian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_finetuned_emotion_distilbert_zakiravian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_finetuned_emotion_distilbert_zakiravian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/zakiravian/my-finetuned-emotion-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-burmese_text_classification_finetuned_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-burmese_text_classification_finetuned_v1_pipeline_en.md
new file mode 100644
index 00000000000000..d55c7d550194db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-burmese_text_classification_finetuned_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_text_classification_finetuned_v1_pipeline pipeline DistilBertForSequenceClassification from cwchang
+author: John Snow Labs
+name: burmese_text_classification_finetuned_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_text_classification_finetuned_v1_pipeline` is a English model originally trained by cwchang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_text_classification_finetuned_v1_pipeline_en_5.5.0_3.0_1725330067465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_text_classification_finetuned_v1_pipeline_en_5.5.0_3.0_1725330067465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_text_classification_finetuned_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_text_classification_finetuned_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_text_classification_finetuned_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/cwchang/my-text-classification-finetuned-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-camembert_base_toxic_french_user_prompts_fr.md b/docs/_posts/ahmedlone127/2024-09-03-camembert_base_toxic_french_user_prompts_fr.md
new file mode 100644
index 00000000000000..7d4e84a1dea4b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-camembert_base_toxic_french_user_prompts_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French camembert_base_toxic_french_user_prompts CamemBertForSequenceClassification from AgentPublic
+author: John Snow Labs
+name: camembert_base_toxic_french_user_prompts
+date: 2024-09-03
+tags: [fr, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_base_toxic_french_user_prompts` is a French model originally trained by AgentPublic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_toxic_french_user_prompts_fr_5.5.0_3.0_1725378668794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_toxic_french_user_prompts_fr_5.5.0_3.0_1725378668794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("camembert_base_toxic_french_user_prompts","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("camembert_base_toxic_french_user_prompts", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_base_toxic_french_user_prompts|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|391.4 MB|
+
+## References
+
+https://huggingface.co/AgentPublic/camembert-base-toxic-fr-user-prompts
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-camembert_base_toxic_french_user_prompts_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-03-camembert_base_toxic_french_user_prompts_pipeline_fr.md
new file mode 100644
index 00000000000000..8915cc0b95dea9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-camembert_base_toxic_french_user_prompts_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French camembert_base_toxic_french_user_prompts_pipeline pipeline CamemBertForSequenceClassification from AgentPublic
+author: John Snow Labs
+name: camembert_base_toxic_french_user_prompts_pipeline
+date: 2024-09-03
+tags: [fr, open_source, pipeline, onnx]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_base_toxic_french_user_prompts_pipeline` is a French model originally trained by AgentPublic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_toxic_french_user_prompts_pipeline_fr_5.5.0_3.0_1725378699989.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_toxic_french_user_prompts_pipeline_fr_5.5.0_3.0_1725378699989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("camembert_base_toxic_french_user_prompts_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("camembert_base_toxic_french_user_prompts_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_base_toxic_french_user_prompts_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|391.4 MB|
+
+## References
+
+https://huggingface.co/AgentPublic/camembert-base-toxic-fr-user-prompts
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cappy_large_en.md b/docs/_posts/ahmedlone127/2024-09-03-cappy_large_en.md
new file mode 100644
index 00000000000000..7b964bfefc3ebf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cappy_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cappy_large RoBertaForSequenceClassification from btan2
+author: John Snow Labs
+name: cappy_large
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cappy_large` is a English model originally trained by btan2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cappy_large_en_5.5.0_3.0_1725369480428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cappy_large_en_5.5.0_3.0_1725369480428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("cappy_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("cappy_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cappy_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/btan2/cappy-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cappy_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cappy_large_pipeline_en.md
new file mode 100644
index 00000000000000..cd16849979aff0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cappy_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cappy_large_pipeline pipeline RoBertaForSequenceClassification from btan2
+author: John Snow Labs
+name: cappy_large_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cappy_large_pipeline` is a English model originally trained by btan2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cappy_large_pipeline_en_5.5.0_3.0_1725369552607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cappy_large_pipeline_en_5.5.0_3.0_1725369552607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cappy_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cappy_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cappy_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/btan2/cappy-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-car_class_classification_en.md b/docs/_posts/ahmedlone127/2024-09-03-car_class_classification_en.md
new file mode 100644
index 00000000000000..ffd9e22e98b3f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-car_class_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English car_class_classification DistilBertForSequenceClassification from pimcore
+author: John Snow Labs
+name: car_class_classification
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_class_classification` is a English model originally trained by pimcore.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/car_class_classification_en_5.5.0_3.0_1725394413813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_class_classification_en_5.5.0_3.0_1725394413813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("car_class_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("car_class_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_class_classification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/pimcore/car-class-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-catalan_capitalization_punctuation_restoration_sanivert_ca.md b/docs/_posts/ahmedlone127/2024-09-03-catalan_capitalization_punctuation_restoration_sanivert_ca.md
new file mode 100644
index 00000000000000..4799a0e0903a26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-catalan_capitalization_punctuation_restoration_sanivert_ca.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Catalan, Valencian catalan_capitalization_punctuation_restoration_sanivert RoBertaForTokenClassification from VOCALINLP
+author: John Snow Labs
+name: catalan_capitalization_punctuation_restoration_sanivert
+date: 2024-09-03
+tags: [ca, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: ca
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`catalan_capitalization_punctuation_restoration_sanivert` is a Catalan, Valencian model originally trained by VOCALINLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/catalan_capitalization_punctuation_restoration_sanivert_ca_5.5.0_3.0_1725383015130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/catalan_capitalization_punctuation_restoration_sanivert_ca_5.5.0_3.0_1725383015130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("catalan_capitalization_punctuation_restoration_sanivert","ca") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("catalan_capitalization_punctuation_restoration_sanivert", "ca")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|catalan_capitalization_punctuation_restoration_sanivert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ca|
+|Size:|453.6 MB|
+
+## References
+
+https://huggingface.co/VOCALINLP/catalan_capitalization_punctuation_restoration_sanivert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-catalan_capitalization_punctuation_restoration_sanivert_pipeline_ca.md b/docs/_posts/ahmedlone127/2024-09-03-catalan_capitalization_punctuation_restoration_sanivert_pipeline_ca.md
new file mode 100644
index 00000000000000..8fd397b6b07dad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-catalan_capitalization_punctuation_restoration_sanivert_pipeline_ca.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Catalan, Valencian catalan_capitalization_punctuation_restoration_sanivert_pipeline pipeline RoBertaForTokenClassification from VOCALINLP
+author: John Snow Labs
+name: catalan_capitalization_punctuation_restoration_sanivert_pipeline
+date: 2024-09-03
+tags: [ca, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ca
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`catalan_capitalization_punctuation_restoration_sanivert_pipeline` is a Catalan, Valencian model originally trained by VOCALINLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/catalan_capitalization_punctuation_restoration_sanivert_pipeline_ca_5.5.0_3.0_1725383043300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/catalan_capitalization_punctuation_restoration_sanivert_pipeline_ca_5.5.0_3.0_1725383043300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("catalan_capitalization_punctuation_restoration_sanivert_pipeline", lang = "ca")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("catalan_capitalization_punctuation_restoration_sanivert_pipeline", lang = "ca")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|catalan_capitalization_punctuation_restoration_sanivert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ca|
+|Size:|453.6 MB|
+
+## References
+
+https://huggingface.co/VOCALINLP/catalan_capitalization_punctuation_restoration_sanivert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-categor_ai_en.md b/docs/_posts/ahmedlone127/2024-09-03-categor_ai_en.md
new file mode 100644
index 00000000000000..9724313542ef2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-categor_ai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English categor_ai DistilBertForSequenceClassification from tinutmap
+author: John Snow Labs
+name: categor_ai
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`categor_ai` is a English model originally trained by tinutmap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/categor_ai_en_5.5.0_3.0_1725394219585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/categor_ai_en_5.5.0_3.0_1725394219585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("categor_ai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("categor_ai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|categor_ai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tinutmap/categor_ai
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-categor_ai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-categor_ai_pipeline_en.md
new file mode 100644
index 00000000000000..f44753d9e25fd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-categor_ai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English categor_ai_pipeline pipeline DistilBertForSequenceClassification from tinutmap
+author: John Snow Labs
+name: categor_ai_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`categor_ai_pipeline` is a English model originally trained by tinutmap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/categor_ai_pipeline_en_5.5.0_3.0_1725394233842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/categor_ai_pipeline_en_5.5.0_3.0_1725394233842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("categor_ai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("categor_ai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|categor_ai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tinutmap/categor_ai
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-categorization_model_svramesh_en.md b/docs/_posts/ahmedlone127/2024-09-03-categorization_model_svramesh_en.md
new file mode 100644
index 00000000000000..fdf8a5bf5fabf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-categorization_model_svramesh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English categorization_model_svramesh DistilBertForSequenceClassification from svramesh
+author: John Snow Labs
+name: categorization_model_svramesh
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`categorization_model_svramesh` is a English model originally trained by svramesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/categorization_model_svramesh_en_5.5.0_3.0_1725330300559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/categorization_model_svramesh_en_5.5.0_3.0_1725330300559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("categorization_model_svramesh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("categorization_model_svramesh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|categorization_model_svramesh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/svramesh/categorization_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-categorization_model_svramesh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-categorization_model_svramesh_pipeline_en.md
new file mode 100644
index 00000000000000..35bd3ef060cdbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-categorization_model_svramesh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English categorization_model_svramesh_pipeline pipeline DistilBertForSequenceClassification from svramesh
+author: John Snow Labs
+name: categorization_model_svramesh_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`categorization_model_svramesh_pipeline` is a English model originally trained by svramesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/categorization_model_svramesh_pipeline_en_5.5.0_3.0_1725330313000.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/categorization_model_svramesh_pipeline_en_5.5.0_3.0_1725330313000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("categorization_model_svramesh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("categorization_model_svramesh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|categorization_model_svramesh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/svramesh/categorization_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-chinese_english_translation_en.md b/docs/_posts/ahmedlone127/2024-09-03-chinese_english_translation_en.md
new file mode 100644
index 00000000000000..1dd6b5d0409b99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-chinese_english_translation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English chinese_english_translation MarianTransformer from jieshenai
+author: John Snow Labs
+name: chinese_english_translation
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_english_translation` is a English model originally trained by jieshenai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_english_translation_en_5.5.0_3.0_1725346295957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_english_translation_en_5.5.0_3.0_1725346295957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("chinese_english_translation","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("chinese_english_translation","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chinese_english_translation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|540.0 MB|
+
+## References
+
+https://huggingface.co/jieshenai/zh_en_translation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-chinese_english_translation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-chinese_english_translation_pipeline_en.md
new file mode 100644
index 00000000000000..d594e1fa130f05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-chinese_english_translation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English chinese_english_translation_pipeline pipeline MarianTransformer from jieshenai
+author: John Snow Labs
+name: chinese_english_translation_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_english_translation_pipeline` is a English model originally trained by jieshenai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_english_translation_pipeline_en_5.5.0_3.0_1725346322340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_english_translation_pipeline_en_5.5.0_3.0_1725346322340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chinese_english_translation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chinese_english_translation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chinese_english_translation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.5 MB|
+
+## References
+
+https://huggingface.co/jieshenai/zh_en_translation
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-citation_classifier_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-citation_classifier_roberta_base_en.md
new file mode 100644
index 00000000000000..8aaf891262e1eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-citation_classifier_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English citation_classifier_roberta_base RoBertaForSequenceClassification from selink
+author: John Snow Labs
+name: citation_classifier_roberta_base
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`citation_classifier_roberta_base` is a English model originally trained by selink.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/citation_classifier_roberta_base_en_5.5.0_3.0_1725337497916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/citation_classifier_roberta_base_en_5.5.0_3.0_1725337497916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("citation_classifier_roberta_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("citation_classifier_roberta_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|citation_classifier_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/selink/citation-classifier-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-classificateur_intention_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-classificateur_intention_camembert_pipeline_en.md
new file mode 100644
index 00000000000000..eb76fd35523251
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-classificateur_intention_camembert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English classificateur_intention_camembert_pipeline pipeline CamemBertForSequenceClassification from DioulaD
+author: John Snow Labs
+name: classificateur_intention_camembert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classificateur_intention_camembert_pipeline` is a English model originally trained by DioulaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classificateur_intention_camembert_pipeline_en_5.5.0_3.0_1725378407325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classificateur_intention_camembert_pipeline_en_5.5.0_3.0_1725378407325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("classificateur_intention_camembert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("classificateur_intention_camembert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classificateur_intention_camembert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|388.1 MB|
+
+## References
+
+https://huggingface.co/DioulaD/classificateur-intention_camembert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cleaned_bert_base_cased_500_620e5b_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cleaned_bert_base_cased_500_620e5b_pipeline_en.md
new file mode 100644
index 00000000000000..fec291d760b94f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cleaned_bert_base_cased_500_620e5b_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cleaned_bert_base_cased_500_620e5b_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: cleaned_bert_base_cased_500_620e5b_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_bert_base_cased_500_620e5b_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_bert_base_cased_500_620e5b_pipeline_en_5.5.0_3.0_1725332535657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_bert_base_cased_500_620e5b_pipeline_en_5.5.0_3.0_1725332535657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cleaned_bert_base_cased_500_620e5b_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cleaned_bert_base_cased_500_620e5b_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cleaned_bert_base_cased_500_620e5b_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/cleaned-bert-base-cased-500-620e5b
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_500_en.md b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_500_en.md
new file mode 100644
index 00000000000000..38ca8ed87418e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_500_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cleaned_e5_base_500 E5Embeddings from rithwik-db
+author: John Snow Labs
+name: cleaned_e5_base_500
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_base_500` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_500_en_5.5.0_3.0_1725340920827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_500_en_5.5.0_3.0_1725340920827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("cleaned_e5_base_500","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("cleaned_e5_base_500","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cleaned_e5_base_500|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|387.4 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/cleaned-e5-base-500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_unsupervised_16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_unsupervised_16_pipeline_en.md
new file mode 100644
index 00000000000000..12de208312c4b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_base_unsupervised_16_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cleaned_e5_base_unsupervised_16_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: cleaned_e5_base_unsupervised_16_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_base_unsupervised_16_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_16_pipeline_en_5.5.0_3.0_1725332708746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_16_pipeline_en_5.5.0_3.0_1725332708746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cleaned_e5_base_unsupervised_16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cleaned_e5_base_unsupervised_16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cleaned_e5_base_unsupervised_16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|386.2 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/cleaned-e5-base-unsupervised-16
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_large_unsupervised_8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_large_unsupervised_8_pipeline_en.md
new file mode 100644
index 00000000000000..f2346044685aaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cleaned_e5_large_unsupervised_8_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cleaned_e5_large_unsupervised_8_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: cleaned_e5_large_unsupervised_8_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_large_unsupervised_8_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_large_unsupervised_8_pipeline_en_5.5.0_3.0_1725340377926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_large_unsupervised_8_pipeline_en_5.5.0_3.0_1725340377926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cleaned_e5_large_unsupervised_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cleaned_e5_large_unsupervised_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cleaned_e5_large_unsupervised_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/rithwik-db/cleaned-e5-large-unsupervised-8
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-climateattention_10k_upscaled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-climateattention_10k_upscaled_pipeline_en.md
new file mode 100644
index 00000000000000..63cedd901b9ac3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-climateattention_10k_upscaled_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English climateattention_10k_upscaled_pipeline pipeline RoBertaForTokenClassification from kruthof
+author: John Snow Labs
+name: climateattention_10k_upscaled_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climateattention_10k_upscaled_pipeline` is a English model originally trained by kruthof.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climateattention_10k_upscaled_pipeline_en_5.5.0_3.0_1725326521236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climateattention_10k_upscaled_pipeline_en_5.5.0_3.0_1725326521236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("climateattention_10k_upscaled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("climateattention_10k_upscaled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|climateattention_10k_upscaled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|307.4 MB|
+
+## References
+
+https://huggingface.co/kruthof/climateattention-10k-upscaled
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_400_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_400_pipeline_en.md
new file mode 100644
index 00000000000000..bf34c031eb56df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_400_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_base_patch16_supervised_mulitilingual_400_pipeline pipeline CLIPForZeroShotClassification from gowitheflowlab
+author: John Snow Labs
+name: clip_base_patch16_supervised_mulitilingual_400_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_400_pipeline` is a English model originally trained by gowitheflowlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_400_pipeline_en_5.5.0_3.0_1725338702225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_400_pipeline_en_5.5.0_3.0_1725338702225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_400_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_400_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_base_patch16_supervised_mulitilingual_400_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.8 MB|
+
+## References
+
+https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-400
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_800_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_800_pipeline_en.md
new file mode 100644
index 00000000000000..bbd3072e26c1f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_base_patch16_supervised_mulitilingual_800_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_base_patch16_supervised_mulitilingual_800_pipeline pipeline CLIPForZeroShotClassification from gowitheflowlab
+author: John Snow Labs
+name: clip_base_patch16_supervised_mulitilingual_800_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_800_pipeline` is a English model originally trained by gowitheflowlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_800_pipeline_en_5.5.0_3.0_1725338129002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_800_pipeline_en_5.5.0_3.0_1725338129002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_800_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_800_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_base_patch16_supervised_mulitilingual_800_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.7 MB|
+
+## References
+
+https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-800
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_fashion_attribute_model_try_2_base32_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_fashion_attribute_model_try_2_base32_en.md
new file mode 100644
index 00000000000000..f199def81664e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_fashion_attribute_model_try_2_base32_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_fashion_attribute_model_try_2_base32 CLIPForZeroShotClassification from Geetansh13
+author: John Snow Labs
+name: clip_fashion_attribute_model_try_2_base32
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_fashion_attribute_model_try_2_base32` is a English model originally trained by Geetansh13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_fashion_attribute_model_try_2_base32_en_5.5.0_3.0_1725339240579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_fashion_attribute_model_try_2_base32_en_5.5.0_3.0_1725339240579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_fashion_attribute_model_try_2_base32","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_fashion_attribute_model_try_2_base32","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_fashion_attribute_model_try_2_base32|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|580.7 MB|
+
+## References
+
+https://huggingface.co/Geetansh13/clip-fashion-attribute-model-try-2-base32
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_general_copy_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_general_copy_en.md
new file mode 100644
index 00000000000000..b400156b8b6c14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_general_copy_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_general_copy CLIPForZeroShotClassification from vinluvie
+author: John Snow Labs
+name: clip_general_copy
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_general_copy` is a English model originally trained by vinluvie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_general_copy_en_5.5.0_3.0_1725339279140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_general_copy_en_5.5.0_3.0_1725339279140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_general_copy","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_general_copy","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_general_copy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/vinluvie/clip-general-copy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_general_copy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_general_copy_pipeline_en.md
new file mode 100644
index 00000000000000..cfb33a622d2777
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_general_copy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_general_copy_pipeline pipeline CLIPForZeroShotClassification from vinluvie
+author: John Snow Labs
+name: clip_general_copy_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_general_copy_pipeline` is a English model originally trained by vinluvie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_general_copy_pipeline_en_5.5.0_3.0_1725339355629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_general_copy_pipeline_en_5.5.0_3.0_1725339355629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_general_copy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_general_copy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_general_copy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/vinluvie/clip-general-copy
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo1_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo1_en.md
new file mode 100644
index 00000000000000..98825050dd47bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo1_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_base_patch32_demo1 CLIPForZeroShotClassification from rkolaghassi
+author: John Snow Labs
+name: clip_vit_base_patch32_demo1
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo1` is a English model originally trained by rkolaghassi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo1_en_5.5.0_3.0_1725339555120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo1_en_5.5.0_3.0_1725339555120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo1","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo1","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_demo1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/rkolaghassi/clip-vit-base-patch32-demo1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo1_pipeline_en.md
new file mode 100644
index 00000000000000..8244338b036a4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_base_patch32_demo1_pipeline pipeline CLIPForZeroShotClassification from rkolaghassi
+author: John Snow Labs
+name: clip_vit_base_patch32_demo1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo1_pipeline` is a English model originally trained by rkolaghassi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo1_pipeline_en_5.5.0_3.0_1725339649374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo1_pipeline_en_5.5.0_3.0_1725339649374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_base_patch32_demo1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_base_patch32_demo1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_demo1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/rkolaghassi/clip-vit-base-patch32-demo1
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo_vinayakvsv_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo_vinayakvsv_en.md
new file mode 100644
index 00000000000000..1e4cf1c645a7a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo_vinayakvsv_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_base_patch32_demo_vinayakvsv CLIPForZeroShotClassification from vinayakvsv
+author: John Snow Labs
+name: clip_vit_base_patch32_demo_vinayakvsv
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_vinayakvsv` is a English model originally trained by vinayakvsv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_vinayakvsv_en_5.5.0_3.0_1725339595655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_vinayakvsv_en_5.5.0_3.0_1725339595655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_vinayakvsv","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_vinayakvsv","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_demo_vinayakvsv|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/vinayakvsv/clip-vit-base-patch32-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo_vinayakvsv_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo_vinayakvsv_pipeline_en.md
new file mode 100644
index 00000000000000..acc6b43dd8a517
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_patch32_demo_vinayakvsv_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_base_patch32_demo_vinayakvsv_pipeline pipeline CLIPForZeroShotClassification from vinayakvsv
+author: John Snow Labs
+name: clip_vit_base_patch32_demo_vinayakvsv_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_vinayakvsv_pipeline` is a English model originally trained by vinayakvsv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_vinayakvsv_pipeline_en_5.5.0_3.0_1725339689216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_vinayakvsv_pipeline_en_5.5.0_3.0_1725339689216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_base_patch32_demo_vinayakvsv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_base_patch32_demo_vinayakvsv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_demo_vinayakvsv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/vinayakvsv/clip-vit-base-patch32-demo
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_pathc32_demo_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_pathc32_demo_en.md
new file mode 100644
index 00000000000000..c57afdef51256a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_base_pathc32_demo_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_base_pathc32_demo CLIPForZeroShotClassification from drn
+author: John Snow Labs
+name: clip_vit_base_pathc32_demo
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_pathc32_demo` is a English model originally trained by drn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_pathc32_demo_en_5.5.0_3.0_1725338608418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_pathc32_demo_en_5.5.0_3.0_1725338608418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_pathc32_demo","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_pathc32_demo","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_pathc32_demo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/drn/clip-vit-base-pathc32-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_baseplate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_baseplate_pipeline_en.md
new file mode 100644
index 00000000000000..3e0a8d5a0bddc2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_baseplate_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_large_patch14_baseplate_pipeline pipeline CLIPForZeroShotClassification from baseplate
+author: John Snow Labs
+name: clip_vit_large_patch14_baseplate_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_baseplate_pipeline` is a English model originally trained by baseplate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_baseplate_pipeline_en_5.5.0_3.0_1725339200377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_baseplate_pipeline_en_5.5.0_3.0_1725339200377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_large_patch14_baseplate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_large_patch14_baseplate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_large_patch14_baseplate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/baseplate/clip-vit-large-patch14
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_krnl_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_krnl_pipeline_en.md
new file mode 100644
index 00000000000000..da04308715aed3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_large_patch14_krnl_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_large_patch14_krnl_pipeline pipeline CLIPForZeroShotClassification from krnl
+author: John Snow Labs
+name: clip_vit_large_patch14_krnl_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_krnl_pipeline` is a English model originally trained by krnl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_krnl_pipeline_en_5.5.0_3.0_1725339620720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_krnl_pipeline_en_5.5.0_3.0_1725339620720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_large_patch14_krnl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_large_patch14_krnl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_large_patch14_krnl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/krnl/clip-vit-large-patch14
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-clip_vit_tjklein_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_tjklein_pipeline_en.md
new file mode 100644
index 00000000000000..1dd9c0171ff266
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-clip_vit_tjklein_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_tjklein_pipeline pipeline CLIPForZeroShotClassification from TJKlein
+author: John Snow Labs
+name: clip_vit_tjklein_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_tjklein_pipeline` is a English model originally trained by TJKlein.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_tjklein_pipeline_en_5.5.0_3.0_1725339579509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_tjklein_pipeline_en_5.5.0_3.0_1725339579509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_tjklein_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_tjklein_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_tjklein_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/TJKlein/CLIP-ViT
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-coptic_english_translator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-coptic_english_translator_pipeline_en.md
new file mode 100644
index 00000000000000..ad63eb8198fb74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-coptic_english_translator_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English coptic_english_translator_pipeline pipeline MarianTransformer from megalaa
+author: John Snow Labs
+name: coptic_english_translator_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`coptic_english_translator_pipeline` is a English model originally trained by megalaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/coptic_english_translator_pipeline_en_5.5.0_3.0_1725346279930.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/coptic_english_translator_pipeline_en_5.5.0_3.0_1725346279930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("coptic_english_translator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("coptic_english_translator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|coptic_english_translator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|533.1 MB|
+
+## References
+
+https://huggingface.co/megalaa/coptic-english-translator
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_en.md b/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_en.md
new file mode 100644
index 00000000000000..cd69bc3a468b2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cross_all_bs160_allneg_finetuned_webnlg2020_metric_average MPNetEmbeddings from teven
+author: John Snow Labs
+name: cross_all_bs160_allneg_finetuned_webnlg2020_metric_average
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_bs160_allneg_finetuned_webnlg2020_metric_average` is a English model originally trained by teven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_en_5.5.0_3.0_1725350617941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_en_5.5.0_3.0_1725350617941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("cross_all_bs160_allneg_finetuned_webnlg2020_metric_average","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("cross_all_bs160_allneg_finetuned_webnlg2020_metric_average","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_all_bs160_allneg_finetuned_webnlg2020_metric_average|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/cross_all_bs160_allneg_finetuned_WebNLG2020_metric_average
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline_en.md
new file mode 100644
index 00000000000000..00fba1fc0e7132
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline pipeline MPNetEmbeddings from teven
+author: John Snow Labs
+name: cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline` is a English model originally trained by teven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline_en_5.5.0_3.0_1725350637994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline_en_5.5.0_3.0_1725350637994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_all_bs160_allneg_finetuned_webnlg2020_metric_average_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/cross_all_bs160_allneg_finetuned_WebNLG2020_metric_average
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_en.md b/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_en.md
new file mode 100644
index 00000000000000..e5362e84749433
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cross_all_bs192_hardneg_finetuned_webnlg2020_correctness MPNetEmbeddings from teven
+author: John Snow Labs
+name: cross_all_bs192_hardneg_finetuned_webnlg2020_correctness
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_bs192_hardneg_finetuned_webnlg2020_correctness` is a English model originally trained by teven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_en_5.5.0_3.0_1725350722553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_en_5.5.0_3.0_1725350722553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("cross_all_bs192_hardneg_finetuned_webnlg2020_correctness","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("cross_all_bs192_hardneg_finetuned_webnlg2020_correctness","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_all_bs192_hardneg_finetuned_webnlg2020_correctness|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/cross_all_bs192_hardneg_finetuned_WebNLG2020_correctness
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline_en.md
new file mode 100644
index 00000000000000..df470a891469fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline pipeline MPNetEmbeddings from teven
+author: John Snow Labs
+name: cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline` is a English model originally trained by teven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline_en_5.5.0_3.0_1725350743223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline_en_5.5.0_3.0_1725350743223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_all_bs192_hardneg_finetuned_webnlg2020_correctness_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/cross_all_bs192_hardneg_finetuned_WebNLG2020_correctness
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_base_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_base_mmarcofr_fr.md
new file mode 100644
index 00000000000000..eeae64afe6348c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_base_mmarcofr_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French crossencoder_camembert_base_mmarcofr CamemBertForSequenceClassification from antoinelouis
+author: John Snow Labs
+name: crossencoder_camembert_base_mmarcofr
+date: 2024-09-03
+tags: [fr, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_base_mmarcofr` is a French model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_base_mmarcofr_fr_5.5.0_3.0_1725378162527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_base_mmarcofr_fr_5.5.0_3.0_1725378162527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_base_mmarcofr","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_base_mmarcofr", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crossencoder_camembert_base_mmarcofr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|414.7 MB|
+
+## References
+
+https://huggingface.co/antoinelouis/crossencoder-camembert-base-mmarcoFR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l4_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l4_mmarcofr_fr.md
new file mode 100644
index 00000000000000..32a2313bc68ef6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_l4_mmarcofr_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French crossencoder_camembert_l4_mmarcofr CamemBertForSequenceClassification from antoinelouis
+author: John Snow Labs
+name: crossencoder_camembert_l4_mmarcofr
+date: 2024-09-03
+tags: [fr, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_l4_mmarcofr` is a French model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l4_mmarcofr_fr_5.5.0_3.0_1725378338368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_l4_mmarcofr_fr_5.5.0_3.0_1725378338368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_l4_mmarcofr","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_l4_mmarcofr", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crossencoder_camembert_l4_mmarcofr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|202.1 MB|
+
+## References
+
+https://huggingface.co/antoinelouis/crossencoder-camembert-L4-mmarcoFR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_large_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_large_mmarcofr_fr.md
new file mode 100644
index 00000000000000..c7002c4a6bfba9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_large_mmarcofr_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French crossencoder_camembert_large_mmarcofr CamemBertForSequenceClassification from antoinelouis
+author: John Snow Labs
+name: crossencoder_camembert_large_mmarcofr
+date: 2024-09-03
+tags: [fr, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_large_mmarcofr` is a French model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_large_mmarcofr_fr_5.5.0_3.0_1725378144416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_large_mmarcofr_fr_5.5.0_3.0_1725378144416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_large_mmarcofr","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_camembert_large_mmarcofr", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crossencoder_camembert_large_mmarcofr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/antoinelouis/crossencoder-camembert-large-mmarcoFR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_large_mmarcofr_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_large_mmarcofr_pipeline_fr.md
new file mode 100644
index 00000000000000..ed4186c36fb210
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_camembert_large_mmarcofr_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French crossencoder_camembert_large_mmarcofr_pipeline pipeline CamemBertForSequenceClassification from antoinelouis
+author: John Snow Labs
+name: crossencoder_camembert_large_mmarcofr_pipeline
+date: 2024-09-03
+tags: [fr, open_source, pipeline, onnx]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_camembert_large_mmarcofr_pipeline` is a French model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_large_mmarcofr_pipeline_fr_5.5.0_3.0_1725378226452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_camembert_large_mmarcofr_pipeline_fr_5.5.0_3.0_1725378226452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("crossencoder_camembert_large_mmarcofr_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("crossencoder_camembert_large_mmarcofr_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crossencoder_camembert_large_mmarcofr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/antoinelouis/crossencoder-camembert-large-mmarcoFR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-crossencoder_xlm_roberta_base_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_xlm_roberta_base_mmarcofr_fr.md
new file mode 100644
index 00000000000000..d091247fe7f446
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-crossencoder_xlm_roberta_base_mmarcofr_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French crossencoder_xlm_roberta_base_mmarcofr XlmRoBertaForSequenceClassification from antoinelouis
+author: John Snow Labs
+name: crossencoder_xlm_roberta_base_mmarcofr
+date: 2024-09-03
+tags: [fr, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_xlm_roberta_base_mmarcofr` is a French model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_xlm_roberta_base_mmarcofr_fr_5.5.0_3.0_1725396048298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_xlm_roberta_base_mmarcofr_fr_5.5.0_3.0_1725396048298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("crossencoder_xlm_roberta_base_mmarcofr","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("crossencoder_xlm_roberta_base_mmarcofr", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crossencoder_xlm_roberta_base_mmarcofr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|853.6 MB|
+
+## References
+
+https://huggingface.co/antoinelouis/crossencoder-xlm-roberta-base-mmarcoFR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-crowdedflowertunedbertt_en.md b/docs/_posts/ahmedlone127/2024-09-03-crowdedflowertunedbertt_en.md
new file mode 100644
index 00000000000000..6ad87a8ab6ce45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-crowdedflowertunedbertt_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English crowdedflowertunedbertt MPNetEmbeddings from tubyneto
+author: John Snow Labs
+name: crowdedflowertunedbertt
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crowdedflowertunedbertt` is a English model originally trained by tubyneto.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crowdedflowertunedbertt_en_5.5.0_3.0_1725350511813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crowdedflowertunedbertt_en_5.5.0_3.0_1725350511813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("crowdedflowertunedbertt","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("crowdedflowertunedbertt","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crowdedflowertunedbertt|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/tubyneto/crowdedflowertunedbertt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-crowdedflowertunedbertt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-crowdedflowertunedbertt_pipeline_en.md
new file mode 100644
index 00000000000000..7544263648223e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-crowdedflowertunedbertt_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English crowdedflowertunedbertt_pipeline pipeline MPNetEmbeddings from tubyneto
+author: John Snow Labs
+name: crowdedflowertunedbertt_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crowdedflowertunedbertt_pipeline` is a English model originally trained by tubyneto.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crowdedflowertunedbertt_pipeline_en_5.5.0_3.0_1725350533406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crowdedflowertunedbertt_pipeline_en_5.5.0_3.0_1725350533406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("crowdedflowertunedbertt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("crowdedflowertunedbertt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crowdedflowertunedbertt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/tubyneto/crowdedflowertunedbertt
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cultural_heritage_metadata_accuracy_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-03-cultural_heritage_metadata_accuracy_mnli_en.md
new file mode 100644
index 00000000000000..1a200fc40f7054
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cultural_heritage_metadata_accuracy_mnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cultural_heritage_metadata_accuracy_mnli XlmRoBertaForSequenceClassification from davanstrien
+author: John Snow Labs
+name: cultural_heritage_metadata_accuracy_mnli
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cultural_heritage_metadata_accuracy_mnli` is a English model originally trained by davanstrien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cultural_heritage_metadata_accuracy_mnli_en_5.5.0_3.0_1725396291182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cultural_heritage_metadata_accuracy_mnli_en_5.5.0_3.0_1725396291182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("cultural_heritage_metadata_accuracy_mnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("cultural_heritage_metadata_accuracy_mnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cultural_heritage_metadata_accuracy_mnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|807.5 MB|
+
+## References
+
+https://huggingface.co/davanstrien/cultural_heritage_metadata_accuracy_mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-custom_bge_en.md b/docs/_posts/ahmedlone127/2024-09-03-custom_bge_en.md
new file mode 100644
index 00000000000000..d6f806daaaffeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-custom_bge_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English custom_bge BGEEmbeddings from rnbokade
+author: John Snow Labs
+name: custom_bge
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_bge` is a English model originally trained by rnbokade.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_bge_en_5.5.0_3.0_1725357230040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_bge_en_5.5.0_3.0_1725357230040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("custom_bge","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("custom_bge","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_bge|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/rnbokade/custom-bge
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-custom_bge_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-custom_bge_pipeline_en.md
new file mode 100644
index 00000000000000..78014357fb595c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-custom_bge_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English custom_bge_pipeline pipeline BGEEmbeddings from rnbokade
+author: John Snow Labs
+name: custom_bge_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_bge_pipeline` is a English model originally trained by rnbokade.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_bge_pipeline_en_5.5.0_3.0_1725357311301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_bge_pipeline_en_5.5.0_3.0_1725357311301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_bge_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_bge_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_bge_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/rnbokade/custom-bge
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-custom_clip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-custom_clip_pipeline_en.md
new file mode 100644
index 00000000000000..c31c64c854a8cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-custom_clip_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English custom_clip_pipeline pipeline CLIPForZeroShotClassification from gokuls
+author: John Snow Labs
+name: custom_clip_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_clip_pipeline` is a English model originally trained by gokuls.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_clip_pipeline_en_5.5.0_3.0_1725338151718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_clip_pipeline_en_5.5.0_3.0_1725338151718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_clip_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_clip_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_clip_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|567.3 MB|
+
+## References
+
+https://huggingface.co/gokuls/custom_clip
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-custom_mpnet_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-custom_mpnet_base_v2_pipeline_en.md
new file mode 100644
index 00000000000000..a90ee29f438b26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-custom_mpnet_base_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English custom_mpnet_base_v2_pipeline pipeline MPNetEmbeddings from 17nshul
+author: John Snow Labs
+name: custom_mpnet_base_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_mpnet_base_v2_pipeline` is a English model originally trained by 17nshul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725350352780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725350352780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_mpnet_base_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_mpnet_base_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_mpnet_base_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/17nshul/custom-mpnet-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cybertuned_securityllm_en.md b/docs/_posts/ahmedlone127/2024-09-03-cybertuned_securityllm_en.md
new file mode 100644
index 00000000000000..c060fbc53a0601
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cybertuned_securityllm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cybertuned_securityllm RoBertaEmbeddings from s2w-ai
+author: John Snow Labs
+name: cybertuned_securityllm
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybertuned_securityllm` is a English model originally trained by s2w-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybertuned_securityllm_en_5.5.0_3.0_1725374576329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybertuned_securityllm_en_5.5.0_3.0_1725374576329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("cybertuned_securityllm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("cybertuned_securityllm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybertuned_securityllm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/s2w-ai/CyBERTuned-SecurityLLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-cybertuned_securityllm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-cybertuned_securityllm_pipeline_en.md
new file mode 100644
index 00000000000000..6c4340741f94b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-cybertuned_securityllm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cybertuned_securityllm_pipeline pipeline RoBertaEmbeddings from s2w-ai
+author: John Snow Labs
+name: cybertuned_securityllm_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybertuned_securityllm_pipeline` is a English model originally trained by s2w-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybertuned_securityllm_pipeline_en_5.5.0_3.0_1725374601176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybertuned_securityllm_pipeline_en_5.5.0_3.0_1725374601176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cybertuned_securityllm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cybertuned_securityllm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybertuned_securityllm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/s2w-ai/CyBERTuned-SecurityLLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-danish_ned_base_da.md b/docs/_posts/ahmedlone127/2024-09-03-danish_ned_base_da.md
new file mode 100644
index 00000000000000..3a6d74eb4441b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-danish_ned_base_da.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Danish danish_ned_base XlmRoBertaForSequenceClassification from alexandrainst
+author: John Snow Labs
+name: danish_ned_base
+date: 2024-09-03
+tags: [da, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_ned_base` is a Danish model originally trained by alexandrainst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_ned_base_da_5.5.0_3.0_1725395303594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_ned_base_da_5.5.0_3.0_1725395303594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("danish_ned_base","da") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("danish_ned_base", "da")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_ned_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|da|
+|Size:|881.6 MB|
+
+## References
+
+https://huggingface.co/alexandrainst/da-ned-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-danish_ned_base_pipeline_da.md b/docs/_posts/ahmedlone127/2024-09-03-danish_ned_base_pipeline_da.md
new file mode 100644
index 00000000000000..5915a8ddccf72f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-danish_ned_base_pipeline_da.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Danish danish_ned_base_pipeline pipeline XlmRoBertaForSequenceClassification from alexandrainst
+author: John Snow Labs
+name: danish_ned_base_pipeline
+date: 2024-09-03
+tags: [da, open_source, pipeline, onnx]
+task: Text Classification
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_ned_base_pipeline` is a Danish model originally trained by alexandrainst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_ned_base_pipeline_da_5.5.0_3.0_1725395385865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_ned_base_pipeline_da_5.5.0_3.0_1725395385865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("danish_ned_base_pipeline", lang = "da")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("danish_ned_base_pipeline", lang = "da")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_ned_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|da|
+|Size:|881.6 MB|
+
+## References
+
+https://huggingface.co/alexandrainst/da-ned-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-danish_sentiment_da.md b/docs/_posts/ahmedlone127/2024-09-03-danish_sentiment_da.md
new file mode 100644
index 00000000000000..41d3cdfaa533c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-danish_sentiment_da.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Danish danish_sentiment XlmRoBertaForSequenceClassification from vesteinn
+author: John Snow Labs
+name: danish_sentiment
+date: 2024-09-03
+tags: [da, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_sentiment` is a Danish model originally trained by vesteinn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_sentiment_da_5.5.0_3.0_1725395723829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_sentiment_da_5.5.0_3.0_1725395723829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("danish_sentiment","da") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("danish_sentiment", "da")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|da|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/vesteinn/danish_sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-danish_sentiment_pipeline_da.md b/docs/_posts/ahmedlone127/2024-09-03-danish_sentiment_pipeline_da.md
new file mode 100644
index 00000000000000..265b0f66458393
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-danish_sentiment_pipeline_da.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Danish danish_sentiment_pipeline pipeline XlmRoBertaForSequenceClassification from vesteinn
+author: John Snow Labs
+name: danish_sentiment_pipeline
+date: 2024-09-03
+tags: [da, open_source, pipeline, onnx]
+task: Text Classification
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_sentiment_pipeline` is a Danish model originally trained by vesteinn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_sentiment_pipeline_da_5.5.0_3.0_1725395785651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_sentiment_pipeline_da_5.5.0_3.0_1725395785651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("danish_sentiment_pipeline", lang = "da")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("danish_sentiment_pipeline", lang = "da")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|da|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/vesteinn/danish_sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dataequity_opus_maltese_german_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-dataequity_opus_maltese_german_english_en.md
new file mode 100644
index 00000000000000..d8a1c63afcdd20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dataequity_opus_maltese_german_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dataequity_opus_maltese_german_english MarianTransformer from dataequity
+author: John Snow Labs
+name: dataequity_opus_maltese_german_english
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dataequity_opus_maltese_german_english` is a English model originally trained by dataequity.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dataequity_opus_maltese_german_english_en_5.5.0_3.0_1725345849323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dataequity_opus_maltese_german_english_en_5.5.0_3.0_1725345849323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("dataequity_opus_maltese_german_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("dataequity_opus_maltese_german_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dataequity_opus_maltese_german_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|499.4 MB|
+
+## References
+
+https://huggingface.co/dataequity/dataequity-opus-mt-de-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-db_aca_5_3_en.md b/docs/_posts/ahmedlone127/2024-09-03-db_aca_5_3_en.md
new file mode 100644
index 00000000000000..224a8ae44bf3ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-db_aca_5_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_aca_5_3 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_aca_5_3
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_aca_5_3` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_aca_5_3_en_5.5.0_3.0_1725329906903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_aca_5_3_en_5.5.0_3.0_1725329906903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_aca_5_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_aca_5_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_aca_5_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/exala/db_aca_5.3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-db_aca_5_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-db_aca_5_3_pipeline_en.md
new file mode 100644
index 00000000000000..d31e262bac537b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-db_aca_5_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_aca_5_3_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_aca_5_3_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_aca_5_3_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_aca_5_3_pipeline_en_5.5.0_3.0_1725329919457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_aca_5_3_pipeline_en_5.5.0_3.0_1725329919457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_aca_5_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_aca_5_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_aca_5_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/exala/db_aca_5.3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_en.md
new file mode 100644
index 00000000000000..c45a39df538c4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English Deberta Embeddings model (from totoro4007)
+author: John Snow Labs
+name: deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli
+date: 2024-09-03
+tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, en, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `MLM-tuned-DeBERTa-v3-large-mnli-fever-anli-ling-wanli` is a English model originally trained by `totoro4007`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_en_5.5.0_3.0_1725376808377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_en_5.5.0_3.0_1725376808377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli","vie") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("embeddings") \
+    .setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli","vie")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("embeddings")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("I love Spark NLP").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+References
+
+https://huggingface.co/totoro4007/MLM-tuned-DeBERTa-v3-large-mnli-fever-anli-ling-wanli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline_en.md
new file mode 100644
index 00000000000000..c4b95bf9fdef26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline pipeline DeBertaEmbeddings from totoro4007
+author: John Snow Labs
+name: deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline` is a English model originally trained by totoro4007.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline_en_5.5.0_3.0_1725376889591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline_en_5.5.0_3.0_1725376889591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_embeddings_mlm_tuned_v3_large_mnli_fever_anli_ling_wanli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/totoro4007/MLM-tuned-DeBERTa-v3-large-mnli-fever-anli-ling-wanli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_nbme_V3_large_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_nbme_V3_large_en.md
new file mode 100644
index 00000000000000..0532c54e2bd0a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_nbme_V3_large_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English Deberta Embeddings model (from smeoni)
+author: John Snow Labs
+name: deberta_embeddings_nbme_V3_large
+date: 2024-09-03
+tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, en, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `nbme-deberta-V3-large` is a English model originally trained by `smeoni`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_nbme_V3_large_en_5.5.0_3.0_1725330996786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_nbme_V3_large_en_5.5.0_3.0_1725330996786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_nbme_V3_large","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("embeddings") \
+    .setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_nbme_V3_large","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("embeddings")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("I love Spark NLP").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_embeddings_nbme_V3_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+References
+
+https://huggingface.co/smeoni/nbme-deberta-V3-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_base_lm_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_base_lm_en.md
new file mode 100644
index 00000000000000..297917c300f637
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_embeddings_v3_base_lm_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English Deberta Embeddings model (from iewaij)
+author: John Snow Labs
+name: deberta_embeddings_v3_base_lm
+date: 2024-09-03
+tags: [deberta, open_source, deberta_embeddings, debertav2formaskedlm, en, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `deberta-v3-base-lm` is a English model originally trained by `iewaij`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_base_lm_en_5.5.0_3.0_1725331009679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_embeddings_v3_base_lm_en_5.5.0_3.0_1725331009679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_v3_base_lm","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("embeddings") \
+    .setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_v3_base_lm","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("embeddings")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("I love Spark NLP").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_embeddings_v3_base_lm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|en|
+|Size:|689.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/iewaij/deberta-v3-base-lm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_ft_fm_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_ft_fm_en.md
new file mode 100644
index 00000000000000..500963beef7ed8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_ft_fm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_ft_fm DeBertaForTokenClassification from codeaze
+author: John Snow Labs
+name: deberta_ft_fm
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_ft_fm` is a English model originally trained by codeaze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_ft_fm_en_5.5.0_3.0_1725401375399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_ft_fm_en_5.5.0_3.0_1725401375399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_ft_fm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_ft_fm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_ft_fm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/codeaze/deberta_FT_FM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_ft_fm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_ft_fm_pipeline_en.md
new file mode 100644
index 00000000000000..067941de604374
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_ft_fm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_ft_fm_pipeline pipeline DeBertaForTokenClassification from codeaze
+author: John Snow Labs
+name: deberta_ft_fm_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_ft_fm_pipeline` is a English model originally trained by codeaze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_ft_fm_pipeline_en_5.5.0_3.0_1725401471888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_ft_fm_pipeline_en_5.5.0_3.0_1725401471888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_ft_fm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_ft_fm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_ft_fm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/codeaze/deberta_FT_FM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_large_metaphor_detection_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_large_metaphor_detection_english_en.md
new file mode 100644
index 00000000000000..ce98c4b48f89e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_large_metaphor_detection_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_large_metaphor_detection_english DeBertaForTokenClassification from HiTZ
+author: John Snow Labs
+name: deberta_large_metaphor_detection_english
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_large_metaphor_detection_english` is a English model originally trained by HiTZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_large_metaphor_detection_english_en_5.5.0_3.0_1725401467749.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_large_metaphor_detection_english_en_5.5.0_3.0_1725401467749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_large_metaphor_detection_english","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_large_metaphor_detection_english", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_large_metaphor_detection_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/HiTZ/deberta-large-metaphor-detection-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_large_metaphor_detection_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_large_metaphor_detection_english_pipeline_en.md
new file mode 100644
index 00000000000000..c67d94ba302015
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_large_metaphor_detection_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_large_metaphor_detection_english_pipeline pipeline DeBertaForTokenClassification from HiTZ
+author: John Snow Labs
+name: deberta_large_metaphor_detection_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_large_metaphor_detection_english_pipeline` is a English model originally trained by HiTZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_large_metaphor_detection_english_pipeline_en_5.5.0_3.0_1725401564575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_large_metaphor_detection_english_pipeline_en_5.5.0_3.0_1725401564575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_large_metaphor_detection_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_large_metaphor_detection_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_large_metaphor_detection_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/HiTZ/deberta-large-metaphor-detection-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_mlm_feedback_1024_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_mlm_feedback_1024_en.md
new file mode 100644
index 00000000000000..309933df78a2ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_mlm_feedback_1024_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_mlm_feedback_1024 DeBertaEmbeddings from TTian
+author: John Snow Labs
+name: deberta_mlm_feedback_1024
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, deberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_mlm_feedback_1024` is a English model originally trained by TTian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_mlm_feedback_1024_en_5.5.0_3.0_1725377253279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_mlm_feedback_1024_en_5.5.0_3.0_1725377253279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("deberta_mlm_feedback_1024","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("deberta_mlm_feedback_1024","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_mlm_feedback_1024|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/TTian/deberta-mlm-feedback-1024
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_finetuned_ner_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_finetuned_ner_ja.md
new file mode 100644
index 00000000000000..8e2af631316ca7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_finetuned_ner_ja.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Japanese deberta_v2_base_japanese_finetuned_ner DeBertaForTokenClassification from Mizuiro-sakura
+author: John Snow Labs
+name: deberta_v2_base_japanese_finetuned_ner
+date: 2024-09-03
+tags: [ja, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_base_japanese_finetuned_ner` is a Japanese model originally trained by Mizuiro-sakura.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_ner_ja_5.5.0_3.0_1725387955429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_ner_ja_5.5.0_3.0_1725387955429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v2_base_japanese_finetuned_ner","ja") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v2_base_japanese_finetuned_ner", "ja")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v2_base_japanese_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ja|
+|Size:|419.0 MB|
+
+## References
+
+https://huggingface.co/Mizuiro-sakura/deberta-v2-base-japanese-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_finetuned_ner_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_finetuned_ner_pipeline_ja.md
new file mode 100644
index 00000000000000..b480c26330dfed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v2_base_japanese_finetuned_ner_pipeline_ja.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Japanese deberta_v2_base_japanese_finetuned_ner_pipeline pipeline DeBertaForTokenClassification from Mizuiro-sakura
+author: John Snow Labs
+name: deberta_v2_base_japanese_finetuned_ner_pipeline
+date: 2024-09-03
+tags: [ja, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_base_japanese_finetuned_ner_pipeline` is a Japanese model originally trained by Mizuiro-sakura.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_ner_pipeline_ja_5.5.0_3.0_1725387977740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_ner_pipeline_ja_5.5.0_3.0_1725387977740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v2_base_japanese_finetuned_ner_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v2_base_japanese_finetuned_ner_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v2_base_japanese_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|419.1 MB|
+
+## References
+
+https://huggingface.co/Mizuiro-sakura/deberta-v2-base-japanese-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,77 @@
+---
+layout: model
+title: DeBERTa base model
+author: John Snow Labs
+name: deberta_v3_base
+date: 2024-09-03
+tags: [en, english, open_source, embeddings, deberta, v3, base, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+The DeBERTa model was proposed in [[https://arxiv.org/abs/2006.03654 DeBERTa: Decoding-enhanced BERT with Disentangled Attention]] by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen It is based on Google’s BERT model released in 2018 and Facebook’s RoBERTa model released in 2019. Compared to RoBERTa-Large, a DeBERTa model trained on half of the training data performs consistently better on a wide range of NLP tasks, achieving improvements on MNLI by +0.9% (90.2% vs. 91.1%), on SQuAD v2.0 by +2.3% (88.4% vs. 90.7%) and RACE by +3.6% (83.2% vs. 86.8%).
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_en_5.5.0_3.0_1725400399037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_en_5.5.0_3.0_1725400399037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+embeddings = DeBertaEmbeddings.pretrained("deberta_v3_base", "en") \
+.setInputCols("sentence", "token") \
+.setOutputCol("embeddings")
+```
+```scala
+val embeddings = DeBertaEmbeddings.pretrained("deberta_v3_base", "en")
+.setInputCols("sentence", "token")
+.setOutputCol("embeddings")
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.embed.deberta_v3_base").predict("""Put your text here.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|687.7 MB|
+
+## Benchmarking
+
+```bash
+
+Benchmarking
+```
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_finetuned_ai4privacy_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_finetuned_ai4privacy_v2_en.md
new file mode 100644
index 00000000000000..7f822321de0798
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_finetuned_ai4privacy_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_ai4privacy_v2 DeBertaForTokenClassification from Isotonic
+author: John Snow Labs
+name: deberta_v3_base_finetuned_ai4privacy_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_ai4privacy_v2` is a English model originally trained by Isotonic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_ai4privacy_v2_en_5.5.0_3.0_1725387714236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_ai4privacy_v2_en_5.5.0_3.0_1725387714236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_base_finetuned_ai4privacy_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_finetuned_ai4privacy_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_ai4privacy_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|587.9 MB|
+
+## References
+
+https://huggingface.co/Isotonic/deberta-v3-base_finetuned_ai4privacy_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_finetuned_ai4privacy_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_finetuned_ai4privacy_v2_pipeline_en.md
new file mode 100644
index 00000000000000..d1b20d7ee691fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_base_finetuned_ai4privacy_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_ai4privacy_v2_pipeline pipeline DeBertaForTokenClassification from Isotonic
+author: John Snow Labs
+name: deberta_v3_base_finetuned_ai4privacy_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_ai4privacy_v2_pipeline` is a English model originally trained by Isotonic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_ai4privacy_v2_pipeline_en_5.5.0_3.0_1725387760561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_ai4privacy_v2_pipeline_en_5.5.0_3.0_1725387760561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_finetuned_ai4privacy_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_ai4privacy_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_ai4privacy_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|587.9 MB|
+
+## References
+
+https://huggingface.co/Isotonic/deberta-v3-base_finetuned_ai4privacy_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_large_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_large_ja.md
new file mode 100644
index 00000000000000..1409aa20435942
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_large_ja.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Japanese deberta_v3_japanese_large DeBertaForTokenClassification from globis-university
+author: John Snow Labs
+name: deberta_v3_japanese_large
+date: 2024-09-03
+tags: [ja, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_japanese_large` is a Japanese model originally trained by globis-university.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_japanese_large_ja_5.5.0_3.0_1725388693987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_japanese_large_ja_5.5.0_3.0_1725388693987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_japanese_large","ja") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_japanese_large", "ja")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_japanese_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ja|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/globis-university/deberta-v3-japanese-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_large_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_large_pipeline_ja.md
new file mode 100644
index 00000000000000..8872d369022cda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_large_pipeline_ja.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Japanese deberta_v3_japanese_large_pipeline pipeline DeBertaForTokenClassification from globis-university
+author: John Snow Labs
+name: deberta_v3_japanese_large_pipeline
+date: 2024-09-03
+tags: [ja, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_japanese_large_pipeline` is a Japanese model originally trained by globis-university.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_japanese_large_pipeline_ja_5.5.0_3.0_1725388767436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_japanese_large_pipeline_ja_5.5.0_3.0_1725388767436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_japanese_large_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_japanese_large_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_japanese_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/globis-university/deberta-v3-japanese-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_xsmall_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_xsmall_ja.md
new file mode 100644
index 00000000000000..7d5f35cbfe24be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_xsmall_ja.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Japanese deberta_v3_japanese_xsmall DeBertaForTokenClassification from globis-university
+author: John Snow Labs
+name: deberta_v3_japanese_xsmall
+date: 2024-09-03
+tags: [ja, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_japanese_xsmall` is a Japanese model originally trained by globis-university.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_japanese_xsmall_ja_5.5.0_3.0_1725388577139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_japanese_xsmall_ja_5.5.0_3.0_1725388577139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_japanese_xsmall","ja") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_japanese_xsmall", "ja")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_japanese_xsmall|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ja|
+|Size:|126.7 MB|
+
+## References
+
+https://huggingface.co/globis-university/deberta-v3-japanese-xsmall
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_xsmall_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_xsmall_pipeline_ja.md
new file mode 100644
index 00000000000000..0eae463ef1a777
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_japanese_xsmall_pipeline_ja.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Japanese deberta_v3_japanese_xsmall_pipeline pipeline DeBertaForTokenClassification from globis-university
+author: John Snow Labs
+name: deberta_v3_japanese_xsmall_pipeline
+date: 2024-09-03
+tags: [ja, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_japanese_xsmall_pipeline` is a Japanese model originally trained by globis-university.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_japanese_xsmall_pipeline_ja_5.5.0_3.0_1725388583420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_japanese_xsmall_pipeline_ja_5.5.0_3.0_1725388583420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_japanese_xsmall_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_japanese_xsmall_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_japanese_xsmall_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|126.7 MB|
+
+## References
+
+https://huggingface.co/globis-university/deberta-v3-japanese-xsmall
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_conll2003_breast_castellon_v1_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_conll2003_breast_castellon_v1_en.md
new file mode 100644
index 00000000000000..6f456d87bde6c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_conll2003_breast_castellon_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_conll2003_breast_castellon_v1 DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: deberta_v3_large_conll2003_breast_castellon_v1
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_conll2003_breast_castellon_v1` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_conll2003_breast_castellon_v1_en_5.5.0_3.0_1725388445615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_conll2003_breast_castellon_v1_en_5.5.0_3.0_1725388445615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_conll2003_breast_castellon_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_conll2003_breast_castellon_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_conll2003_breast_castellon_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/deberta-v3-large_conll2003_breast-castellon-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline_en.md
new file mode 100644
index 00000000000000..e078d453fe8a2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline pipeline DeBertaEmbeddings from quastrinos
+author: John Snow Labs
+name: deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline` is a English model originally trained by quastrinos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline_en_5.5.0_3.0_1725376610320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline_en_5.5.0_3.0_1725376610320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_mlm_accelerate_v3_02_xp_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/quastrinos/deberta-v3-large-finetuned-mlm-accelerate-v3-02-xp-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_10epochs_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_10epochs_en.md
new file mode 100644
index 00000000000000..b79f79b7ba2c85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_10epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_ner_10epochs DeBertaForTokenClassification from ABrinkmann
+author: John Snow Labs
+name: deberta_v3_large_finetuned_ner_10epochs
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_ner_10epochs` is a English model originally trained by ABrinkmann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_10epochs_en_5.5.0_3.0_1725387611448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_10epochs_en_5.5.0_3.0_1725387611448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_finetuned_ner_10epochs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_finetuned_ner_10epochs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_ner_10epochs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ABrinkmann/deberta-v3-large-finetuned-ner-10epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_10epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_10epochs_pipeline_en.md
new file mode 100644
index 00000000000000..cee7f987c86fc2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_10epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_ner_10epochs_pipeline pipeline DeBertaForTokenClassification from ABrinkmann
+author: John Snow Labs
+name: deberta_v3_large_finetuned_ner_10epochs_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_ner_10epochs_pipeline` is a English model originally trained by ABrinkmann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_10epochs_pipeline_en_5.5.0_3.0_1725387696706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_10epochs_pipeline_en_5.5.0_3.0_1725387696706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_finetuned_ner_10epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_ner_10epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_ner_10epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ABrinkmann/deberta-v3-large-finetuned-ner-10epochs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_ktgiahieu_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_ktgiahieu_en.md
new file mode 100644
index 00000000000000..453bba6d25cd5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_ktgiahieu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_ner_ktgiahieu DeBertaForTokenClassification from ktgiahieu
+author: John Snow Labs
+name: deberta_v3_large_finetuned_ner_ktgiahieu
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_ner_ktgiahieu` is a English model originally trained by ktgiahieu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_ktgiahieu_en_5.5.0_3.0_1725388338435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_ktgiahieu_en_5.5.0_3.0_1725388338435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_finetuned_ner_ktgiahieu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_finetuned_ner_ktgiahieu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_ner_ktgiahieu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ktgiahieu/deberta-v3-large-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_ktgiahieu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_ktgiahieu_pipeline_en.md
new file mode 100644
index 00000000000000..64799f09756ee8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_finetuned_ner_ktgiahieu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_ner_ktgiahieu_pipeline pipeline DeBertaForTokenClassification from ktgiahieu
+author: John Snow Labs
+name: deberta_v3_large_finetuned_ner_ktgiahieu_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_ner_ktgiahieu_pipeline` is a English model originally trained by ktgiahieu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_ktgiahieu_pipeline_en_5.5.0_3.0_1725388441379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_ktgiahieu_pipeline_en_5.5.0_3.0_1725388441379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_finetuned_ner_ktgiahieu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_ner_ktgiahieu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_ner_ktgiahieu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ktgiahieu/deberta-v3-large-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_hf_llm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_hf_llm_pipeline_en.md
new file mode 100644
index 00000000000000..5077584ee94826
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_hf_llm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_hf_llm_pipeline pipeline DeBertaEmbeddings from nagupv
+author: John Snow Labs
+name: deberta_v3_large_hf_llm_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_hf_llm_pipeline` is a English model originally trained by nagupv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_hf_llm_pipeline_en_5.5.0_3.0_1725377673120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_hf_llm_pipeline_en_5.5.0_3.0_1725377673120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_hf_llm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_hf_llm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_hf_llm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/nagupv/deberta-v3-large-hf-llm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_ontonotes5_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_ontonotes5_en.md
new file mode 100644
index 00000000000000..7d3539b78e914a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_ontonotes5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_ontonotes5 DeBertaForTokenClassification from tner
+author: John Snow Labs
+name: deberta_v3_large_ontonotes5
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_ontonotes5` is a English model originally trained by tner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ontonotes5_en_5.5.0_3.0_1725388893714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ontonotes5_en_5.5.0_3.0_1725388893714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_ontonotes5","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_ontonotes5", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_ontonotes5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/tner/deberta-v3-large-ontonotes5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_ontonotes5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_ontonotes5_pipeline_en.md
new file mode 100644
index 00000000000000..15b0b437a3dbe1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_ontonotes5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_ontonotes5_pipeline pipeline DeBertaForTokenClassification from tner
+author: John Snow Labs
+name: deberta_v3_large_ontonotes5_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_ontonotes5_pipeline` is a English model originally trained by tner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ontonotes5_pipeline_en_5.5.0_3.0_1725389016160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ontonotes5_pipeline_en_5.5.0_3.0_1725389016160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_ontonotes5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_ontonotes5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_ontonotes5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/tner/deberta-v3-large-ontonotes5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_orgs_v1_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_orgs_v1_en.md
new file mode 100644
index 00000000000000..2d95bdf5084aa1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_orgs_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_orgs_v1 DeBertaForTokenClassification from nbroad
+author: John Snow Labs
+name: deberta_v3_large_orgs_v1
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_orgs_v1` is a English model originally trained by nbroad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_orgs_v1_en_5.5.0_3.0_1725388702012.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_orgs_v1_en_5.5.0_3.0_1725388702012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_orgs_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_orgs_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_orgs_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/nbroad/deberta-v3-large-orgs-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_orgs_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_orgs_v1_pipeline_en.md
new file mode 100644
index 00000000000000..01d946cf9b1d56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_orgs_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_orgs_v1_pipeline pipeline DeBertaForTokenClassification from nbroad
+author: John Snow Labs
+name: deberta_v3_large_orgs_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_orgs_v1_pipeline` is a English model originally trained by nbroad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_orgs_v1_pipeline_en_5.5.0_3.0_1725388791293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_orgs_v1_pipeline_en_5.5.0_3.0_1725388791293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_orgs_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_orgs_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_orgs_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/nbroad/deberta-v3-large-orgs-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_ner_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_ner_finetuned_en.md
new file mode 100644
index 00000000000000..d550aae3aefe85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_ner_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_ner_finetuned DeBertaForTokenClassification from retr00h
+author: John Snow Labs
+name: deberta_v3_xsmall_ner_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_ner_finetuned` is a English model originally trained by retr00h.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_ner_finetuned_en_5.5.0_3.0_1725400363537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_ner_finetuned_en_5.5.0_3.0_1725400363537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_xsmall_ner_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_xsmall_ner_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_ner_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|226.6 MB|
+
+## References
+
+https://huggingface.co/retr00h/deberta-v3-xsmall-NER-FINETUNED
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_ner_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_ner_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..b555a054355301
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_ner_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_ner_finetuned_pipeline pipeline DeBertaForTokenClassification from retr00h
+author: John Snow Labs
+name: deberta_v3_xsmall_ner_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_ner_finetuned_pipeline` is a English model originally trained by retr00h.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_ner_finetuned_pipeline_en_5.5.0_3.0_1725400382501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_ner_finetuned_pipeline_en_5.5.0_3.0_1725400382501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_ner_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_ner_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_ner_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|226.6 MB|
+
+## References
+
+https://huggingface.co/retr00h/deberta-v3-xsmall-NER-FINETUNED
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_qa_squad2_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_qa_squad2_en.md
new file mode 100644
index 00000000000000..d06fff108ff12d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_xsmall_qa_squad2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English DebertaForQuestionAnswering model (from nbroad)
+author: John Snow Labs
+name: deberta_v3_xsmall_qa_squad2
+date: 2024-09-03
+tags: [open_source, deberta, question_answering, en, openvino]
+task: Question Answering
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: openvino
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `deberta-v3-xsmall-squad2` is a English model originally trained by `nbroad`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qa_squad2_en_5.4.2_3.0_1725401584818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qa_squad2_en_5.4.2_3.0_1725401584818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = DebertaForQuestionAnswering.pretrained("deberta_v3_xsmall_qa_squad2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = DebertaForQuestionAnswering.pretrained("deberta_v3_xsmall_qa_squad2","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.deberta").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_qa_squad2|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[token, document]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|411.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+https://huggingface.co/nbroad/deberta-v3-xsmall-squad2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_xsmall_dapt_scientific_papers_pubmed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_xsmall_dapt_scientific_papers_pubmed_pipeline_en.md
new file mode 100644
index 00000000000000..35e0e4bdf87c9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_xsmall_dapt_scientific_papers_pubmed_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_xsmall_dapt_scientific_papers_pubmed_pipeline pipeline DeBertaEmbeddings from domenicrosati
+author: John Snow Labs
+name: deberta_xsmall_dapt_scientific_papers_pubmed_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_xsmall_dapt_scientific_papers_pubmed_pipeline` is a English model originally trained by domenicrosati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_xsmall_dapt_scientific_papers_pubmed_pipeline_en_5.5.0_3.0_1725331301187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_xsmall_dapt_scientific_papers_pubmed_pipeline_en_5.5.0_3.0_1725331301187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_xsmall_dapt_scientific_papers_pubmed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_xsmall_dapt_scientific_papers_pubmed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_xsmall_dapt_scientific_papers_pubmed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.9 MB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-xsmall-dapt-scientific-papers-pubmed
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-declutr_emanuals_s10_serbian_en.md b/docs/_posts/ahmedlone127/2024-09-03-declutr_emanuals_s10_serbian_en.md
new file mode 100644
index 00000000000000..b8704c2a5dfa3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-declutr_emanuals_s10_serbian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English declutr_emanuals_s10_serbian RoBertaForSequenceClassification from AnonymousSub
+author: John Snow Labs
+name: declutr_emanuals_s10_serbian
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`declutr_emanuals_s10_serbian` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/declutr_emanuals_s10_serbian_en_5.5.0_3.0_1725369702400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/declutr_emanuals_s10_serbian_en_5.5.0_3.0_1725369702400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("declutr_emanuals_s10_serbian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("declutr_emanuals_s10_serbian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|declutr_emanuals_s10_serbian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/declutr-emanuals-s10-SR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-declutr_emanuals_s10_serbian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-declutr_emanuals_s10_serbian_pipeline_en.md
new file mode 100644
index 00000000000000..4f27664178352b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-declutr_emanuals_s10_serbian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English declutr_emanuals_s10_serbian_pipeline pipeline RoBertaForSequenceClassification from AnonymousSub
+author: John Snow Labs
+name: declutr_emanuals_s10_serbian_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`declutr_emanuals_s10_serbian_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/declutr_emanuals_s10_serbian_pipeline_en_5.5.0_3.0_1725369729335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/declutr_emanuals_s10_serbian_pipeline_en_5.5.0_3.0_1725369729335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("declutr_emanuals_s10_serbian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("declutr_emanuals_s10_serbian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|declutr_emanuals_s10_serbian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/declutr-emanuals-s10-SR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deepdanbooruclip_en.md b/docs/_posts/ahmedlone127/2024-09-03-deepdanbooruclip_en.md
new file mode 100644
index 00000000000000..9568fd895715f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deepdanbooruclip_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English deepdanbooruclip CLIPForZeroShotClassification from Chars
+author: John Snow Labs
+name: deepdanbooruclip
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepdanbooruclip` is a English model originally trained by Chars.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepdanbooruclip_en_5.5.0_3.0_1725338579682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepdanbooruclip_en_5.5.0_3.0_1725338579682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("deepdanbooruclip","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("deepdanbooruclip","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deepdanbooruclip|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Chars/DeepDanbooruClip
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline_en.md
new file mode 100644
index 00000000000000..53e4dcc4186abf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline pipeline XlmRoBertaForSequenceClassification from gossminn
+author: John Snow Labs
+name: detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline` is a English model originally trained by gossminn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline_en_5.5.0_3.0_1725395307024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline_en_5.5.0_3.0_1725395307024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|detect_femicide_news_xlmr_dutch_fft_freeze2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|863.0 MB|
+
+## References
+
+https://huggingface.co/gossminn/detect-femicide-news-xlmr-nl-fft-freeze2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dhivehi_roberta_base_dv.md b/docs/_posts/ahmedlone127/2024-09-03-dhivehi_roberta_base_dv.md
new file mode 100644
index 00000000000000..65f174af0b1021
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dhivehi_roberta_base_dv.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Dhivehi, Divehi, Maldivian dhivehi_roberta_base RoBertaEmbeddings from shahukareem
+author: John Snow Labs
+name: dhivehi_roberta_base
+date: 2024-09-03
+tags: [dv, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: dv
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dhivehi_roberta_base` is a Dhivehi, Divehi, Maldivian model originally trained by shahukareem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dhivehi_roberta_base_dv_5.5.0_3.0_1725382109952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dhivehi_roberta_base_dv_5.5.0_3.0_1725382109952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("dhivehi_roberta_base","dv") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("dhivehi_roberta_base","dv") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dhivehi_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|dv|
+|Size:|464.9 MB|
+
+## References
+
+https://huggingface.co/shahukareem/dhivehi-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dhivehi_roberta_base_pipeline_dv.md b/docs/_posts/ahmedlone127/2024-09-03-dhivehi_roberta_base_pipeline_dv.md
new file mode 100644
index 00000000000000..f98e6a82e1ebef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dhivehi_roberta_base_pipeline_dv.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Dhivehi, Divehi, Maldivian dhivehi_roberta_base_pipeline pipeline RoBertaEmbeddings from shahukareem
+author: John Snow Labs
+name: dhivehi_roberta_base_pipeline
+date: 2024-09-03
+tags: [dv, open_source, pipeline, onnx]
+task: Embeddings
+language: dv
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dhivehi_roberta_base_pipeline` is a Dhivehi, Divehi, Maldivian model originally trained by shahukareem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dhivehi_roberta_base_pipeline_dv_5.5.0_3.0_1725382134425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dhivehi_roberta_base_pipeline_dv_5.5.0_3.0_1725382134425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dhivehi_roberta_base_pipeline", lang = "dv")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dhivehi_roberta_base_pipeline", lang = "dv")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dhivehi_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|dv|
+|Size:|464.9 MB|
+
+## References
+
+https://huggingface.co/shahukareem/dhivehi-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dirty_e5_base_unsupervised_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dirty_e5_base_unsupervised_pipeline_en.md
new file mode 100644
index 00000000000000..aa93dc8159e4c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dirty_e5_base_unsupervised_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dirty_e5_base_unsupervised_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: dirty_e5_base_unsupervised_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dirty_e5_base_unsupervised_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dirty_e5_base_unsupervised_pipeline_en_5.5.0_3.0_1725344587747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dirty_e5_base_unsupervised_pipeline_en_5.5.0_3.0_1725344587747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dirty_e5_base_unsupervised_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dirty_e5_base_unsupervised_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dirty_e5_base_unsupervised_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|386.0 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/dirty-e5-base-unsupervised
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_analisis_sentimientos_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_analisis_sentimientos_en.md
new file mode 100644
index 00000000000000..ac56202c528c68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_analisis_sentimientos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_analisis_sentimientos DistilBertForSequenceClassification from raulgdp
+author: John Snow Labs
+name: distilbert_analisis_sentimientos
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_analisis_sentimientos` is a English model originally trained by raulgdp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_analisis_sentimientos_en_5.5.0_3.0_1725394123534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_analisis_sentimientos_en_5.5.0_3.0_1725394123534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_analisis_sentimientos","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_analisis_sentimientos", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_analisis_sentimientos|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/raulgdp/Distilbert-Analisis-sentimientos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_analisis_sentimientos_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_analisis_sentimientos_pipeline_en.md
new file mode 100644
index 00000000000000..904ea0dde3fb3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_analisis_sentimientos_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_analisis_sentimientos_pipeline pipeline DistilBertForSequenceClassification from raulgdp
+author: John Snow Labs
+name: distilbert_analisis_sentimientos_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_analisis_sentimientos_pipeline` is a English model originally trained by raulgdp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_analisis_sentimientos_pipeline_en_5.5.0_3.0_1725394136866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_analisis_sentimientos_pipeline_en_5.5.0_3.0_1725394136866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_analisis_sentimientos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_analisis_sentimientos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_analisis_sentimientos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/raulgdp/Distilbert-Analisis-sentimientos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_chinanews_chinese_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_chinanews_chinese_pipeline_zh.md
new file mode 100644
index 00000000000000..445a31bceb3309
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_chinanews_chinese_pipeline_zh.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Chinese distilbert_base_finetuned_chinanews_chinese_pipeline pipeline DistilBertForSequenceClassification from WangA
+author: John Snow Labs
+name: distilbert_base_finetuned_chinanews_chinese_pipeline
+date: 2024-09-03
+tags: [zh, open_source, pipeline, onnx]
+task: Text Classification
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_finetuned_chinanews_chinese_pipeline` is a Chinese model originally trained by WangA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_finetuned_chinanews_chinese_pipeline_zh_5.5.0_3.0_1725393987807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_finetuned_chinanews_chinese_pipeline_zh_5.5.0_3.0_1725393987807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_finetuned_chinanews_chinese_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_finetuned_chinanews_chinese_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_finetuned_chinanews_chinese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/WangA/distilbert-base-finetuned-chinanews-chinese
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_chinanews_chinese_zh.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_chinanews_chinese_zh.md
new file mode 100644
index 00000000000000..45d97e93fd9b10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_chinanews_chinese_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese distilbert_base_finetuned_chinanews_chinese DistilBertForSequenceClassification from WangA
+author: John Snow Labs
+name: distilbert_base_finetuned_chinanews_chinese
+date: 2024-09-03
+tags: [zh, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_finetuned_chinanews_chinese` is a Chinese model originally trained by WangA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_finetuned_chinanews_chinese_zh_5.5.0_3.0_1725393961075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_finetuned_chinanews_chinese_zh_5.5.0_3.0_1725393961075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_finetuned_chinanews_chinese","zh") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_finetuned_chinanews_chinese", "zh")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_finetuned_chinanews_chinese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|zh|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/WangA/distilbert-base-finetuned-chinanews-chinese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_sentiment_en.md
new file mode 100644
index 00000000000000..a6d20a9f3dd8b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_finetuned_sentiment DistilBertForSequenceClassification from lyrisha
+author: John Snow Labs
+name: distilbert_base_finetuned_sentiment
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_finetuned_sentiment` is a English model originally trained by lyrisha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_finetuned_sentiment_en_5.5.0_3.0_1725330343428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_finetuned_sentiment_en_5.5.0_3.0_1725330343428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_finetuned_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_finetuned_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_finetuned_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lyrisha/distilbert-base-finetuned-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..af1ed75ef7a143
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_finetuned_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_finetuned_sentiment_pipeline pipeline DistilBertForSequenceClassification from lyrisha
+author: John Snow Labs
+name: distilbert_base_finetuned_sentiment_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_finetuned_sentiment_pipeline` is a English model originally trained by lyrisha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_finetuned_sentiment_pipeline_en_5.5.0_3.0_1725330355600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_finetuned_sentiment_pipeline_en_5.5.0_3.0_1725330355600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_finetuned_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_finetuned_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_finetuned_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lyrisha/distilbert-base-finetuned-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_german_cased_cimt_argument_de.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_german_cased_cimt_argument_de.md
new file mode 100644
index 00000000000000..60fae668f845ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_german_cased_cimt_argument_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German distilbert_base_german_cased_cimt_argument DistilBertForSequenceClassification from juliaromberg
+author: John Snow Labs
+name: distilbert_base_german_cased_cimt_argument
+date: 2024-09-03
+tags: [de, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_german_cased_cimt_argument` is a German model originally trained by juliaromberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_german_cased_cimt_argument_de_5.5.0_3.0_1725394019364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_german_cased_cimt_argument_de_5.5.0_3.0_1725394019364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_german_cased_cimt_argument","de") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_german_cased_cimt_argument", "de")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_german_cased_cimt_argument|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|de|
+|Size:|252.5 MB|
+
+## References
+
+https://huggingface.co/juliaromberg/distilbert-base-german-cased_cimt-argument
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_german_cased_cimt_argument_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_german_cased_cimt_argument_pipeline_de.md
new file mode 100644
index 00000000000000..0b8d224cbc2ccf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_german_cased_cimt_argument_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German distilbert_base_german_cased_cimt_argument_pipeline pipeline DistilBertForSequenceClassification from juliaromberg
+author: John Snow Labs
+name: distilbert_base_german_cased_cimt_argument_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Text Classification
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_german_cased_cimt_argument_pipeline` is a German model originally trained by juliaromberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_german_cased_cimt_argument_pipeline_de_5.5.0_3.0_1725394033991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_german_cased_cimt_argument_pipeline_de_5.5.0_3.0_1725394033991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_german_cased_cimt_argument_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_german_cased_cimt_argument_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_german_cased_cimt_argument_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|252.5 MB|
+
+## References
+
+https://huggingface.co/juliaromberg/distilbert-base-german-cased_cimt-argument
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_italian_cased_it.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_italian_cased_it.md
new file mode 100644
index 00000000000000..291404ac157c87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_italian_cased_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian distilbert_base_italian_cased DistilBertEmbeddings from osiria
+author: John Snow Labs
+name: distilbert_base_italian_cased
+date: 2024-09-03
+tags: [it, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_italian_cased` is a Italian model originally trained by osiria.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_italian_cased_it_5.5.0_3.0_1725384564049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_italian_cased_it_5.5.0_3.0_1725384564049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_italian_cased","it") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_italian_cased","it") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_italian_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|it|
+|Size:|249.4 MB|
+
+## References
+
+https://huggingface.co/osiria/distilbert-base-italian-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_italian_cased_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_italian_cased_pipeline_it.md
new file mode 100644
index 00000000000000..77d385f6f10109
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_italian_cased_pipeline_it.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Italian distilbert_base_italian_cased_pipeline pipeline DistilBertEmbeddings from osiria
+author: John Snow Labs
+name: distilbert_base_italian_cased_pipeline
+date: 2024-09-03
+tags: [it, open_source, pipeline, onnx]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_italian_cased_pipeline` is a Italian model originally trained by osiria.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_italian_cased_pipeline_it_5.5.0_3.0_1725384578955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_italian_cased_pipeline_it_5.5.0_3.0_1725384578955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_italian_cased_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_italian_cased_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_italian_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|249.4 MB|
+
+## References
+
+https://huggingface.co/osiria/distilbert-base-italian-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline_xx.md
new file mode 100644
index 00000000000000..b950af54e26942
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline pipeline DistilBertEmbeddings from Suksuma
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline` is a Multilingual model originally trained by Suksuma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline_xx_5.5.0_3.0_1725384613423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline_xx_5.5.0_3.0_1725384613423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_imdb_suksuma_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/Suksuma/distilbert-base-multilingual-cased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_wanted_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_wanted_pipeline_xx.md
new file mode 100644
index 00000000000000..5040d3e405870c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_wanted_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_wanted_pipeline pipeline DistilBertEmbeddings from Suksuma
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_wanted_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_wanted_pipeline` is a Multilingual model originally trained by Suksuma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_wanted_pipeline_xx_5.5.0_3.0_1725389797392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_wanted_pipeline_xx_5.5.0_3.0_1725389797392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_wanted_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_wanted_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_wanted_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/Suksuma/distilbert-base-multilingual-cased-finetuned-wanted
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_wanted_xx.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_wanted_xx.md
new file mode 100644
index 00000000000000..fec284a0117ad1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_multilingual_cased_finetuned_wanted_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_wanted DistilBertEmbeddings from Suksuma
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_wanted
+date: 2024-09-03
+tags: [xx, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_wanted` is a Multilingual model originally trained by Suksuma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_wanted_xx_5.5.0_3.0_1725389768113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_wanted_xx_5.5.0_3.0_1725389768113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_wanted","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_wanted","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_wanted|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/Suksuma/distilbert-base-multilingual-cased-finetuned-wanted
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline_en.md
new file mode 100644
index 00000000000000..fd8260f55ea132
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline pipeline DistilBertForSequenceClassification from research-dump
+author: John Snow Labs
+name: distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline_en_5.5.0_3.0_1725394492201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline_en_5.5.0_3.0_1725394492201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_deletion_multiclass_complete_final_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/research-dump/distilbert-base-uncased_deletion_multiclass_complete_final_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_edu_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_edu_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..91b193ee8080e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_edu_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_edu_classifier_pipeline pipeline DistilBertForSequenceClassification from pszemraj
+author: John Snow Labs
+name: distilbert_base_uncased_edu_classifier_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_edu_classifier_pipeline` is a English model originally trained by pszemraj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_edu_classifier_pipeline_en_5.5.0_3.0_1725394080873.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_edu_classifier_pipeline_en_5.5.0_3.0_1725394080873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_edu_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_edu_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_edu_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/pszemraj/distilbert-base-uncased-edu-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fake_news_tfg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fake_news_tfg_pipeline_en.md
new file mode 100644
index 00000000000000..c77d51221dfae2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fake_news_tfg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_fake_news_tfg_pipeline pipeline DistilBertForSequenceClassification from LittleFish-Coder
+author: John Snow Labs
+name: distilbert_base_uncased_fake_news_tfg_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_fake_news_tfg_pipeline` is a English model originally trained by LittleFish-Coder.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_fake_news_tfg_pipeline_en_5.5.0_3.0_1725329964776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_fake_news_tfg_pipeline_en_5.5.0_3.0_1725329964776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_fake_news_tfg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_fake_news_tfg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_fake_news_tfg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LittleFish-Coder/distilbert-base-uncased-fake-news-tfg
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_ag_news_v5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_ag_news_v5_pipeline_en.md
new file mode 100644
index 00000000000000..10604fce0265f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_ag_news_v5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ag_news_v5_pipeline pipeline DistilBertEmbeddings from miggwp
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ag_news_v5_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ag_news_v5_pipeline` is a English model originally trained by miggwp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_v5_pipeline_en_5.5.0_3.0_1725384876988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_v5_pipeline_en_5.5.0_3.0_1725384876988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ag_news_v5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ag_news_v5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ag_news_v5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/miggwp/distilbert-base-uncased-finetuned-ag-news-v5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_bert_school_questions_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_bert_school_questions_en.md
new file mode 100644
index 00000000000000..04065aa68b4f5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_bert_school_questions_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_bert_school_questions DistilBertEmbeddings from Clyine1
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_bert_school_questions
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_bert_school_questions` is a English model originally trained by Clyine1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_bert_school_questions_en_5.5.0_3.0_1725389237092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_bert_school_questions_en_5.5.0_3.0_1725389237092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_bert_school_questions","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_bert_school_questions","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_bert_school_questions|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Clyine1/distilbert-base-uncased-finetuned-bert-school-questions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_bert_school_questions_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_bert_school_questions_pipeline_en.md
new file mode 100644
index 00000000000000..608103bbe75d63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_bert_school_questions_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_bert_school_questions_pipeline pipeline DistilBertEmbeddings from Clyine1
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_bert_school_questions_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_bert_school_questions_pipeline` is a English model originally trained by Clyine1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_bert_school_questions_pipeline_en_5.5.0_3.0_1725389256339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_bert_school_questions_pipeline_en_5.5.0_3.0_1725389256339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_bert_school_questions_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_bert_school_questions_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_bert_school_questions_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Clyine1/distilbert-base-uncased-finetuned-bert-school-questions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_ff112_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_ff112_en.md
new file mode 100644
index 00000000000000..5ddccff3da451c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_ff112_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ff112 DistilBertForSequenceClassification from ff112
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ff112
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ff112` is a English model originally trained by ff112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ff112_en_5.5.0_3.0_1725329932324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ff112_en_5.5.0_3.0_1725329932324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_ff112","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_ff112", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ff112|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ff112/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_ff112_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_ff112_pipeline_en.md
new file mode 100644
index 00000000000000..9015faa4799d40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_ff112_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ff112_pipeline pipeline DistilBertForSequenceClassification from ff112
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ff112_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ff112_pipeline` is a English model originally trained by ff112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ff112_pipeline_en_5.5.0_3.0_1725329944656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ff112_pipeline_en_5.5.0_3.0_1725329944656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ff112_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ff112_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ff112_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ff112/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline_en.md
new file mode 100644
index 00000000000000..1a31ac05edf6ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline pipeline DistilBertForSequenceClassification from iamsubrata
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline` is a English model originally trained by iamsubrata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline_en_5.5.0_3.0_1725394694105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline_en_5.5.0_3.0_1725394694105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_iamsubrata_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/iamsubrata/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_it_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_it_pipeline_en.md
new file mode 100644
index 00000000000000..d85b362b3322b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_it_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_it_pipeline pipeline DistilBertForSequenceClassification from It
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_it_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_it_pipeline` is a English model originally trained by It.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_it_pipeline_en_5.5.0_3.0_1725330027043.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_it_pipeline_en_5.5.0_3.0_1725330027043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_it_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_it_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_it_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/It/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_en.md
new file mode 100644
index 00000000000000..82797d4f7661b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0 DistilBertForSequenceClassification from LeBruse
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0` is a English model originally trained by LeBruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_en_5.5.0_3.0_1725394389162.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_en_5.5.0_3.0_1725394389162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-malay-normalised-text-3.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline_en.md
new file mode 100644
index 00000000000000..a225ecbd360161
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline pipeline DistilBertForSequenceClassification from LeBruse
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline` is a English model originally trained by LeBruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline_en_5.5.0_3.0_1725394404439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline_en_5.5.0_3.0_1725394404439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_malay_normalised_text_3_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-malay-normalised-text-3.0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_nalrunyan_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_nalrunyan_en.md
new file mode 100644
index 00000000000000..a9ae4472b43188
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_nalrunyan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_nalrunyan DistilBertForSequenceClassification from nalrunyan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_nalrunyan
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_nalrunyan` is a English model originally trained by nalrunyan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_nalrunyan_en_5.5.0_3.0_1725329963720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_nalrunyan_en_5.5.0_3.0_1725329963720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_nalrunyan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_nalrunyan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_nalrunyan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nalrunyan/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline_en.md
new file mode 100644
index 00000000000000..a73429b4828f22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline pipeline DistilBertForSequenceClassification from nalrunyan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline` is a English model originally trained by nalrunyan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline_en_5.5.0_3.0_1725329975628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline_en_5.5.0_3.0_1725329975628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_nalrunyan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nalrunyan/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_pulpilisory_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_pulpilisory_en.md
new file mode 100644
index 00000000000000..2aa3194f5bcc8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotion_pulpilisory_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_pulpilisory DistilBertForSequenceClassification from pulpilisory
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_pulpilisory
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_pulpilisory` is a English model originally trained by pulpilisory.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_pulpilisory_en_5.5.0_3.0_1725329812992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_pulpilisory_en_5.5.0_3.0_1725329812992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_pulpilisory","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_pulpilisory", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_pulpilisory|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/pulpilisory/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotions_depi_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotions_depi_en.md
new file mode 100644
index 00000000000000..35681da4d568c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_emotions_depi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_depi DistilBertForSequenceClassification from agoor97
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_depi
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_depi` is a English model originally trained by agoor97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_depi_en_5.5.0_3.0_1725330042537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_depi_en_5.5.0_3.0_1725330042537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_depi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_depi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_depi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/agoor97/distilbert-base-uncased-finetuned-emotions-DEPI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_en.md
new file mode 100644
index 00000000000000..a2ce435e7e11d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_chineidu DistilBertEmbeddings from chineidu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_chineidu
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_chineidu` is a English model originally trained by chineidu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_en_5.5.0_3.0_1725385243438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_en_5.5.0_3.0_1725385243438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_chineidu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_chineidu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_chineidu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/chineidu/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline_en.md
new file mode 100644
index 00000000000000..b2f203424ad9f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline pipeline DistilBertEmbeddings from chineidu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline` is a English model originally trained by chineidu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline_en_5.5.0_3.0_1725385267341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline_en_5.5.0_3.0_1725385267341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_chineidu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/chineidu/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12_en.md
new file mode 100644
index 00000000000000..7487f8690958b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12 DistilBertEmbeddings from cxbn12
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12` is a English model originally trained by cxbn12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12_en_5.5.0_3.0_1725389349337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12_en_5.5.0_3.0_1725389349337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_cxbn12|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cxbn12/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline_en.md
new file mode 100644
index 00000000000000..096064ebc3e15e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline pipeline DistilBertEmbeddings from JHhan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline` is a English model originally trained by JHhan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline_en_5.5.0_3.0_1725385347239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline_en_5.5.0_3.0_1725385347239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_jhhan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/JHhan/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_longma98_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_longma98_en.md
new file mode 100644
index 00000000000000..555707fa2e5109
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_longma98_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_longma98 DistilBertEmbeddings from longma98
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_longma98
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_longma98` is a English model originally trained by longma98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_longma98_en_5.5.0_3.0_1725384660465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_longma98_en_5.5.0_3.0_1725384660465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_longma98","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_longma98","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_longma98|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/longma98/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline_en.md
new file mode 100644
index 00000000000000..4dcdd1aed0e73f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline pipeline DistilBertEmbeddings from longma98
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline` is a English model originally trained by longma98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline_en_5.5.0_3.0_1725384674241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline_en_5.5.0_3.0_1725384674241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_longma98_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/longma98/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_aliekens_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_aliekens_en.md
new file mode 100644
index 00000000000000..4e6771901f809c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_aliekens_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_aliekens DistilBertEmbeddings from aliekens
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_aliekens
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_aliekens` is a English model originally trained by aliekens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_aliekens_en_5.5.0_3.0_1725385148664.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_aliekens_en_5.5.0_3.0_1725385148664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_aliekens","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_aliekens","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_aliekens|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/aliekens/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_aliekens_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_aliekens_pipeline_en.md
new file mode 100644
index 00000000000000..e77b22826af5e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_aliekens_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_aliekens_pipeline pipeline DistilBertEmbeddings from aliekens
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_aliekens_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_aliekens_pipeline` is a English model originally trained by aliekens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_aliekens_pipeline_en_5.5.0_3.0_1725385162053.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_aliekens_pipeline_en_5.5.0_3.0_1725385162053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_aliekens_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_aliekens_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_aliekens_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/aliekens/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_cpeng89_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_cpeng89_en.md
new file mode 100644
index 00000000000000..3d77ed8935cfc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_cpeng89_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_cpeng89 DistilBertEmbeddings from cpeng89
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_cpeng89
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_cpeng89` is a English model originally trained by cpeng89.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cpeng89_en_5.5.0_3.0_1725389975707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cpeng89_en_5.5.0_3.0_1725389975707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_cpeng89","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_cpeng89","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_cpeng89|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cpeng89/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline_en.md
new file mode 100644
index 00000000000000..7e8fc0c37d534f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline pipeline DistilBertEmbeddings from cpeng89
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline` is a English model originally trained by cpeng89.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline_en_5.5.0_3.0_1725389988520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline_en_5.5.0_3.0_1725389988520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_cpeng89_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cpeng89/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_ddn0116_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_ddn0116_en.md
new file mode 100644
index 00000000000000..ab05568b14cade
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_ddn0116_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_ddn0116 DistilBertEmbeddings from ddn0116
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_ddn0116
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ddn0116` is a English model originally trained by ddn0116.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ddn0116_en_5.5.0_3.0_1725389350119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ddn0116_en_5.5.0_3.0_1725389350119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ddn0116","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ddn0116","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_ddn0116|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ddn0116/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline_en.md
new file mode 100644
index 00000000000000..275f90247f8155
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline pipeline DistilBertEmbeddings from gertjanvanderwel
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline` is a English model originally trained by gertjanvanderwel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline_en_5.5.0_3.0_1725385015912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline_en_5.5.0_3.0_1725385015912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_gertjanvanderwel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/gertjanvanderwel/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_linh2001hanoi_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_linh2001hanoi_en.md
new file mode 100644
index 00000000000000..6792c844ef37ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_linh2001hanoi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_linh2001hanoi DistilBertEmbeddings from linh2001hanoi
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_linh2001hanoi
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_linh2001hanoi` is a English model originally trained by linh2001hanoi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_linh2001hanoi_en_5.5.0_3.0_1725389810267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_linh2001hanoi_en_5.5.0_3.0_1725389810267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_linh2001hanoi","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_linh2001hanoi","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_linh2001hanoi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/linh2001hanoi/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline_en.md
new file mode 100644
index 00000000000000..80d6282ef41deb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline pipeline DistilBertEmbeddings from linh2001hanoi
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline` is a English model originally trained by linh2001hanoi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline_en_5.5.0_3.0_1725389823914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline_en_5.5.0_3.0_1725389823914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_linh2001hanoi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/linh2001hanoi/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mhdfadhil_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mhdfadhil_en.md
new file mode 100644
index 00000000000000..21e5268e2903b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mhdfadhil_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mhdfadhil DistilBertEmbeddings from mhdfadhil
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mhdfadhil
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mhdfadhil` is a English model originally trained by mhdfadhil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mhdfadhil_en_5.5.0_3.0_1725384887156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mhdfadhil_en_5.5.0_3.0_1725384887156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_mhdfadhil","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_mhdfadhil","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mhdfadhil|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mhdfadhil/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline_en.md
new file mode 100644
index 00000000000000..cf841cac168407
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline pipeline DistilBertEmbeddings from mhdfadhil
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline` is a English model originally trained by mhdfadhil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline_en_5.5.0_3.0_1725384907527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline_en_5.5.0_3.0_1725384907527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mhdfadhil_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mhdfadhil/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mithegooie_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mithegooie_en.md
new file mode 100644
index 00000000000000..e6aa8d153078f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mithegooie_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mithegooie DistilBertEmbeddings from mithegooie
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mithegooie
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mithegooie` is a English model originally trained by mithegooie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mithegooie_en_5.5.0_3.0_1725389884080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mithegooie_en_5.5.0_3.0_1725389884080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_mithegooie","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_mithegooie","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mithegooie|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mithegooie/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline_en.md
new file mode 100644
index 00000000000000..6bcf3b6570b3b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline pipeline DistilBertEmbeddings from mithegooie
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline` is a English model originally trained by mithegooie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline_en_5.5.0_3.0_1725389898269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline_en_5.5.0_3.0_1725389898269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mithegooie_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/mithegooie/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline_en.md
new file mode 100644
index 00000000000000..2ea15bbacf3069
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline pipeline DistilBertEmbeddings from mongdiutindei
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline` is a English model originally trained by mongdiutindei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline_en_5.5.0_3.0_1725384987788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline_en_5.5.0_3.0_1725384987788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mongdiutindei_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mongdiutindei/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_okinnako_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_okinnako_en.md
new file mode 100644
index 00000000000000..7232c70274e933
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_okinnako_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_okinnako DistilBertEmbeddings from okinnako
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_okinnako
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_okinnako` is a English model originally trained by okinnako.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_okinnako_en_5.5.0_3.0_1725385061736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_okinnako_en_5.5.0_3.0_1725385061736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_okinnako","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_okinnako","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_okinnako|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/okinnako/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_okinnako_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_okinnako_pipeline_en.md
new file mode 100644
index 00000000000000..54ba6ed8d1eb68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_okinnako_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_okinnako_pipeline pipeline DistilBertEmbeddings from okinnako
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_okinnako_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_okinnako_pipeline` is a English model originally trained by okinnako.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_okinnako_pipeline_en_5.5.0_3.0_1725385075042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_okinnako_pipeline_en_5.5.0_3.0_1725385075042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_okinnako_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_okinnako_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_okinnako_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/okinnako/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_en.md
new file mode 100644
index 00000000000000..58fd20772180fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah DistilBertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_en_5.5.0_3.0_1725389264911.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_en_5.5.0_3.0_1725389264911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline_en.md
new file mode 100644
index 00000000000000..873a02a6aeaf77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline pipeline DistilBertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline_en_5.5.0_3.0_1725389278496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline_en_5.5.0_3.0_1725389278496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_pragash_mohanarajah_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_qiyuan123_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_qiyuan123_en.md
new file mode 100644
index 00000000000000..7fd1dba421c321
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_qiyuan123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_qiyuan123 DistilBertEmbeddings from qiyuan123
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_qiyuan123
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_qiyuan123` is a English model originally trained by qiyuan123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_qiyuan123_en_5.5.0_3.0_1725389342787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_qiyuan123_en_5.5.0_3.0_1725389342787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_qiyuan123","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_qiyuan123","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_qiyuan123|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/qiyuan123/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_rohit5895_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_rohit5895_en.md
new file mode 100644
index 00000000000000..6f510acf6777a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_rohit5895_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_rohit5895 DistilBertEmbeddings from rohit5895
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_rohit5895
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_rohit5895` is a English model originally trained by rohit5895.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rohit5895_en_5.5.0_3.0_1725389398451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rohit5895_en_5.5.0_3.0_1725389398451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_rohit5895","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_rohit5895","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_rohit5895|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rohit5895/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sdinger_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sdinger_pipeline_en.md
new file mode 100644
index 00000000000000..7fa73bc2ba4203
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sdinger_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sdinger_pipeline pipeline DistilBertEmbeddings from sdinger
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sdinger_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sdinger_pipeline` is a English model originally trained by sdinger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sdinger_pipeline_en_5.5.0_3.0_1725389484168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sdinger_pipeline_en_5.5.0_3.0_1725389484168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sdinger_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sdinger_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sdinger_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sdinger/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline_en.md
new file mode 100644
index 00000000000000..9589b03010b8fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline pipeline DistilBertEmbeddings from sharanharsoor
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline` is a English model originally trained by sharanharsoor.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline_en_5.5.0_3.0_1725385249048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline_en_5.5.0_3.0_1725385249048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sharanharsoor_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sharanharsoor/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline_en.md
new file mode 100644
index 00000000000000..8ffc711b5d5126
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline pipeline DistilBertEmbeddings from shenberg1
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline` is a English model originally trained by shenberg1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline_en_5.5.0_3.0_1725389846634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline_en_5.5.0_3.0_1725389846634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_shenberg1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/shenberg1/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sooh098_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sooh098_en.md
new file mode 100644
index 00000000000000..516ceff213ec2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sooh098_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sooh098 DistilBertEmbeddings from sooh098
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sooh098
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sooh098` is a English model originally trained by sooh098.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sooh098_en_5.5.0_3.0_1725384663808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sooh098_en_5.5.0_3.0_1725384663808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sooh098","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sooh098","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sooh098|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sooh098/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sooh098_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sooh098_pipeline_en.md
new file mode 100644
index 00000000000000..e005dd4b0c7194
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sooh098_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sooh098_pipeline pipeline DistilBertEmbeddings from sooh098
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sooh098_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sooh098_pipeline` is a English model originally trained by sooh098.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sooh098_pipeline_en_5.5.0_3.0_1725384677628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sooh098_pipeline_en_5.5.0_3.0_1725384677628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sooh098_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sooh098_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sooh098_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sooh098/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_stormer1981_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_stormer1981_en.md
new file mode 100644
index 00000000000000..5d1cd59c4fbbf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_stormer1981_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_stormer1981 DistilBertEmbeddings from stormer1981
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_stormer1981
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_stormer1981` is a English model originally trained by stormer1981.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_stormer1981_en_5.5.0_3.0_1725389720653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_stormer1981_en_5.5.0_3.0_1725389720653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_stormer1981","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_stormer1981","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_stormer1981|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/stormer1981/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline_en.md
new file mode 100644
index 00000000000000..49d36f35e7e128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline pipeline DistilBertEmbeddings from stormer1981
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline` is a English model originally trained by stormer1981.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline_en_5.5.0_3.0_1725389734039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline_en_5.5.0_3.0_1725389734039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_stormer1981_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/stormer1981/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_tslan_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_tslan_en.md
new file mode 100644
index 00000000000000..635730b49d29c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_tslan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_tslan DistilBertEmbeddings from tslan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_tslan
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_tslan` is a English model originally trained by tslan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_tslan_en_5.5.0_3.0_1725389755906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_tslan_en_5.5.0_3.0_1725389755906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_tslan","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_tslan","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_tslan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/tslan/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_tslan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_tslan_pipeline_en.md
new file mode 100644
index 00000000000000..d6669bd1a84667
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_tslan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_tslan_pipeline pipeline DistilBertEmbeddings from tslan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_tslan_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_tslan_pipeline` is a English model originally trained by tslan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_tslan_pipeline_en_5.5.0_3.0_1725389769716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_tslan_pipeline_en_5.5.0_3.0_1725389769716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_tslan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_tslan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_tslan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/tslan/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_utshav_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_utshav_en.md
new file mode 100644
index 00000000000000..87af266baa2e14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_utshav_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_utshav DistilBertEmbeddings from Utshav
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_utshav
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_utshav` is a English model originally trained by Utshav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_utshav_en_5.5.0_3.0_1725389508556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_utshav_en_5.5.0_3.0_1725389508556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_utshav","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_utshav","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_utshav|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Utshav/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_utshav_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_utshav_pipeline_en.md
new file mode 100644
index 00000000000000..6b789fe437f8c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_utshav_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_utshav_pipeline pipeline DistilBertEmbeddings from Utshav
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_utshav_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_utshav_pipeline` is a English model originally trained by Utshav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_utshav_pipeline_en_5.5.0_3.0_1725389521909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_utshav_pipeline_en_5.5.0_3.0_1725389521909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_utshav_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_utshav_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_utshav_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Utshav/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_react_content_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_react_content_en.md
new file mode 100644
index 00000000000000..194df20d0d47d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_react_content_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_react_content DistilBertEmbeddings from mjalg
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_react_content
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_react_content` is a English model originally trained by mjalg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_react_content_en_5.5.0_3.0_1725389882495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_react_content_en_5.5.0_3.0_1725389882495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_react_content","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_react_content","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_react_content|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mjalg/distilbert-base-uncased-finetuned-react-content
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic_en.md
new file mode 100644
index 00000000000000..f1c0b6e26beeeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic DistilBertEmbeddings from Chrisantha
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic` is a English model originally trained by Chrisantha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic_en_5.5.0_3.0_1725389921717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic_en_5.5.0_3.0_1725389921717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_synthetic_finetuned_synthetic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Chrisantha/distilbert-base-uncased-finetuned-synthetic-finetuned-synthetic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fineturned_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fineturned_imdb_en.md
new file mode 100644
index 00000000000000..bcfc74da5dab73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fineturned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_fineturned_imdb DistilBertEmbeddings from cwtmyd
+author: John Snow Labs
+name: distilbert_base_uncased_fineturned_imdb
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_fineturned_imdb` is a English model originally trained by cwtmyd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_fineturned_imdb_en_5.5.0_3.0_1725389236996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_fineturned_imdb_en_5.5.0_3.0_1725389236996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_fineturned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_fineturned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_fineturned_imdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cwtmyd/distilbert-base-uncased-fineturned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fineturned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fineturned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..1872e1ca3e44ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_fineturned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_fineturned_imdb_pipeline pipeline DistilBertEmbeddings from cwtmyd
+author: John Snow Labs
+name: distilbert_base_uncased_fineturned_imdb_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_fineturned_imdb_pipeline` is a English model originally trained by cwtmyd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_fineturned_imdb_pipeline_en_5.5.0_3.0_1725389254062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_fineturned_imdb_pipeline_en_5.5.0_3.0_1725389254062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_fineturned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_fineturned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_fineturned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cwtmyd/distilbert-base-uncased-fineturned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_portfolio_pred_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_portfolio_pred_en.md
new file mode 100644
index 00000000000000..6f20f968f2b375
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_portfolio_pred_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_portfolio_pred DistilBertForSequenceClassification from MFrazz
+author: John Snow Labs
+name: distilbert_base_uncased_portfolio_pred
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_portfolio_pred` is a English model originally trained by MFrazz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_portfolio_pred_en_5.5.0_3.0_1725394236998.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_portfolio_pred_en_5.5.0_3.0_1725394236998.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_portfolio_pred","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_portfolio_pred", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_portfolio_pred|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MFrazz/distilbert-base-uncased-Portfolio-Pred
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_portfolio_pred_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_portfolio_pred_pipeline_en.md
new file mode 100644
index 00000000000000..36d03419146f0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_portfolio_pred_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_portfolio_pred_pipeline pipeline DistilBertForSequenceClassification from MFrazz
+author: John Snow Labs
+name: distilbert_base_uncased_portfolio_pred_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_portfolio_pred_pipeline` is a English model originally trained by MFrazz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_portfolio_pred_pipeline_en_5.5.0_3.0_1725394251082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_portfolio_pred_pipeline_en_5.5.0_3.0_1725394251082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_portfolio_pred_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_portfolio_pred_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_portfolio_pred_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MFrazz/distilbert-base-uncased-Portfolio-Pred
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_finetuned_imdb_indah1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_finetuned_imdb_indah1_pipeline_en.md
new file mode 100644
index 00000000000000..9536898a08e379
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_finetuned_imdb_indah1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_imdb_indah1_pipeline pipeline DistilBertEmbeddings from Indah1
+author: John Snow Labs
+name: distilbert_finetuned_imdb_indah1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_imdb_indah1_pipeline` is a English model originally trained by Indah1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_indah1_pipeline_en_5.5.0_3.0_1725384577686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_indah1_pipeline_en_5.5.0_3.0_1725384577686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_imdb_indah1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_imdb_indah1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_imdb_indah1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Indah1/distilbert-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_finetuned_imdb_prateekag159_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_finetuned_imdb_prateekag159_en.md
new file mode 100644
index 00000000000000..c8a0496bf3cd73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_finetuned_imdb_prateekag159_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_imdb_prateekag159 DistilBertEmbeddings from prateekag159
+author: John Snow Labs
+name: distilbert_finetuned_imdb_prateekag159
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_imdb_prateekag159` is a English model originally trained by prateekag159.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_prateekag159_en_5.5.0_3.0_1725389547153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_prateekag159_en_5.5.0_3.0_1725389547153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_finetuned_imdb_prateekag159","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_finetuned_imdb_prateekag159","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_imdb_prateekag159|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/prateekag159/distilbert-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_one_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_one_en.md
new file mode 100644
index 00000000000000..444e98418d7485
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_one_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_one DistilBertEmbeddings from emma7897
+author: John Snow Labs
+name: distilbert_one
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_one` is a English model originally trained by emma7897.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_one_en_5.5.0_3.0_1725389556294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_one_en_5.5.0_3.0_1725389556294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_one","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_one","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_one|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/emma7897/distilbert_one
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_one_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_one_pipeline_en.md
new file mode 100644
index 00000000000000..272892cbb70d07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_one_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_one_pipeline pipeline DistilBertEmbeddings from emma7897
+author: John Snow Labs
+name: distilbert_one_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_one_pipeline` is a English model originally trained by emma7897.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_one_pipeline_en_5.5.0_3.0_1725389569533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_one_pipeline_en_5.5.0_3.0_1725389569533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_one_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_one_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_one_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/emma7897/distilbert_one
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_finetuned_lm_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_finetuned_lm_en.md
new file mode 100644
index 00000000000000..cb48001a2d68eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_finetuned_lm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_persian_farsi_zwnj_base_finetuned_lm DistilBertEmbeddings from 4h0r4
+author: John Snow Labs
+name: distilbert_persian_farsi_zwnj_base_finetuned_lm
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_persian_farsi_zwnj_base_finetuned_lm` is a English model originally trained by 4h0r4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_persian_farsi_zwnj_base_finetuned_lm_en_5.5.0_3.0_1725389488820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_persian_farsi_zwnj_base_finetuned_lm_en_5.5.0_3.0_1725389488820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_persian_farsi_zwnj_base_finetuned_lm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_persian_farsi_zwnj_base_finetuned_lm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_persian_farsi_zwnj_base_finetuned_lm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|282.3 MB|
+
+## References
+
+https://huggingface.co/4h0r4/distilbert-fa-zwnj-base-finetuned-lm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..f5e5fbac9398f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb DistilBertEmbeddings from drAliMollaei
+author: John Snow Labs
+name: distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb` is a English model originally trained by drAliMollaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_en_5.5.0_3.0_1725389919095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_en_5.5.0_3.0_1725389919095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|282.3 MB|
+
+## References
+
+https://huggingface.co/drAliMollaei/distilbert-fa-zwnj-base-ner-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..bd56e64db67142
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline pipeline DistilBertEmbeddings from drAliMollaei
+author: John Snow Labs
+name: distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline` is a English model originally trained by drAliMollaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline_en_5.5.0_3.0_1725389934384.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline_en_5.5.0_3.0_1725389934384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_persian_farsi_zwnj_base_ner_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.3 MB|
+
+## References
+
+https://huggingface.co/drAliMollaei/distilbert-fa-zwnj-base-ner-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_250k_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_250k_en.md
new file mode 100644
index 00000000000000..30d431be903e07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_250k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_tokenizer_256k_mlm_250k DistilBertEmbeddings from vocab-transformers
+author: John Snow Labs
+name: distilbert_tokenizer_256k_mlm_250k
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_tokenizer_256k_mlm_250k` is a English model originally trained by vocab-transformers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_tokenizer_256k_mlm_250k_en_5.5.0_3.0_1725385232760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_tokenizer_256k_mlm_250k_en_5.5.0_3.0_1725385232760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_tokenizer_256k_mlm_250k","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_tokenizer_256k_mlm_250k","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_tokenizer_256k_mlm_250k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|901.1 MB|
+
+## References
+
+https://huggingface.co/vocab-transformers/distilbert-tokenizer_256k-MLM_250k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_250k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_250k_pipeline_en.md
new file mode 100644
index 00000000000000..21c8005e2e0898
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_250k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_tokenizer_256k_mlm_250k_pipeline pipeline DistilBertEmbeddings from vocab-transformers
+author: John Snow Labs
+name: distilbert_tokenizer_256k_mlm_250k_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_tokenizer_256k_mlm_250k_pipeline` is a English model originally trained by vocab-transformers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_tokenizer_256k_mlm_250k_pipeline_en_5.5.0_3.0_1725385283370.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_tokenizer_256k_mlm_250k_pipeline_en_5.5.0_3.0_1725385283370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_tokenizer_256k_mlm_250k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_tokenizer_256k_mlm_250k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_tokenizer_256k_mlm_250k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|901.1 MB|
+
+## References
+
+https://huggingface.co/vocab-transformers/distilbert-tokenizer_256k-MLM_250k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_best_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_best_pipeline_en.md
new file mode 100644
index 00000000000000..8b113d11cca0c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_tokenizer_256k_mlm_best_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_tokenizer_256k_mlm_best_pipeline pipeline DistilBertEmbeddings from vocab-transformers
+author: John Snow Labs
+name: distilbert_tokenizer_256k_mlm_best_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_tokenizer_256k_mlm_best_pipeline` is a English model originally trained by vocab-transformers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_tokenizer_256k_mlm_best_pipeline_en_5.5.0_3.0_1725384879114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_tokenizer_256k_mlm_best_pipeline_en_5.5.0_3.0_1725384879114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_tokenizer_256k_mlm_best_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_tokenizer_256k_mlm_best_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_tokenizer_256k_mlm_best_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|878.7 MB|
+
+## References
+
+https://huggingface.co/vocab-transformers/distilbert-tokenizer_256k-MLM_best
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_yelp_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_yelp_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..c6f4bc1371d95c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_yelp_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_yelp_sentiment_analysis DistilBertForSequenceClassification from noahnsimbe
+author: John Snow Labs
+name: distilbert_yelp_sentiment_analysis
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_yelp_sentiment_analysis` is a English model originally trained by noahnsimbe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_yelp_sentiment_analysis_en_5.5.0_3.0_1725394562438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_yelp_sentiment_analysis_en_5.5.0_3.0_1725394562438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_yelp_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_yelp_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_yelp_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/noahnsimbe/DistilBERT-yelp-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false_en.md
new file mode 100644
index 00000000000000..c7abf40e9d7d46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false RoBertaForSequenceClassification from ali2066
+author: John Snow Labs
+name: distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false` is a English model originally trained by ali2066.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false_en_5.5.0_3.0_1725403268497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false_en_5.5.0_3.0_1725403268497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbertfinal_ctxsentence_train_all_test_french_second_train_set_french_false|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+https://huggingface.co/ali2066/DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_french_False
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilkobert_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilkobert_ft_pipeline_en.md
new file mode 100644
index 00000000000000..2043f85f1d91e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilkobert_ft_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilkobert_ft_pipeline pipeline DistilBertForSequenceClassification from yeye776
+author: John Snow Labs
+name: distilkobert_ft_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilkobert_ft_pipeline` is a English model originally trained by yeye776.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilkobert_ft_pipeline_en_5.5.0_3.0_1725394557371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilkobert_ft_pipeline_en_5.5.0_3.0_1725394557371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilkobert_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilkobert_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilkobert_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|106.5 MB|
+
+## References
+
+https://huggingface.co/yeye776/DistilKoBERT-ft
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_finetuned_topic_news_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_finetuned_topic_news_en.md
new file mode 100644
index 00000000000000..8659ced17086d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_finetuned_topic_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_topic_news RoBertaForSequenceClassification from RamAnanth1
+author: John Snow Labs
+name: distilroberta_base_finetuned_topic_news
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_topic_news` is a English model originally trained by RamAnanth1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_topic_news_en_5.5.0_3.0_1725402817855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_topic_news_en_5.5.0_3.0_1725402817855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilroberta_base_finetuned_topic_news","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_finetuned_topic_news", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_topic_news|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.9 MB|
+
+## References
+
+https://huggingface.co/RamAnanth1/distilroberta-base-finetuned-topic-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_finetuned_topic_news_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_finetuned_topic_news_pipeline_en.md
new file mode 100644
index 00000000000000..1d877b524948d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_finetuned_topic_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_topic_news_pipeline pipeline RoBertaForSequenceClassification from RamAnanth1
+author: John Snow Labs
+name: distilroberta_base_finetuned_topic_news_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_topic_news_pipeline` is a English model originally trained by RamAnanth1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_topic_news_pipeline_en_5.5.0_3.0_1725402834413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_topic_news_pipeline_en_5.5.0_3.0_1725402834413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_finetuned_topic_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_finetuned_topic_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_topic_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.9 MB|
+
+## References
+
+https://huggingface.co/RamAnanth1/distilroberta-base-finetuned-topic-news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mic_pipeline_en.md
new file mode 100644
index 00000000000000..e0c9d7042d8f77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_mic_pipeline pipeline RoBertaForSequenceClassification from agi-css
+author: John Snow Labs
+name: distilroberta_base_mic_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_mic_pipeline` is a English model originally trained by agi-css.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_mic_pipeline_en_5.5.0_3.0_1725337499082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_mic_pipeline_en_5.5.0_3.0_1725337499082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_mic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_mic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_mic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.1 MB|
+
+## References
+
+https://huggingface.co/agi-css/distilroberta-base-mic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mrpc_glue_raymundosglz_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mrpc_glue_raymundosglz_en.md
new file mode 100644
index 00000000000000..559d133292f83a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mrpc_glue_raymundosglz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_mrpc_glue_raymundosglz RoBertaForSequenceClassification from RaymundoSGlz
+author: John Snow Labs
+name: distilroberta_base_mrpc_glue_raymundosglz
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_mrpc_glue_raymundosglz` is a English model originally trained by RaymundoSGlz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_mrpc_glue_raymundosglz_en_5.5.0_3.0_1725402414564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_mrpc_glue_raymundosglz_en_5.5.0_3.0_1725402414564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilroberta_base_mrpc_glue_raymundosglz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_mrpc_glue_raymundosglz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_mrpc_glue_raymundosglz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/RaymundoSGlz/distilroberta-base-mrpc-glue
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mrpc_glue_raymundosglz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mrpc_glue_raymundosglz_pipeline_en.md
new file mode 100644
index 00000000000000..838b92dc399882
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_mrpc_glue_raymundosglz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_mrpc_glue_raymundosglz_pipeline pipeline RoBertaForSequenceClassification from RaymundoSGlz
+author: John Snow Labs
+name: distilroberta_base_mrpc_glue_raymundosglz_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_mrpc_glue_raymundosglz_pipeline` is a English model originally trained by RaymundoSGlz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_mrpc_glue_raymundosglz_pipeline_en_5.5.0_3.0_1725402430947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_mrpc_glue_raymundosglz_pipeline_en_5.5.0_3.0_1725402430947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_mrpc_glue_raymundosglz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_mrpc_glue_raymundosglz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_mrpc_glue_raymundosglz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/RaymundoSGlz/distilroberta-base-mrpc-glue
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_v2_en.md
new file mode 100644
index 00000000000000..a903bdfe69ad3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_v2 RoBertaEmbeddings from typeform
+author: John Snow Labs
+name: distilroberta_base_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_v2` is a English model originally trained by typeform.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_v2_en_5.5.0_3.0_1725375704213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_v2_en_5.5.0_3.0_1725375704213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.3 MB|
+
+## References
+
+https://huggingface.co/typeform/distilroberta-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_v2_pipeline_en.md
new file mode 100644
index 00000000000000..906c89965ea808
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_v2_pipeline pipeline RoBertaEmbeddings from typeform
+author: John Snow Labs
+name: distilroberta_base_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_v2_pipeline` is a English model originally trained by typeform.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_v2_pipeline_en_5.5.0_3.0_1725375720469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_v2_pipeline_en_5.5.0_3.0_1725375720469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.3 MB|
+
+## References
+
+https://huggingface.co/typeform/distilroberta-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_wandb_week_3_complaints_classifier_1024_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_wandb_week_3_complaints_classifier_1024_en.md
new file mode 100644
index 00000000000000..d467229c67502e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_wandb_week_3_complaints_classifier_1024_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_wandb_week_3_complaints_classifier_1024 RoBertaForSequenceClassification from Kayvane
+author: John Snow Labs
+name: distilroberta_base_wandb_week_3_complaints_classifier_1024
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_wandb_week_3_complaints_classifier_1024` is a English model originally trained by Kayvane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_wandb_week_3_complaints_classifier_1024_en_5.5.0_3.0_1725402141003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_wandb_week_3_complaints_classifier_1024_en_5.5.0_3.0_1725402141003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilroberta_base_wandb_week_3_complaints_classifier_1024","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_wandb_week_3_complaints_classifier_1024", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_wandb_week_3_complaints_classifier_1024|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|309.1 MB|
+
+## References
+
+https://huggingface.co/Kayvane/distilroberta-base-wandb-week-3-complaints-classifier-1024
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline_en.md
new file mode 100644
index 00000000000000..40ad23a1176832
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline pipeline RoBertaForSequenceClassification from Kayvane
+author: John Snow Labs
+name: distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline` is a English model originally trained by Kayvane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline_en_5.5.0_3.0_1725402157479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline_en_5.5.0_3.0_1725402157479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_wandb_week_3_complaints_classifier_1024_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.1 MB|
+
+## References
+
+https://huggingface.co/Kayvane/distilroberta-base-wandb-week-3-complaints-classifier-1024
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_nsfw_prompt_stable_diffusion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_nsfw_prompt_stable_diffusion_pipeline_en.md
new file mode 100644
index 00000000000000..ea9a922f9af82d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_nsfw_prompt_stable_diffusion_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_nsfw_prompt_stable_diffusion_pipeline pipeline RoBertaForSequenceClassification from AdamCodd
+author: John Snow Labs
+name: distilroberta_nsfw_prompt_stable_diffusion_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_nsfw_prompt_stable_diffusion_pipeline` is a English model originally trained by AdamCodd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_nsfw_prompt_stable_diffusion_pipeline_en_5.5.0_3.0_1725336560276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_nsfw_prompt_stable_diffusion_pipeline_en_5.5.0_3.0_1725336560276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_nsfw_prompt_stable_diffusion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_nsfw_prompt_stable_diffusion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_nsfw_prompt_stable_diffusion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.1 MB|
+
+## References
+
+https://huggingface.co/AdamCodd/distilroberta-nsfw-prompt-stable-diffusion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilroberta_spam_comments_detection_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_spam_comments_detection_en.md
new file mode 100644
index 00000000000000..99ef8ee76bf870
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilroberta_spam_comments_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_spam_comments_detection RoBertaForSequenceClassification from valurank
+author: John Snow Labs
+name: distilroberta_spam_comments_detection
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_spam_comments_detection` is a English model originally trained by valurank.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_spam_comments_detection_en_5.5.0_3.0_1725337149113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_spam_comments_detection_en_5.5.0_3.0_1725337149113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilroberta_spam_comments_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_spam_comments_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_spam_comments_detection|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|309.0 MB|
+
+## References
+
+https://huggingface.co/valurank/distilroberta-spam-comments-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dlfbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-dlfbert_en.md
new file mode 100644
index 00000000000000..193a91bc31245f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dlfbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dlfbert RoBertaForSequenceClassification from PubChimps
+author: John Snow Labs
+name: dlfbert
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dlfbert` is a English model originally trained by PubChimps.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dlfbert_en_5.5.0_3.0_1725368781382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dlfbert_en_5.5.0_3.0_1725368781382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("dlfbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("dlfbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dlfbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|314.0 MB|
+
+## References
+
+https://huggingface.co/PubChimps/dlfBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dragon_roberta_base_mixed_domain_en.md b/docs/_posts/ahmedlone127/2024-09-03-dragon_roberta_base_mixed_domain_en.md
new file mode 100644
index 00000000000000..d6361f3abcd90c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dragon_roberta_base_mixed_domain_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dragon_roberta_base_mixed_domain XlmRoBertaEmbeddings from joeranbosma
+author: John Snow Labs
+name: dragon_roberta_base_mixed_domain
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dragon_roberta_base_mixed_domain` is a English model originally trained by joeranbosma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dragon_roberta_base_mixed_domain_en_5.5.0_3.0_1725405893047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dragon_roberta_base_mixed_domain_en_5.5.0_3.0_1725405893047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("dragon_roberta_base_mixed_domain","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("dragon_roberta_base_mixed_domain","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dragon_roberta_base_mixed_domain|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/joeranbosma/dragon-roberta-base-mixed-domain
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dragon_roberta_base_mixed_domain_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dragon_roberta_base_mixed_domain_pipeline_en.md
new file mode 100644
index 00000000000000..b59aeda6696195
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dragon_roberta_base_mixed_domain_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dragon_roberta_base_mixed_domain_pipeline pipeline XlmRoBertaEmbeddings from joeranbosma
+author: John Snow Labs
+name: dragon_roberta_base_mixed_domain_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dragon_roberta_base_mixed_domain_pipeline` is a English model originally trained by joeranbosma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dragon_roberta_base_mixed_domain_pipeline_en_5.5.0_3.0_1725405955062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dragon_roberta_base_mixed_domain_pipeline_en_5.5.0_3.0_1725405955062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dragon_roberta_base_mixed_domain_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dragon_roberta_base_mixed_domain_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dragon_roberta_base_mixed_domain_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/joeranbosma/dragon-roberta-base-mixed-domain
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-drawify_snapsearch_en.md b/docs/_posts/ahmedlone127/2024-09-03-drawify_snapsearch_en.md
new file mode 100644
index 00000000000000..508ea6dfc3204a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-drawify_snapsearch_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English drawify_snapsearch CLIPForZeroShotClassification from drift-ai
+author: John Snow Labs
+name: drawify_snapsearch
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drawify_snapsearch` is a English model originally trained by drift-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/drawify_snapsearch_en_5.5.0_3.0_1725338090375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drawify_snapsearch_en_5.5.0_3.0_1725338090375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("drawify_snapsearch","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("drawify_snapsearch","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|drawify_snapsearch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|567.3 MB|
+
+## References
+
+https://huggingface.co/drift-ai/drawify-snapsearch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_0xeloco_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_0xeloco_en.md
new file mode 100644
index 00000000000000..1dac2d24a5f3b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_0xeloco_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_0xeloco CamemBertEmbeddings from 0xEloco
+author: John Snow Labs
+name: dummy_model_0xeloco
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_0xeloco` is a English model originally trained by 0xEloco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_0xeloco_en_5.5.0_3.0_1725407913558.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_0xeloco_en_5.5.0_3.0_1725407913558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_0xeloco","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_0xeloco","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_0xeloco|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/0xEloco/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_0xeloco_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_0xeloco_pipeline_en.md
new file mode 100644
index 00000000000000..572d3c1e489135
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_0xeloco_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_0xeloco_pipeline pipeline CamemBertEmbeddings from 0xEloco
+author: John Snow Labs
+name: dummy_model_0xeloco_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_0xeloco_pipeline` is a English model originally trained by 0xEloco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_0xeloco_pipeline_en_5.5.0_3.0_1725407991582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_0xeloco_pipeline_en_5.5.0_3.0_1725407991582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_0xeloco_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_0xeloco_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_0xeloco_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/0xEloco/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_c0uchp0tat0_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_c0uchp0tat0_en.md
new file mode 100644
index 00000000000000..cba5dc51a8baea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_c0uchp0tat0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_c0uchp0tat0 CamemBertEmbeddings from C0uchP0tat0
+author: John Snow Labs
+name: dummy_model_c0uchp0tat0
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_c0uchp0tat0` is a English model originally trained by C0uchP0tat0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_c0uchp0tat0_en_5.5.0_3.0_1725407679422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_c0uchp0tat0_en_5.5.0_3.0_1725407679422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_c0uchp0tat0","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_c0uchp0tat0","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_c0uchp0tat0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/C0uchP0tat0/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_c0uchp0tat0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_c0uchp0tat0_pipeline_en.md
new file mode 100644
index 00000000000000..f8bcbd861c5b88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_c0uchp0tat0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_c0uchp0tat0_pipeline pipeline CamemBertEmbeddings from C0uchP0tat0
+author: John Snow Labs
+name: dummy_model_c0uchp0tat0_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_c0uchp0tat0_pipeline` is a English model originally trained by C0uchP0tat0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_c0uchp0tat0_pipeline_en_5.5.0_3.0_1725407762718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_c0uchp0tat0_pipeline_en_5.5.0_3.0_1725407762718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_c0uchp0tat0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_c0uchp0tat0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_c0uchp0tat0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/C0uchP0tat0/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_edge2992_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_edge2992_en.md
new file mode 100644
index 00000000000000..d6b98d4314fb7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_edge2992_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_edge2992 CamemBertEmbeddings from edge2992
+author: John Snow Labs
+name: dummy_model_edge2992
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_edge2992` is a English model originally trained by edge2992.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_edge2992_en_5.5.0_3.0_1725407679158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_edge2992_en_5.5.0_3.0_1725407679158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_edge2992","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_edge2992","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_edge2992|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/edge2992/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_guydebruyn_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_guydebruyn_en.md
new file mode 100644
index 00000000000000..75bb89e70bcee7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_guydebruyn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_guydebruyn CamemBertEmbeddings from guydebruyn
+author: John Snow Labs
+name: dummy_model_guydebruyn
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_guydebruyn` is a English model originally trained by guydebruyn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_guydebruyn_en_5.5.0_3.0_1725407731320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_guydebruyn_en_5.5.0_3.0_1725407731320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_guydebruyn","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_guydebruyn","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_guydebruyn|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/guydebruyn/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_guydebruyn_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_guydebruyn_pipeline_en.md
new file mode 100644
index 00000000000000..90aa71e444e73c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_guydebruyn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_guydebruyn_pipeline pipeline CamemBertEmbeddings from guydebruyn
+author: John Snow Labs
+name: dummy_model_guydebruyn_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_guydebruyn_pipeline` is a English model originally trained by guydebruyn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_guydebruyn_pipeline_en_5.5.0_3.0_1725407809746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_guydebruyn_pipeline_en_5.5.0_3.0_1725407809746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_guydebruyn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_guydebruyn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_guydebruyn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/guydebruyn/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_iamj1han_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_iamj1han_en.md
new file mode 100644
index 00000000000000..17d4fa31b0a3b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_iamj1han_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_iamj1han CamemBertEmbeddings from iamj1han
+author: John Snow Labs
+name: dummy_model_iamj1han
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_iamj1han` is a English model originally trained by iamj1han.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_iamj1han_en_5.5.0_3.0_1725407959215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_iamj1han_en_5.5.0_3.0_1725407959215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_iamj1han","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_iamj1han","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_iamj1han|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/iamj1han/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jianfeng777_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jianfeng777_en.md
new file mode 100644
index 00000000000000..2a90bcb2a88a44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jianfeng777_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jianfeng777 CamemBertEmbeddings from Jianfeng777
+author: John Snow Labs
+name: dummy_model_jianfeng777
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jianfeng777` is a English model originally trained by Jianfeng777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jianfeng777_en_5.5.0_3.0_1725407926447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jianfeng777_en_5.5.0_3.0_1725407926447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jianfeng777","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jianfeng777","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jianfeng777|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Jianfeng777/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jlnlu_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jlnlu_en.md
new file mode 100644
index 00000000000000..a9829b02dfd95e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jlnlu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jlnlu CamemBertEmbeddings from jlnlu
+author: John Snow Labs
+name: dummy_model_jlnlu
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jlnlu` is a English model originally trained by jlnlu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jlnlu_en_5.5.0_3.0_1725407707820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jlnlu_en_5.5.0_3.0_1725407707820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jlnlu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jlnlu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jlnlu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jlnlu/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jlnlu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jlnlu_pipeline_en.md
new file mode 100644
index 00000000000000..09c02929f5587e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_jlnlu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jlnlu_pipeline pipeline CamemBertEmbeddings from jlnlu
+author: John Snow Labs
+name: dummy_model_jlnlu_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jlnlu_pipeline` is a English model originally trained by jlnlu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jlnlu_pipeline_en_5.5.0_3.0_1725407786811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jlnlu_pipeline_en_5.5.0_3.0_1725407786811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jlnlu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jlnlu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jlnlu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jlnlu/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_mhrecaldeb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_mhrecaldeb_pipeline_en.md
new file mode 100644
index 00000000000000..3d07d4fbe00bc2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_mhrecaldeb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_mhrecaldeb_pipeline pipeline CamemBertEmbeddings from mhrecaldeb
+author: John Snow Labs
+name: dummy_model_mhrecaldeb_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_mhrecaldeb_pipeline` is a English model originally trained by mhrecaldeb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_mhrecaldeb_pipeline_en_5.5.0_3.0_1725407758528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_mhrecaldeb_pipeline_en_5.5.0_3.0_1725407758528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_mhrecaldeb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_mhrecaldeb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_mhrecaldeb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mhrecaldeb/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_renyulin_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_renyulin_en.md
new file mode 100644
index 00000000000000..6ba7f938d7d1d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_renyulin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_renyulin CamemBertEmbeddings from renyulin
+author: John Snow Labs
+name: dummy_model_renyulin
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_renyulin` is a English model originally trained by renyulin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_renyulin_en_5.5.0_3.0_1725407900494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_renyulin_en_5.5.0_3.0_1725407900494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_renyulin","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_renyulin","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_renyulin|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/renyulin/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_model_renyulin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_renyulin_pipeline_en.md
new file mode 100644
index 00000000000000..31e3437d5bddcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_model_renyulin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_renyulin_pipeline pipeline CamemBertEmbeddings from renyulin
+author: John Snow Labs
+name: dummy_model_renyulin_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_renyulin_pipeline` is a English model originally trained by renyulin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_renyulin_pipeline_en_5.5.0_3.0_1725407978590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_renyulin_pipeline_en_5.5.0_3.0_1725407978590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_renyulin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_renyulin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_renyulin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/renyulin/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-dummy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-dummy_pipeline_en.md
new file mode 100644
index 00000000000000..ba901d02473180
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-dummy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_pipeline pipeline CamemBertForSequenceClassification from phamsonn
+author: John Snow Labs
+name: dummy_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_pipeline` is a English model originally trained by phamsonn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_pipeline_en_5.5.0_3.0_1725325503547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_pipeline_en_5.5.0_3.0_1725325503547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.2 MB|
+
+## References
+
+https://huggingface.co/phamsonn/dummy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_40k_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_40k_en.md
new file mode 100644
index 00000000000000..f4386a7dd6ef0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_40k_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_40k E5Embeddings from heka-ai
+author: John Snow Labs
+name: e5_40k
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_40k` is a English model originally trained by heka-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_40k_en_5.5.0_3.0_1725344931468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_40k_en_5.5.0_3.0_1725344931468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_40k","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_40k","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_40k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|401.1 MB|
+
+## References
+
+https://huggingface.co/heka-ai/e5-40k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_40k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_40k_pipeline_en.md
new file mode 100644
index 00000000000000..7b331fa5ce3122
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_40k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_40k_pipeline pipeline E5Embeddings from heka-ai
+author: John Snow Labs
+name: e5_40k_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_40k_pipeline` is a English model originally trained by heka-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_40k_pipeline_en_5.5.0_3.0_1725344952424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_40k_pipeline_en_5.5.0_3.0_1725344952424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_40k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_40k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_40k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|401.1 MB|
+
+## References
+
+https://huggingface.co/heka-ai/e5-40k
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_consensus_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_consensus_en.md
new file mode 100644
index 00000000000000..3e950bcd6d332c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_consensus_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_base_consensus E5Embeddings from Consensus
+author: John Snow Labs
+name: e5_base_consensus
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_consensus` is a English model originally trained by Consensus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_consensus_en_5.5.0_3.0_1725332860533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_consensus_en_5.5.0_3.0_1725332860533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_base_consensus","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_base_consensus","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_consensus|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|258.6 MB|
+
+## References
+
+https://huggingface.co/Consensus/e5-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_scifact_10000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_scifact_10000_pipeline_en.md
new file mode 100644
index 00000000000000..6a1882147debfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_scifact_10000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_scifact_10000_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_scifact_10000_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_scifact_10000_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_scifact_10000_pipeline_en_5.5.0_3.0_1725345048121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_scifact_10000_pipeline_en_5.5.0_3.0_1725345048121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_scifact_10000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_scifact_10000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_scifact_10000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|389.8 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base_scifact_10000
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_covid_small_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_covid_small_en.md
new file mode 100644
index 00000000000000..39a021251e9c91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_covid_small_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_base_unsupervised_covid_small E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_covid_small
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_covid_small` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_covid_small_en_5.5.0_3.0_1725393120934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_covid_small_en_5.5.0_3.0_1725393120934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_base_unsupervised_covid_small","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_base_unsupervised_covid_small","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_covid_small|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|397.0 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised-covid-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_covid_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_covid_small_pipeline_en.md
new file mode 100644
index 00000000000000..8c719c33fab6cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_covid_small_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_unsupervised_covid_small_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_covid_small_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_covid_small_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_covid_small_pipeline_en_5.5.0_3.0_1725393146083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_covid_small_pipeline_en_5.5.0_3.0_1725393146083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_unsupervised_covid_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_unsupervised_covid_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_covid_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.0 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised-covid-small
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_1_en.md
new file mode 100644
index 00000000000000..490486da5e97e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_base_unsupervised_pseudo_gpl_1 E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_pseudo_gpl_1
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_pseudo_gpl_1` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_1_en_5.5.0_3.0_1725332474487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_1_en_5.5.0_3.0_1725332474487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_base_unsupervised_pseudo_gpl_1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_base_unsupervised_pseudo_gpl_1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_pseudo_gpl_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|386.9 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised-pseudo-gpl-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_1_pipeline_en.md
new file mode 100644
index 00000000000000..307f7ace886455
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_unsupervised_pseudo_gpl_1_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_pseudo_gpl_1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_pseudo_gpl_1_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_1_pipeline_en_5.5.0_3.0_1725332501320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_1_pipeline_en_5.5.0_3.0_1725332501320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_unsupervised_pseudo_gpl_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_unsupervised_pseudo_gpl_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_pseudo_gpl_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|386.9 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised-pseudo-gpl-1
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline_en.md
new file mode 100644
index 00000000000000..3dfd7e93a89cc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline_en_5.5.0_3.0_1725393219140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline_en_5.5.0_3.0_1725393219140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_586e0b_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.6 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised-pseudo-gpl-fiqa-131a12-d23573-4be015-1bbc3e-586e0b
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_en.md
new file mode 100644
index 00000000000000..4cc023d7e6c055
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_en_5.5.0_3.0_1725333022262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_en_5.5.0_3.0_1725333022262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|402.7 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised-pseudo-gpl-fiqa-131a12-d23573-4be015-1bbc3e
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline_en.md
new file mode 100644
index 00000000000000..368a469461360b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline_en_5.5.0_3.0_1725333047515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline_en_5.5.0_3.0_1725333047515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_pseudo_gpl_fiqa_131a12_d23573_4be015_1bbc3e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.7 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised-pseudo-gpl-fiqa-131a12-d23573-4be015-1bbc3e
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_5000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_5000_pipeline_en.md
new file mode 100644
index 00000000000000..624ef887f33a13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_5000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_unsupervised_scifact_5000_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_scifact_5000_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_scifact_5000_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_scifact_5000_pipeline_en_5.5.0_3.0_1725344939629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_scifact_5000_pipeline_en_5.5.0_3.0_1725344939629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_unsupervised_scifact_5000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_unsupervised_scifact_5000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_scifact_5000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|393.9 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised_scifact_5000
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_7233c2_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_7233c2_en.md
new file mode 100644
index 00000000000000..d7d395fb75d832
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_7233c2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_base_unsupervised_scifact_7233c2 E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_scifact_7233c2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_scifact_7233c2` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_scifact_7233c2_en_5.5.0_3.0_1725340470846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_scifact_7233c2_en_5.5.0_3.0_1725340470846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_base_unsupervised_scifact_7233c2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_base_unsupervised_scifact_7233c2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_scifact_7233c2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|393.9 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised_scifact_7233c2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_7233c2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_7233c2_pipeline_en.md
new file mode 100644
index 00000000000000..e5d90cfd9941d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_unsupervised_scifact_7233c2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_unsupervised_scifact_7233c2_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: e5_base_unsupervised_scifact_7233c2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_unsupervised_scifact_7233c2_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_scifact_7233c2_pipeline_en_5.5.0_3.0_1725340495271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_unsupervised_scifact_7233c2_pipeline_en_5.5.0_3.0_1725340495271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_unsupervised_scifact_7233c2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_unsupervised_scifact_7233c2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_unsupervised_scifact_7233c2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|393.9 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/e5-base-unsupervised_scifact_7233c2
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_intfloat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_intfloat_pipeline_en.md
new file mode 100644
index 00000000000000..fbe9ae79c0e8e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_intfloat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_v2_intfloat_pipeline pipeline E5Embeddings from intfloat
+author: John Snow Labs
+name: e5_base_v2_intfloat_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_v2_intfloat_pipeline` is a English model originally trained by intfloat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_v2_intfloat_pipeline_en_5.5.0_3.0_1725332494934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_v2_intfloat_pipeline_en_5.5.0_3.0_1725332494934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_v2_intfloat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_v2_intfloat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_v2_intfloat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|258.7 MB|
+
+## References
+
+https://huggingface.co/intfloat/e5-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_vectoriseai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_vectoriseai_pipeline_en.md
new file mode 100644
index 00000000000000..9685838ba24c81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_v2_vectoriseai_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_v2_vectoriseai_pipeline pipeline E5Embeddings from vectoriseai
+author: John Snow Labs
+name: e5_base_v2_vectoriseai_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_v2_vectoriseai_pipeline` is a English model originally trained by vectoriseai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_v2_vectoriseai_pipeline_en_5.5.0_3.0_1725344506373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_v2_vectoriseai_pipeline_en_5.5.0_3.0_1725344506373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_v2_vectoriseai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_v2_vectoriseai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_v2_vectoriseai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|258.7 MB|
+
+## References
+
+https://huggingface.co/vectoriseai/e5-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_base_vectoriseai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_base_vectoriseai_pipeline_en.md
new file mode 100644
index 00000000000000..3e62db448700ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_base_vectoriseai_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_base_vectoriseai_pipeline pipeline E5Embeddings from vectoriseai
+author: John Snow Labs
+name: e5_base_vectoriseai_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_vectoriseai_pipeline` is a English model originally trained by vectoriseai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_vectoriseai_pipeline_en_5.5.0_3.0_1725344366881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_vectoriseai_pipeline_en_5.5.0_3.0_1725344366881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_vectoriseai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_vectoriseai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_vectoriseai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|258.6 MB|
+
+## References
+
+https://huggingface.co/vectoriseai/e5-base
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_nli_v1_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_nli_v1_en.md
new file mode 100644
index 00000000000000..aca9125869232e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_nli_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_large_v2_nli_v1 E5Embeddings from hongming
+author: John Snow Labs
+name: e5_large_v2_nli_v1
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_nli_v1` is a English model originally trained by hongming.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_nli_v1_en_5.5.0_3.0_1725332940426.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_nli_v1_en_5.5.0_3.0_1725332940426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_large_v2_nli_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_large_v2_nli_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_large_v2_nli_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/hongming/e5-large-v2-nli-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_nli_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_nli_v1_pipeline_en.md
new file mode 100644
index 00000000000000..58a9a2b849342f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_nli_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_large_v2_nli_v1_pipeline pipeline E5Embeddings from hongming
+author: John Snow Labs
+name: e5_large_v2_nli_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_nli_v1_pipeline` is a English model originally trained by hongming.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_nli_v1_pipeline_en_5.5.0_3.0_1725333011901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_nli_v1_pipeline_en_5.5.0_3.0_1725333011901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_large_v2_nli_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_large_v2_nli_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_large_v2_nli_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/hongming/e5-large-v2-nli-v1
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_vectoriseai_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_vectoriseai_en.md
new file mode 100644
index 00000000000000..aa2b0dc1f9b901
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_large_v2_vectoriseai_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_large_v2_vectoriseai E5Embeddings from vectoriseai
+author: John Snow Labs
+name: e5_large_v2_vectoriseai
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_vectoriseai` is a English model originally trained by vectoriseai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_vectoriseai_en_5.5.0_3.0_1725344834126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_vectoriseai_en_5.5.0_3.0_1725344834126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_large_v2_vectoriseai","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_large_v2_vectoriseai","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_large_v2_vectoriseai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|796.2 MB|
+
+## References
+
+https://huggingface.co/vectoriseai/e5-large-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_small_unsupervised_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_small_unsupervised_pipeline_en.md
new file mode 100644
index 00000000000000..6168915d259f27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_small_unsupervised_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_small_unsupervised_pipeline pipeline E5Embeddings from intfloat
+author: John Snow Labs
+name: e5_small_unsupervised_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_unsupervised_pipeline` is a English model originally trained by intfloat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_unsupervised_pipeline_en_5.5.0_3.0_1725332371290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_unsupervised_pipeline_en_5.5.0_3.0_1725332371290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_small_unsupervised_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_small_unsupervised_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_small_unsupervised_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|80.0 MB|
+
+## References
+
+https://huggingface.co/intfloat/e5-small-unsupervised
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_intfloat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_intfloat_pipeline_en.md
new file mode 100644
index 00000000000000..1d1315d09498a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-e5_small_v2_intfloat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_small_v2_intfloat_pipeline pipeline E5Embeddings from intfloat
+author: John Snow Labs
+name: e5_small_v2_intfloat_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_v2_intfloat_pipeline` is a English model originally trained by intfloat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_v2_intfloat_pipeline_en_5.5.0_3.0_1725332431344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_v2_intfloat_pipeline_en_5.5.0_3.0_1725332431344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_small_v2_intfloat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_small_v2_intfloat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_small_v2_intfloat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|79.9 MB|
+
+## References
+
+https://huggingface.co/intfloat/e5-small-v2
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-electra_qa_DSPFirst_Finetuning_2_en.md b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_DSPFirst_Finetuning_2_en.md
new file mode 100644
index 00000000000000..c13d19de3135a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_DSPFirst_Finetuning_2_en.md
@@ -0,0 +1,99 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from ptran74) Version-2
+author: John Snow Labs
+name: electra_qa_DSPFirst_Finetuning_2
+date: 2024-09-03
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `DSPFirst-Finetuning-2` is a English model originally trained by `ptran74`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_DSPFirst_Finetuning_2_en_5.5.0_3.0_1725352138236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_DSPFirst_Finetuning_2_en_5.5.0_3.0_1725352138236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_DSPFirst_Finetuning_2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_DSPFirst_Finetuning_2","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.electra.finetuning_2").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_DSPFirst_Finetuning_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/ptran74/DSPFirst-Finetuning-2
+- https://github.gatech.edu/pages/VIP-ITS/textbook_SQuAD_explore/explore/textbookv1.0/textbook/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-electra_qa_DSPFirst_Finetuning_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_DSPFirst_Finetuning_2_pipeline_en.md
new file mode 100644
index 00000000000000..5ab2117af7c672
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_DSPFirst_Finetuning_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English electra_qa_DSPFirst_Finetuning_2_pipeline pipeline BertForQuestionAnswering from ptran74
+author: John Snow Labs
+name: electra_qa_DSPFirst_Finetuning_2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_DSPFirst_Finetuning_2_pipeline` is a English model originally trained by ptran74.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_DSPFirst_Finetuning_2_pipeline_en_5.5.0_3.0_1725352199176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_DSPFirst_Finetuning_2_pipeline_en_5.5.0_3.0_1725352199176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("electra_qa_DSPFirst_Finetuning_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("electra_qa_DSPFirst_Finetuning_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_DSPFirst_Finetuning_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ptran74/DSPFirst-Finetuning-2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_discriminator_squad2_512_en.md b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_discriminator_squad2_512_en.md
new file mode 100644
index 00000000000000..90a478bfeae222
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_discriminator_squad2_512_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from ahotrod)
+author: John Snow Labs
+name: electra_qa_large_discriminator_squad2_512
+date: 2024-09-03
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra_large_discriminator_squad2_512` is a English model originally trained by `ahotrod`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_large_discriminator_squad2_512_en_5.5.0_3.0_1725352000774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_large_discriminator_squad2_512_en_5.5.0_3.0_1725352000774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_large_discriminator_squad2_512","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_large_discriminator_squad2_512","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.electra.large_512d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_large_discriminator_squad2_512|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/ahotrod/electra_large_discriminator_squad2_512
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_discriminator_squad2_512_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_discriminator_squad2_512_pipeline_en.md
new file mode 100644
index 00000000000000..b986ca0591ed53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_discriminator_squad2_512_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English electra_qa_large_discriminator_squad2_512_pipeline pipeline BertForQuestionAnswering from ahotrod
+author: John Snow Labs
+name: electra_qa_large_discriminator_squad2_512_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_large_discriminator_squad2_512_pipeline` is a English model originally trained by ahotrod.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_large_discriminator_squad2_512_pipeline_en_5.5.0_3.0_1725352063085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_large_discriminator_squad2_512_pipeline_en_5.5.0_3.0_1725352063085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("electra_qa_large_discriminator_squad2_512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("electra_qa_large_discriminator_squad2_512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_large_discriminator_squad2_512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ahotrod/electra_large_discriminator_squad2_512
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_finetuned_squadv1_en.md b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_finetuned_squadv1_en.md
new file mode 100644
index 00000000000000..8c3d08d7d9fa97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_finetuned_squadv1_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering Large model (from mrm8488)
+author: John Snow Labs
+name: electra_qa_large_finetuned_squadv1
+date: 2024-09-03
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-large-finetuned-squadv1` is a English model originally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_large_finetuned_squadv1_en_5.5.0_3.0_1725351819896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_large_finetuned_squadv1_en_5.5.0_3.0_1725351819896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_large_finetuned_squadv1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_large_finetuned_squadv1","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.large.by_mrm8488").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_large_finetuned_squadv1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/electra-large-finetuned-squadv1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_finetuned_squadv1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_finetuned_squadv1_pipeline_en.md
new file mode 100644
index 00000000000000..b7ee6ef232b857
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-electra_qa_large_finetuned_squadv1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English electra_qa_large_finetuned_squadv1_pipeline pipeline BertForQuestionAnswering from mrm8488
+author: John Snow Labs
+name: electra_qa_large_finetuned_squadv1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_large_finetuned_squadv1_pipeline` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_large_finetuned_squadv1_pipeline_en_5.5.0_3.0_1725351883117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_large_finetuned_squadv1_pipeline_en_5.5.0_3.0_1725351883117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("electra_qa_large_finetuned_squadv1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("electra_qa_large_finetuned_squadv1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_large_finetuned_squadv1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mrm8488/electra-large-finetuned-squadv1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-emb_crossenc_msmarco_teacher_1_albert_en.md b/docs/_posts/ahmedlone127/2024-09-03-emb_crossenc_msmarco_teacher_1_albert_en.md
new file mode 100644
index 00000000000000..b6a7df78b1922b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-emb_crossenc_msmarco_teacher_1_albert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emb_crossenc_msmarco_teacher_1_albert AlbertForSequenceClassification from nishantyadav
+author: John Snow Labs
+name: emb_crossenc_msmarco_teacher_1_albert
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emb_crossenc_msmarco_teacher_1_albert` is a English model originally trained by nishantyadav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emb_crossenc_msmarco_teacher_1_albert_en_5.5.0_3.0_1725385765185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emb_crossenc_msmarco_teacher_1_albert_en_5.5.0_3.0_1725385765185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("emb_crossenc_msmarco_teacher_1_albert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("emb_crossenc_msmarco_teacher_1_albert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emb_crossenc_msmarco_teacher_1_albert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|66.7 MB|
+
+## References
+
+https://huggingface.co/nishantyadav/emb_crossenc_msmarco_teacher_1_albert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-emb_crossenc_msmarco_teacher_1_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-emb_crossenc_msmarco_teacher_1_albert_pipeline_en.md
new file mode 100644
index 00000000000000..c774eb8ac26dfb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-emb_crossenc_msmarco_teacher_1_albert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English emb_crossenc_msmarco_teacher_1_albert_pipeline pipeline AlbertForSequenceClassification from nishantyadav
+author: John Snow Labs
+name: emb_crossenc_msmarco_teacher_1_albert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emb_crossenc_msmarco_teacher_1_albert_pipeline` is a English model originally trained by nishantyadav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emb_crossenc_msmarco_teacher_1_albert_pipeline_en_5.5.0_3.0_1725385768776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emb_crossenc_msmarco_teacher_1_albert_pipeline_en_5.5.0_3.0_1725385768776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("emb_crossenc_msmarco_teacher_1_albert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("emb_crossenc_msmarco_teacher_1_albert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emb_crossenc_msmarco_teacher_1_albert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|66.7 MB|
+
+## References
+
+https://huggingface.co/nishantyadav/emb_crossenc_msmarco_teacher_1_albert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_50_10_en.md b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_50_10_en.md
new file mode 100644
index 00000000000000..213288aab84d24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-embedded_e5_base_50_10_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English embedded_e5_base_50_10 E5Embeddings from rithwik-db
+author: John Snow Labs
+name: embedded_e5_base_50_10
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedded_e5_base_50_10` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedded_e5_base_50_10_en_5.5.0_3.0_1725340877848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedded_e5_base_50_10_en_5.5.0_3.0_1725340877848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("embedded_e5_base_50_10","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("embedded_e5_base_50_10","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|embedded_e5_base_50_10|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|382.1 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/embedded-e5-base-50-10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-embedding_finetune1_bge_small_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-embedding_finetune1_bge_small_english_en.md
new file mode 100644
index 00000000000000..c6e2148524abcb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-embedding_finetune1_bge_small_english_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English embedding_finetune1_bge_small_english BGEEmbeddings from Rohit2581
+author: John Snow Labs
+name: embedding_finetune1_bge_small_english
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedding_finetune1_bge_small_english` is a English model originally trained by Rohit2581.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedding_finetune1_bge_small_english_en_5.5.0_3.0_1725357216069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedding_finetune1_bge_small_english_en_5.5.0_3.0_1725357216069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("embedding_finetune1_bge_small_english","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("embedding_finetune1_bge_small_english","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|embedding_finetune1_bge_small_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|112.5 MB|
+
+## References
+
+https://huggingface.co/Rohit2581/Embedding-Finetune1-bge-small-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-embedding_finetune1_bge_small_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-embedding_finetune1_bge_small_english_pipeline_en.md
new file mode 100644
index 00000000000000..1908a854b3fecf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-embedding_finetune1_bge_small_english_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English embedding_finetune1_bge_small_english_pipeline pipeline BGEEmbeddings from Rohit2581
+author: John Snow Labs
+name: embedding_finetune1_bge_small_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedding_finetune1_bge_small_english_pipeline` is a English model originally trained by Rohit2581.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedding_finetune1_bge_small_english_pipeline_en_5.5.0_3.0_1725357225927.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedding_finetune1_bge_small_english_pipeline_en_5.5.0_3.0_1725357225927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("embedding_finetune1_bge_small_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("embedding_finetune1_bge_small_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|embedding_finetune1_bge_small_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|112.5 MB|
+
+## References
+
+https://huggingface.co/Rohit2581/Embedding-Finetune1-bge-small-en
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-emotion_amaniabuzaid_en.md b/docs/_posts/ahmedlone127/2024-09-03-emotion_amaniabuzaid_en.md
new file mode 100644
index 00000000000000..5f64b6c22f86c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-emotion_amaniabuzaid_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emotion_amaniabuzaid DistilBertForSequenceClassification from amaniabuzaid
+author: John Snow Labs
+name: emotion_amaniabuzaid
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_amaniabuzaid` is a English model originally trained by amaniabuzaid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_amaniabuzaid_en_5.5.0_3.0_1725394594224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_amaniabuzaid_en_5.5.0_3.0_1725394594224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("emotion_amaniabuzaid","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("emotion_amaniabuzaid", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_amaniabuzaid|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/amaniabuzaid/emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-enccr_balanced_en.md b/docs/_posts/ahmedlone127/2024-09-03-enccr_balanced_en.md
new file mode 100644
index 00000000000000..5f1f7d37621583
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-enccr_balanced_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English enccr_balanced RoBertaForSequenceClassification from AntoineGourru
+author: John Snow Labs
+name: enccr_balanced
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enccr_balanced` is a English model originally trained by AntoineGourru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/enccr_balanced_en_5.5.0_3.0_1725369350906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enccr_balanced_en_5.5.0_3.0_1725369350906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("enccr_balanced","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("enccr_balanced", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enccr_balanced|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|417.0 MB|
+
+## References
+
+https://huggingface.co/AntoineGourru/Enccr_balanced
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-enccr_balanced_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-enccr_balanced_pipeline_en.md
new file mode 100644
index 00000000000000..3b5adf737da923
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-enccr_balanced_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English enccr_balanced_pipeline pipeline RoBertaForSequenceClassification from AntoineGourru
+author: John Snow Labs
+name: enccr_balanced_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enccr_balanced_pipeline` is a English model originally trained by AntoineGourru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/enccr_balanced_pipeline_en_5.5.0_3.0_1725369383795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enccr_balanced_pipeline_en_5.5.0_3.0_1725369383795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("enccr_balanced_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("enccr_balanced_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enccr_balanced_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|417.0 MB|
+
+## References
+
+https://huggingface.co/AntoineGourru/Enccr_balanced
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-english_tamil_translator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-english_tamil_translator_pipeline_en.md
new file mode 100644
index 00000000000000..481841526447f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-english_tamil_translator_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tamil_translator_pipeline pipeline MarianTransformer from Vasanth
+author: John Snow Labs
+name: english_tamil_translator_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tamil_translator_pipeline` is a English model originally trained by Vasanth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tamil_translator_pipeline_en_5.5.0_3.0_1725345705204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tamil_translator_pipeline_en_5.5.0_3.0_1725345705204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tamil_translator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tamil_translator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tamil_translator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.7 MB|
+
+## References
+
+https://huggingface.co/Vasanth/en-ta-translator
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_ganda_nllb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_ganda_nllb_pipeline_en.md
new file mode 100644
index 00000000000000..80b1e563eda1ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_ganda_nllb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_ganda_nllb_pipeline pipeline MarianTransformer from EricPeter
+author: John Snow Labs
+name: english_tonga_tonga_islands_ganda_nllb_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_ganda_nllb_pipeline` is a English model originally trained by EricPeter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_ganda_nllb_pipeline_en_5.5.0_3.0_1725404175945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_ganda_nllb_pipeline_en_5.5.0_3.0_1725404175945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_ganda_nllb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_ganda_nllb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_ganda_nllb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.4 MB|
+
+## References
+
+https://huggingface.co/EricPeter/en-to-lg-nllb
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_hindi_en.md b/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_hindi_en.md
new file mode 100644
index 00000000000000..4f89e74e902377
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_hindi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_hindi MarianTransformer from barghavani
+author: John Snow Labs
+name: english_tonga_tonga_islands_hindi
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_hindi` is a English model originally trained by barghavani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_hindi_en_5.5.0_3.0_1725347298768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_hindi_en_5.5.0_3.0_1725347298768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_tonga_tonga_islands_hindi","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_hindi","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_hindi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|523.2 MB|
+
+## References
+
+https://huggingface.co/barghavani/English_to_Hindi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_hindi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_hindi_pipeline_en.md
new file mode 100644
index 00000000000000..cbbeb238ec61a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_hindi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_hindi_pipeline pipeline MarianTransformer from barghavani
+author: John Snow Labs
+name: english_tonga_tonga_islands_hindi_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_hindi_pipeline` is a English model originally trained by barghavani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_hindi_pipeline_en_5.5.0_3.0_1725347323344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_hindi_pipeline_en_5.5.0_3.0_1725347323344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_hindi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_hindi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_hindi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.7 MB|
+
+## References
+
+https://huggingface.co/barghavani/English_to_Hindi
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_turkish_finetuned_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_turkish_finetuned_model_pipeline_en.md
new file mode 100644
index 00000000000000..928f8fdfd8742a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-english_tonga_tonga_islands_turkish_finetuned_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_turkish_finetuned_model_pipeline pipeline MarianTransformer from ckartal
+author: John Snow Labs
+name: english_tonga_tonga_islands_turkish_finetuned_model_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_turkish_finetuned_model_pipeline` is a English model originally trained by ckartal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_turkish_finetuned_model_pipeline_en_5.5.0_3.0_1725404051967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_turkish_finetuned_model_pipeline_en_5.5.0_3.0_1725404051967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_turkish_finetuned_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_turkish_finetuned_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_turkish_finetuned_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|510.3 MB|
+
+## References
+
+https://huggingface.co/ckartal/english-to-turkish-finetuned-model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-environmentalbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-environmentalbert_en.md
new file mode 100644
index 00000000000000..873eee09df277f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-environmentalbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English environmentalbert RoBertaForSequenceClassification from Fabchi
+author: John Snow Labs
+name: environmentalbert
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`environmentalbert` is a English model originally trained by Fabchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/environmentalbert_en_5.5.0_3.0_1725402226211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/environmentalbert_en_5.5.0_3.0_1725402226211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("environmentalbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("environmentalbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|environmentalbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/Fabchi/ENVIRONMENTALBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-environmentalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-environmentalbert_pipeline_en.md
new file mode 100644
index 00000000000000..444a40774db388
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-environmentalbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English environmentalbert_pipeline pipeline RoBertaForSequenceClassification from Fabchi
+author: John Snow Labs
+name: environmentalbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`environmentalbert_pipeline` is a English model originally trained by Fabchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/environmentalbert_pipeline_en_5.5.0_3.0_1725402250925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/environmentalbert_pipeline_en_5.5.0_3.0_1725402250925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("environmentalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("environmentalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|environmentalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.4 MB|
+
+## References
+
+https://huggingface.co/Fabchi/ENVIRONMENTALBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-estroberta_et.md b/docs/_posts/ahmedlone127/2024-09-03-estroberta_et.md
new file mode 100644
index 00000000000000..0ed3ea3254fd5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-estroberta_et.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Estonian estroberta XlmRoBertaEmbeddings from tartuNLP
+author: John Snow Labs
+name: estroberta
+date: 2024-09-03
+tags: [et, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: et
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`estroberta` is a Estonian model originally trained by tartuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/estroberta_et_5.5.0_3.0_1725400121620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/estroberta_et_5.5.0_3.0_1725400121620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("estroberta","et") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("estroberta","et") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|estroberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|et|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/tartuNLP/EstRoBERTa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-estroberta_pipeline_et.md b/docs/_posts/ahmedlone127/2024-09-03-estroberta_pipeline_et.md
new file mode 100644
index 00000000000000..6feece9a84d8bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-estroberta_pipeline_et.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Estonian estroberta_pipeline pipeline XlmRoBertaEmbeddings from tartuNLP
+author: John Snow Labs
+name: estroberta_pipeline
+date: 2024-09-03
+tags: [et, open_source, pipeline, onnx]
+task: Embeddings
+language: et
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`estroberta_pipeline` is a Estonian model originally trained by tartuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/estroberta_pipeline_et_5.5.0_3.0_1725400175648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/estroberta_pipeline_et_5.5.0_3.0_1725400175648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("estroberta_pipeline", lang = "et")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("estroberta_pipeline", lang = "et")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|estroberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|et|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/tartuNLP/EstRoBERTa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-exigent_bge_base_financial_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-03-exigent_bge_base_financial_matryoshka_en.md
new file mode 100644
index 00000000000000..941187aa96350f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-exigent_bge_base_financial_matryoshka_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English exigent_bge_base_financial_matryoshka BGEEmbeddings from RishuD7
+author: John Snow Labs
+name: exigent_bge_base_financial_matryoshka
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exigent_bge_base_financial_matryoshka` is a English model originally trained by RishuD7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exigent_bge_base_financial_matryoshka_en_5.5.0_3.0_1725357462617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exigent_bge_base_financial_matryoshka_en_5.5.0_3.0_1725357462617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("exigent_bge_base_financial_matryoshka","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("exigent_bge_base_financial_matryoshka","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exigent_bge_base_financial_matryoshka|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|389.0 MB|
+
+## References
+
+https://huggingface.co/RishuD7/exigent-bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-exigent_bge_base_financial_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-exigent_bge_base_financial_matryoshka_pipeline_en.md
new file mode 100644
index 00000000000000..e5f79230d78d3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-exigent_bge_base_financial_matryoshka_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English exigent_bge_base_financial_matryoshka_pipeline pipeline BGEEmbeddings from RishuD7
+author: John Snow Labs
+name: exigent_bge_base_financial_matryoshka_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exigent_bge_base_financial_matryoshka_pipeline` is a English model originally trained by RishuD7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exigent_bge_base_financial_matryoshka_pipeline_en_5.5.0_3.0_1725357489077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exigent_bge_base_financial_matryoshka_pipeline_en_5.5.0_3.0_1725357489077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("exigent_bge_base_financial_matryoshka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("exigent_bge_base_financial_matryoshka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exigent_bge_base_financial_matryoshka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|389.0 MB|
+
+## References
+
+https://huggingface.co/RishuD7/exigent-bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-expe_2_en.md b/docs/_posts/ahmedlone127/2024-09-03-expe_2_en.md
new file mode 100644
index 00000000000000..8f15e9b795977d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-expe_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English expe_2 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: expe_2
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`expe_2` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/expe_2_en_5.5.0_3.0_1725402348882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/expe_2_en_5.5.0_3.0_1725402348882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("expe_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("expe_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|expe_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Expe_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-expe_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-expe_2_pipeline_en.md
new file mode 100644
index 00000000000000..f92d4e68d824e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-expe_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English expe_2_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: expe_2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`expe_2_pipeline` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/expe_2_pipeline_en_5.5.0_3.0_1725402373160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/expe_2_pipeline_en_5.5.0_3.0_1725402373160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("expe_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("expe_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|expe_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Expe_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-expe_3_en.md b/docs/_posts/ahmedlone127/2024-09-03-expe_3_en.md
new file mode 100644
index 00000000000000..4ebc0d84b98e89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-expe_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English expe_3 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: expe_3
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`expe_3` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/expe_3_en_5.5.0_3.0_1725402294570.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/expe_3_en_5.5.0_3.0_1725402294570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("expe_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("expe_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|expe_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Expe_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-expe_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-expe_3_pipeline_en.md
new file mode 100644
index 00000000000000..fcc41103ac1bc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-expe_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English expe_3_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: expe_3_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`expe_3_pipeline` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/expe_3_pipeline_en_5.5.0_3.0_1725402319619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/expe_3_pipeline_en_5.5.0_3.0_1725402319619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("expe_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("expe_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|expe_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Expe_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-facets_gpt_42_en.md b/docs/_posts/ahmedlone127/2024-09-03-facets_gpt_42_en.md
new file mode 100644
index 00000000000000..7d6755ba62d9d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-facets_gpt_42_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English facets_gpt_42 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_gpt_42
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facets_gpt_42` is a English model originally trained by ingeol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facets_gpt_42_en_5.5.0_3.0_1725350161139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_gpt_42_en_5.5.0_3.0_1725350161139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("facets_gpt_42","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("facets_gpt_42","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_gpt_42|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_gpt_42
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-facets_gpt_42_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-facets_gpt_42_pipeline_en.md
new file mode 100644
index 00000000000000..c53502ab4c4a11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-facets_gpt_42_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English facets_gpt_42_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_gpt_42_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facets_gpt_42_pipeline` is a English model originally trained by ingeol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facets_gpt_42_pipeline_en_5.5.0_3.0_1725350180451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_gpt_42_pipeline_en_5.5.0_3.0_1725350180451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("facets_gpt_42_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("facets_gpt_42_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_gpt_42_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_gpt_42
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-facets_real_5_en.md b/docs/_posts/ahmedlone127/2024-09-03-facets_real_5_en.md
new file mode 100644
index 00000000000000..7e4683a6c0df11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-facets_real_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English facets_real_5 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_real_5
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facets_real_5` is a English model originally trained by ingeol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facets_real_5_en_5.5.0_3.0_1725351014393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_real_5_en_5.5.0_3.0_1725351014393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("facets_real_5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("facets_real_5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_real_5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_real_5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-facets_real_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-facets_real_5_pipeline_en.md
new file mode 100644
index 00000000000000..aa5f419a4c4729
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-facets_real_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English facets_real_5_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_real_5_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facets_real_5_pipeline` is a English model originally trained by ingeol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facets_real_5_pipeline_en_5.5.0_3.0_1725351034359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_real_5_pipeline_en_5.5.0_3.0_1725351034359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("facets_real_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("facets_real_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_real_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_real_5
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fashion_pattern_clip_en.md b/docs/_posts/ahmedlone127/2024-09-03-fashion_pattern_clip_en.md
new file mode 100644
index 00000000000000..eaec928ecaf99c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fashion_pattern_clip_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English fashion_pattern_clip CLIPForZeroShotClassification from yainage90
+author: John Snow Labs
+name: fashion_pattern_clip
+date: 2024-09-03
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_pattern_clip` is a English model originally trained by yainage90.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_pattern_clip_en_5.5.0_3.0_1725338266105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_pattern_clip_en_5.5.0_3.0_1725338266105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_pattern_clip","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_pattern_clip","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fashion_pattern_clip|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|568.0 MB|
+
+## References
+
+https://huggingface.co/yainage90/fashion-pattern-clip
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fin_microsoft_deberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-fin_microsoft_deberta_v3_base_pipeline_en.md
new file mode 100644
index 00000000000000..a6d809c412c66d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fin_microsoft_deberta_v3_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fin_microsoft_deberta_v3_base_pipeline pipeline DeBertaEmbeddings from Ngawang
+author: John Snow Labs
+name: fin_microsoft_deberta_v3_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fin_microsoft_deberta_v3_base_pipeline` is a English model originally trained by Ngawang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fin_microsoft_deberta_v3_base_pipeline_en_5.5.0_3.0_1725377124637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fin_microsoft_deberta_v3_base_pipeline_en_5.5.0_3.0_1725377124637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fin_microsoft_deberta_v3_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fin_microsoft_deberta_v3_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fin_microsoft_deberta_v3_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|689.7 MB|
+
+## References
+
+https://huggingface.co/Ngawang/fin_microsoft_deberta-v3-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-final_luna_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-03-final_luna_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..4233d7fd89108f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-final_luna_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English final_luna_sentiment_analysis RoBertaForSequenceClassification from snoneeightfive
+author: John Snow Labs
+name: final_luna_sentiment_analysis
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_luna_sentiment_analysis` is a English model originally trained by snoneeightfive.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_luna_sentiment_analysis_en_5.5.0_3.0_1725336899408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_luna_sentiment_analysis_en_5.5.0_3.0_1725336899408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("final_luna_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("final_luna_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_luna_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/snoneeightfive/final-luna-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-financial_sentiment_model_5000_samples_en.md b/docs/_posts/ahmedlone127/2024-09-03-financial_sentiment_model_5000_samples_en.md
new file mode 100644
index 00000000000000..91c3b0643268ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-financial_sentiment_model_5000_samples_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English financial_sentiment_model_5000_samples DistilBertForSequenceClassification from kevinwlip
+author: John Snow Labs
+name: financial_sentiment_model_5000_samples
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`financial_sentiment_model_5000_samples` is a English model originally trained by kevinwlip.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/financial_sentiment_model_5000_samples_en_5.5.0_3.0_1725330326839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/financial_sentiment_model_5000_samples_en_5.5.0_3.0_1725330326839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("financial_sentiment_model_5000_samples","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("financial_sentiment_model_5000_samples", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|financial_sentiment_model_5000_samples|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kevinwlip/financial-sentiment-model-5000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-financial_sentiment_model_5000_samples_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-financial_sentiment_model_5000_samples_pipeline_en.md
new file mode 100644
index 00000000000000..595b740e45e3c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-financial_sentiment_model_5000_samples_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English financial_sentiment_model_5000_samples_pipeline pipeline DistilBertForSequenceClassification from kevinwlip
+author: John Snow Labs
+name: financial_sentiment_model_5000_samples_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`financial_sentiment_model_5000_samples_pipeline` is a English model originally trained by kevinwlip.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/financial_sentiment_model_5000_samples_pipeline_en_5.5.0_3.0_1725330338748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/financial_sentiment_model_5000_samples_pipeline_en_5.5.0_3.0_1725330338748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("financial_sentiment_model_5000_samples_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("financial_sentiment_model_5000_samples_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|financial_sentiment_model_5000_samples_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kevinwlip/financial-sentiment-model-5000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_hf_language_identification_model_xx.md b/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_hf_language_identification_model_xx.md
new file mode 100644
index 00000000000000..d86da4b5b3e144
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_hf_language_identification_model_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual fine_tuned_hf_language_identification_model XlmRoBertaForSequenceClassification from Joshi-Aryan
+author: John Snow Labs
+name: fine_tuned_hf_language_identification_model
+date: 2024-09-03
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_hf_language_identification_model` is a Multilingual model originally trained by Joshi-Aryan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_hf_language_identification_model_xx_5.5.0_3.0_1725328466919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_hf_language_identification_model_xx_5.5.0_3.0_1725328466919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("fine_tuned_hf_language_identification_model","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("fine_tuned_hf_language_identification_model", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_hf_language_identification_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|854.4 MB|
+
+## References
+
+https://huggingface.co/Joshi-Aryan/Fine_Tuned_HF_Language_Identification_Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_paws_en.md b/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_paws_en.md
new file mode 100644
index 00000000000000..916058f1500ad6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_paws_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_paws MPNetForSequenceClassification from spyzvarun
+author: John Snow Labs
+name: fine_tuned_paws
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_paws` is a English model originally trained by spyzvarun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_paws_en_5.5.0_3.0_1725386708374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_paws_en_5.5.0_3.0_1725386708374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("fine_tuned_paws","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("fine_tuned_paws", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_paws|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/spyzvarun/fine-tuned-paws
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_paws_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_paws_pipeline_en.md
new file mode 100644
index 00000000000000..4f283f6b9626dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fine_tuned_paws_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_paws_pipeline pipeline MPNetForSequenceClassification from spyzvarun
+author: John Snow Labs
+name: fine_tuned_paws_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_paws_pipeline` is a English model originally trained by spyzvarun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_paws_pipeline_en_5.5.0_3.0_1725386730948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_paws_pipeline_en_5.5.0_3.0_1725386730948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_paws_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_paws_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_paws_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/spyzvarun/fine-tuned-paws
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fine_tuning_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-fine_tuning_distilbert_en.md
new file mode 100644
index 00000000000000..817741add320b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fine_tuning_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuning_distilbert DistilBertEmbeddings from Nguyens
+author: John Snow Labs
+name: fine_tuning_distilbert
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuning_distilbert` is a English model originally trained by Nguyens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuning_distilbert_en_5.5.0_3.0_1725384620010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuning_distilbert_en_5.5.0_3.0_1725384620010.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("fine_tuning_distilbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("fine_tuning_distilbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuning_distilbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Nguyens/fine-tuning-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fine_tuning_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-fine_tuning_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..de2300a75a46e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fine_tuning_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuning_distilbert_pipeline pipeline DistilBertEmbeddings from Nguyens
+author: John Snow Labs
+name: fine_tuning_distilbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuning_distilbert_pipeline` is a English model originally trained by Nguyens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuning_distilbert_pipeline_en_5.5.0_3.0_1725384635194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuning_distilbert_pipeline_en_5.5.0_3.0_1725384635194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuning_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuning_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuning_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Nguyens/fine-tuning-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finer_ord_transformers_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finer_ord_transformers_2_pipeline_en.md
new file mode 100644
index 00000000000000..b639d9f8da918f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finer_ord_transformers_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finer_ord_transformers_2_pipeline pipeline XlmRoBertaForTokenClassification from elshehawy
+author: John Snow Labs
+name: finer_ord_transformers_2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finer_ord_transformers_2_pipeline` is a English model originally trained by elshehawy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finer_ord_transformers_2_pipeline_en_5.5.0_3.0_1725373836563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finer_ord_transformers_2_pipeline_en_5.5.0_3.0_1725373836563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finer_ord_transformers_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finer_ord_transformers_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finer_ord_transformers_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|782.3 MB|
+
+## References
+
+https://huggingface.co/elshehawy/finer-ord-transformers-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_hindi_tonga_tonga_islands_english_v5_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_hindi_tonga_tonga_islands_english_v5_en.md
new file mode 100644
index 00000000000000..380e396f2e1c9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_hindi_tonga_tonga_islands_english_v5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_hindi_tonga_tonga_islands_english_v5 MarianTransformer from TestZee
+author: John Snow Labs
+name: finetuned_hindi_tonga_tonga_islands_english_v5
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_hindi_tonga_tonga_islands_english_v5` is a English model originally trained by TestZee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_hindi_tonga_tonga_islands_english_v5_en_5.5.0_3.0_1725403938681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_hindi_tonga_tonga_islands_english_v5_en_5.5.0_3.0_1725403938681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("finetuned_hindi_tonga_tonga_islands_english_v5","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("finetuned_hindi_tonga_tonga_islands_english_v5","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_hindi_tonga_tonga_islands_english_v5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|518.4 MB|
+
+## References
+
+https://huggingface.co/TestZee/Finetuned-hindi-to-english-V5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_hindi_tonga_tonga_islands_english_v5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_hindi_tonga_tonga_islands_english_v5_pipeline_en.md
new file mode 100644
index 00000000000000..5ee8b97e9418c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_hindi_tonga_tonga_islands_english_v5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_hindi_tonga_tonga_islands_english_v5_pipeline pipeline MarianTransformer from TestZee
+author: John Snow Labs
+name: finetuned_hindi_tonga_tonga_islands_english_v5_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_hindi_tonga_tonga_islands_english_v5_pipeline` is a English model originally trained by TestZee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_hindi_tonga_tonga_islands_english_v5_pipeline_en_5.5.0_3.0_1725403967856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_hindi_tonga_tonga_islands_english_v5_pipeline_en_5.5.0_3.0_1725403967856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_hindi_tonga_tonga_islands_english_v5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_hindi_tonga_tonga_islands_english_v5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_hindi_tonga_tonga_islands_english_v5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|519.0 MB|
+
+## References
+
+https://huggingface.co/TestZee/Finetuned-hindi-to-english-V5
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_kde4_english_tonga_tonga_islands_french_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_kde4_english_tonga_tonga_islands_french_en.md
new file mode 100644
index 00000000000000..2c5c9b35fde740
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_kde4_english_tonga_tonga_islands_french_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_kde4_english_tonga_tonga_islands_french MarianTransformer from jcheigh
+author: John Snow Labs
+name: finetuned_kde4_english_tonga_tonga_islands_french
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_kde4_english_tonga_tonga_islands_french` is a English model originally trained by jcheigh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_kde4_english_tonga_tonga_islands_french_en_5.5.0_3.0_1725346096022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_kde4_english_tonga_tonga_islands_french_en_5.5.0_3.0_1725346096022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("finetuned_kde4_english_tonga_tonga_islands_french","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("finetuned_kde4_english_tonga_tonga_islands_french","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_kde4_english_tonga_tonga_islands_french|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.3 MB|
+
+## References
+
+https://huggingface.co/jcheigh/finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_roberta_base_squad2_model_for_insurance_data_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_roberta_base_squad2_model_for_insurance_data_en.md
new file mode 100644
index 00000000000000..3eb8e6458379ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_roberta_base_squad2_model_for_insurance_data_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_roberta_base_squad2_model_for_insurance_data RoBertaForQuestionAnswering from sprateek
+author: John Snow Labs
+name: finetuned_roberta_base_squad2_model_for_insurance_data
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_roberta_base_squad2_model_for_insurance_data` is a English model originally trained by sprateek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_roberta_base_squad2_model_for_insurance_data_en_5.5.0_3.0_1725370305281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_roberta_base_squad2_model_for_insurance_data_en_5.5.0_3.0_1725370305281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("finetuned_roberta_base_squad2_model_for_insurance_data","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("finetuned_roberta_base_squad2_model_for_insurance_data", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_roberta_base_squad2_model_for_insurance_data|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/sprateek/finetuned-roberta-base-squad2-model-for-insurance-data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_roberta_base_squad2_model_for_insurance_data_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_roberta_base_squad2_model_for_insurance_data_pipeline_en.md
new file mode 100644
index 00000000000000..af506514028897
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_roberta_base_squad2_model_for_insurance_data_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_roberta_base_squad2_model_for_insurance_data_pipeline pipeline RoBertaForQuestionAnswering from sprateek
+author: John Snow Labs
+name: finetuned_roberta_base_squad2_model_for_insurance_data_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_roberta_base_squad2_model_for_insurance_data_pipeline` is a English model originally trained by sprateek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_roberta_base_squad2_model_for_insurance_data_pipeline_en_5.5.0_3.0_1725370334453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_roberta_base_squad2_model_for_insurance_data_pipeline_en_5.5.0_3.0_1725370334453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_roberta_base_squad2_model_for_insurance_data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_roberta_base_squad2_model_for_insurance_data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_roberta_base_squad2_model_for_insurance_data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/sprateek/finetuned-roberta-base-squad2-model-for-insurance-data
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline_en.md
new file mode 100644
index 00000000000000..1a4022e385d2f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline pipeline MPNetEmbeddings from Deehan1866
+author: John Snow Labs
+name: finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline` is a English model originally trained by Deehan1866.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline_en_5.5.0_3.0_1725350563755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline_en_5.5.0_3.0_1725350563755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_sentence_transformers_multi_qa_mpnet_base_dot_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/Deehan1866/finetuned-sentence-transformers-multi-qa-mpnet-base-dot-v1
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_profane_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_profane_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..8e278839114664
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuned_twitter_profane_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_twitter_profane_roberta_pipeline pipeline XlmRoBertaForSequenceClassification from coderSounak
+author: John Snow Labs
+name: finetuned_twitter_profane_roberta_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_twitter_profane_roberta_pipeline` is a English model originally trained by coderSounak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_twitter_profane_roberta_pipeline_en_5.5.0_3.0_1725395301068.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_twitter_profane_roberta_pipeline_en_5.5.0_3.0_1725395301068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_twitter_profane_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_twitter_profane_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_twitter_profane_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/coderSounak/finetuned_twitter_profane_roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_parth05_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_parth05_en.md
new file mode 100644
index 00000000000000..7e6f4a55847360
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_parth05_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_parth05 DistilBertForSequenceClassification from Parth05
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_parth05
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_parth05` is a English model originally trained by Parth05.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_parth05_en_5.5.0_3.0_1725394342818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_parth05_en_5.5.0_3.0_1725394342818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_parth05","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_parth05", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_parth05|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Parth05/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_shijh302_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_shijh302_en.md
new file mode 100644
index 00000000000000..bdf1dbc42fb1d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_shijh302_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_shijh302 DistilBertForSequenceClassification from shijh302
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_shijh302
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_shijh302` is a English model originally trained by shijh302.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_shijh302_en_5.5.0_3.0_1725394271860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_shijh302_en_5.5.0_3.0_1725394271860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_shijh302","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_shijh302", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_shijh302|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/shijh302/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_shijh302_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_shijh302_pipeline_en.md
new file mode 100644
index 00000000000000..678c3aea48d183
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_3000_samples_shijh302_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_shijh302_pipeline pipeline DistilBertForSequenceClassification from shijh302
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_shijh302_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_shijh302_pipeline` is a English model originally trained by shijh302.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_shijh302_pipeline_en_5.5.0_3.0_1725394285352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_shijh302_pipeline_en_5.5.0_3.0_1725394285352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_shijh302_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_shijh302_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_shijh302_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/shijh302/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_jaskaransingh98_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_jaskaransingh98_en.md
new file mode 100644
index 00000000000000..8f622ed0a38d0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_jaskaransingh98_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_jaskaransingh98 DistilBertForSequenceClassification from Jaskaransingh98
+author: John Snow Labs
+name: finetuning_sentiment_model_jaskaransingh98
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_jaskaransingh98` is a English model originally trained by Jaskaransingh98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_jaskaransingh98_en_5.5.0_3.0_1725393940372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_jaskaransingh98_en_5.5.0_3.0_1725393940372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_jaskaransingh98","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_jaskaransingh98", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_jaskaransingh98|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Jaskaransingh98/finetuning-sentiment-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_jaskaransingh98_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_jaskaransingh98_pipeline_en.md
new file mode 100644
index 00000000000000..49444a84c99ab4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_jaskaransingh98_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_jaskaransingh98_pipeline pipeline DistilBertForSequenceClassification from Jaskaransingh98
+author: John Snow Labs
+name: finetuning_sentiment_model_jaskaransingh98_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_jaskaransingh98_pipeline` is a English model originally trained by Jaskaransingh98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_jaskaransingh98_pipeline_en_5.5.0_3.0_1725393953872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_jaskaransingh98_pipeline_en_5.5.0_3.0_1725393953872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_jaskaransingh98_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_jaskaransingh98_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_jaskaransingh98_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Jaskaransingh98/finetuning-sentiment-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_mpnet_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_mpnet_imdb_en.md
new file mode 100644
index 00000000000000..b1c3f0fc42b2bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_mpnet_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_mpnet_imdb MPNetForSequenceClassification from abhiramd22
+author: John Snow Labs
+name: finetuning_sentiment_model_mpnet_imdb
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_mpnet_imdb` is a English model originally trained by abhiramd22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_mpnet_imdb_en_5.5.0_3.0_1725386963819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_mpnet_imdb_en_5.5.0_3.0_1725386963819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("finetuning_sentiment_model_mpnet_imdb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("finetuning_sentiment_model_mpnet_imdb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_mpnet_imdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/abhiramd22/finetuning-sentiment-model-mpnet-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_mpnet_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_mpnet_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..ceaeb713269804
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-finetuning_sentiment_model_mpnet_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_mpnet_imdb_pipeline pipeline MPNetForSequenceClassification from abhiramd22
+author: John Snow Labs
+name: finetuning_sentiment_model_mpnet_imdb_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_mpnet_imdb_pipeline` is a English model originally trained by abhiramd22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_mpnet_imdb_pipeline_en_5.5.0_3.0_1725386985677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_mpnet_imdb_pipeline_en_5.5.0_3.0_1725386985677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_mpnet_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_mpnet_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_mpnet_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/abhiramd22/finetuning-sentiment-model-mpnet-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fomc_roberta_en.md b/docs/_posts/ahmedlone127/2024-09-03-fomc_roberta_en.md
new file mode 100644
index 00000000000000..55d06f7d4e8630
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fomc_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fomc_roberta RoBertaForSequenceClassification from gtfintechlab
+author: John Snow Labs
+name: fomc_roberta
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fomc_roberta` is a English model originally trained by gtfintechlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fomc_roberta_en_5.5.0_3.0_1725402735774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fomc_roberta_en_5.5.0_3.0_1725402735774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("fomc_roberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("fomc_roberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fomc_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/gtfintechlab/FOMC-RoBERTa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fomc_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-fomc_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..1ebd60f24c566f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fomc_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fomc_roberta_pipeline pipeline RoBertaForSequenceClassification from gtfintechlab
+author: John Snow Labs
+name: fomc_roberta_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fomc_roberta_pipeline` is a English model originally trained by gtfintechlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fomc_roberta_pipeline_en_5.5.0_3.0_1725402828211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fomc_roberta_pipeline_en_5.5.0_3.0_1725402828211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fomc_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fomc_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fomc_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/gtfintechlab/FOMC-RoBERTa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fp_xlm_en.md b/docs/_posts/ahmedlone127/2024-09-03-fp_xlm_en.md
new file mode 100644
index 00000000000000..37d5df54618290
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fp_xlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fp_xlm XlmRoBertaEmbeddings from Sadia2000
+author: John Snow Labs
+name: fp_xlm
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fp_xlm` is a English model originally trained by Sadia2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fp_xlm_en_5.5.0_3.0_1725353265903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fp_xlm_en_5.5.0_3.0_1725353265903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("fp_xlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("fp_xlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fp_xlm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Sadia2000/fp_xlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-fp_xlm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-fp_xlm_pipeline_en.md
new file mode 100644
index 00000000000000..ff940ea831e377
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-fp_xlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fp_xlm_pipeline pipeline XlmRoBertaEmbeddings from Sadia2000
+author: John Snow Labs
+name: fp_xlm_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fp_xlm_pipeline` is a English model originally trained by Sadia2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fp_xlm_pipeline_en_5.5.0_3.0_1725353320672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fp_xlm_pipeline_en_5.5.0_3.0_1725353320672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fp_xlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fp_xlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fp_xlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Sadia2000/fp_xlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-french_double_negation_model_en.md b/docs/_posts/ahmedlone127/2024-09-03-french_double_negation_model_en.md
new file mode 100644
index 00000000000000..a156bf7bfb8c32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-french_double_negation_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English french_double_negation_model DistilBertForSequenceClassification from zzy2524
+author: John Snow Labs
+name: french_double_negation_model
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`french_double_negation_model` is a English model originally trained by zzy2524.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/french_double_negation_model_en_5.5.0_3.0_1725330206505.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/french_double_negation_model_en_5.5.0_3.0_1725330206505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("french_double_negation_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("french_double_negation_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|french_double_negation_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/zzy2524/french_double_negation_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-french_double_negation_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-french_double_negation_model_pipeline_en.md
new file mode 100644
index 00000000000000..bbeb07d911807c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-french_double_negation_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English french_double_negation_model_pipeline pipeline DistilBertForSequenceClassification from zzy2524
+author: John Snow Labs
+name: french_double_negation_model_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`french_double_negation_model_pipeline` is a English model originally trained by zzy2524.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/french_double_negation_model_pipeline_en_5.5.0_3.0_1725330219607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/french_double_negation_model_pipeline_en_5.5.0_3.0_1725330219607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("french_double_negation_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("french_double_negation_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|french_double_negation_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/zzy2524/french_double_negation_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-french_wolof_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-french_wolof_classification_pipeline_en.md
new file mode 100644
index 00000000000000..204c04b540eb0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-french_wolof_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English french_wolof_classification_pipeline pipeline DistilBertForSequenceClassification from Alwaly
+author: John Snow Labs
+name: french_wolof_classification_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`french_wolof_classification_pipeline` is a English model originally trained by Alwaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/french_wolof_classification_pipeline_en_5.5.0_3.0_1725329660341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/french_wolof_classification_pipeline_en_5.5.0_3.0_1725329660341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("french_wolof_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("french_wolof_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|french_wolof_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Alwaly/fr-wo-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-furina_indic_en.md b/docs/_posts/ahmedlone127/2024-09-03-furina_indic_en.md
new file mode 100644
index 00000000000000..de963de90dbf33
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-furina_indic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English furina_indic XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: furina_indic
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`furina_indic` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/furina_indic_en_5.5.0_3.0_1725405997249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/furina_indic_en_5.5.0_3.0_1725405997249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("furina_indic","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("furina_indic","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|furina_indic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/furina-indic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-furina_indic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-furina_indic_pipeline_en.md
new file mode 100644
index 00000000000000..4e83c9aec0c8c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-furina_indic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English furina_indic_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: furina_indic_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`furina_indic_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/furina_indic_pipeline_en_5.5.0_3.0_1725406073722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/furina_indic_pipeline_en_5.5.0_3.0_1725406073722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("furina_indic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("furina_indic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|furina_indic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/furina-indic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-furina_with_transliteration_average_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-furina_with_transliteration_average_pipeline_en.md
new file mode 100644
index 00000000000000..db74771a234134
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-furina_with_transliteration_average_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English furina_with_transliteration_average_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: furina_with_transliteration_average_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`furina_with_transliteration_average_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/furina_with_transliteration_average_pipeline_en_5.5.0_3.0_1725342475216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/furina_with_transliteration_average_pipeline_en_5.5.0_3.0_1725342475216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("furina_with_transliteration_average_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("furina_with_transliteration_average_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|furina_with_transliteration_average_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/furina-with-transliteration-average
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-gal_english_xlm_r_gl.md b/docs/_posts/ahmedlone127/2024-09-03-gal_english_xlm_r_gl.md
new file mode 100644
index 00000000000000..7e983ba6f52e0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-gal_english_xlm_r_gl.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Galician gal_english_xlm_r XlmRoBertaForTokenClassification from mbruton
+author: John Snow Labs
+name: gal_english_xlm_r
+date: 2024-09-03
+tags: [gl, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: gl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gal_english_xlm_r` is a Galician model originally trained by mbruton.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gal_english_xlm_r_gl_5.5.0_3.0_1725372368892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gal_english_xlm_r_gl_5.5.0_3.0_1725372368892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("gal_english_xlm_r","gl") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("gal_english_xlm_r", "gl")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gal_english_xlm_r|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|gl|
+|Size:|869.9 MB|
+
+## References
+
+https://huggingface.co/mbruton/gal_en_XLM-R
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-gal_english_xlm_r_pipeline_gl.md b/docs/_posts/ahmedlone127/2024-09-03-gal_english_xlm_r_pipeline_gl.md
new file mode 100644
index 00000000000000..d886a69989ea44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-gal_english_xlm_r_pipeline_gl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Galician gal_english_xlm_r_pipeline pipeline XlmRoBertaForTokenClassification from mbruton
+author: John Snow Labs
+name: gal_english_xlm_r_pipeline
+date: 2024-09-03
+tags: [gl, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: gl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gal_english_xlm_r_pipeline` is a Galician model originally trained by mbruton.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gal_english_xlm_r_pipeline_gl_5.5.0_3.0_1725372436110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gal_english_xlm_r_pipeline_gl_5.5.0_3.0_1725372436110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gal_english_xlm_r_pipeline", lang = "gl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gal_english_xlm_r_pipeline", lang = "gl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gal_english_xlm_r_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|gl|
+|Size:|869.9 MB|
+
+## References
+
+https://huggingface.co/mbruton/gal_en_XLM-R
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-geoloc_entity_linking_cross_encoder_en.md b/docs/_posts/ahmedlone127/2024-09-03-geoloc_entity_linking_cross_encoder_en.md
new file mode 100644
index 00000000000000..fe5ac14fc58c3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-geoloc_entity_linking_cross_encoder_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English geoloc_entity_linking_cross_encoder CamemBertForSequenceClassification from gcaillaut
+author: John Snow Labs
+name: geoloc_entity_linking_cross_encoder
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`geoloc_entity_linking_cross_encoder` is a English model originally trained by gcaillaut.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/geoloc_entity_linking_cross_encoder_en_5.5.0_3.0_1725325584593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/geoloc_entity_linking_cross_encoder_en_5.5.0_3.0_1725325584593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("geoloc_entity_linking_cross_encoder","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("geoloc_entity_linking_cross_encoder", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|geoloc_entity_linking_cross_encoder|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|202.1 MB|
+
+## References
+
+https://huggingface.co/gcaillaut/geoloc-entity-linking-cross-encoder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-georgian_homonym_disambiguation_fm_ka.md b/docs/_posts/ahmedlone127/2024-09-03-georgian_homonym_disambiguation_fm_ka.md
new file mode 100644
index 00000000000000..f827fb7423a4cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-georgian_homonym_disambiguation_fm_ka.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Georgian georgian_homonym_disambiguation_fm DistilBertEmbeddings from davmel
+author: John Snow Labs
+name: georgian_homonym_disambiguation_fm
+date: 2024-09-03
+tags: [ka, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: ka
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`georgian_homonym_disambiguation_fm` is a Georgian model originally trained by davmel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/georgian_homonym_disambiguation_fm_ka_5.5.0_3.0_1725389237010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/georgian_homonym_disambiguation_fm_ka_5.5.0_3.0_1725389237010.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("georgian_homonym_disambiguation_fm","ka") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("georgian_homonym_disambiguation_fm","ka") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|georgian_homonym_disambiguation_fm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|ka|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/davmel/ka_homonym_disambiguation_FM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-georgian_homonym_disambiguation_fm_pipeline_ka.md b/docs/_posts/ahmedlone127/2024-09-03-georgian_homonym_disambiguation_fm_pipeline_ka.md
new file mode 100644
index 00000000000000..3e96c1b38fc849
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-georgian_homonym_disambiguation_fm_pipeline_ka.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Georgian georgian_homonym_disambiguation_fm_pipeline pipeline DistilBertEmbeddings from davmel
+author: John Snow Labs
+name: georgian_homonym_disambiguation_fm_pipeline
+date: 2024-09-03
+tags: [ka, open_source, pipeline, onnx]
+task: Embeddings
+language: ka
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`georgian_homonym_disambiguation_fm_pipeline` is a Georgian model originally trained by davmel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/georgian_homonym_disambiguation_fm_pipeline_ka_5.5.0_3.0_1725389256185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/georgian_homonym_disambiguation_fm_pipeline_ka_5.5.0_3.0_1725389256185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("georgian_homonym_disambiguation_fm_pipeline", lang = "ka")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("georgian_homonym_disambiguation_fm_pipeline", lang = "ka")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|georgian_homonym_disambiguation_fm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ka|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/davmel/ka_homonym_disambiguation_FM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ger_roberta_en.md b/docs/_posts/ahmedlone127/2024-09-03-ger_roberta_en.md
new file mode 100644
index 00000000000000..85f7ed89b44d4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ger_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ger_roberta RoBertaEmbeddings from svalabs
+author: John Snow Labs
+name: ger_roberta
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ger_roberta` is a English model originally trained by svalabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ger_roberta_en_5.5.0_3.0_1725375246760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ger_roberta_en_5.5.0_3.0_1725375246760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("ger_roberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("ger_roberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ger_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|470.6 MB|
+
+## References
+
+https://huggingface.co/svalabs/ger-roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ger_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-ger_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..51f6578c67e42e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ger_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ger_roberta_pipeline pipeline RoBertaEmbeddings from svalabs
+author: John Snow Labs
+name: ger_roberta_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ger_roberta_pipeline` is a English model originally trained by svalabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ger_roberta_pipeline_en_5.5.0_3.0_1725375276652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ger_roberta_pipeline_en_5.5.0_3.0_1725375276652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ger_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ger_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ger_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.6 MB|
+
+## References
+
+https://huggingface.co/svalabs/ger-roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_max_en.md b/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_max_en.md
new file mode 100644
index 00000000000000..56c74792545acf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_max_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English glot500_with_transliteration_max XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: glot500_with_transliteration_max
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glot500_with_transliteration_max` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_max_en_5.5.0_3.0_1725343855745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_max_en_5.5.0_3.0_1725343855745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("glot500_with_transliteration_max","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("glot500_with_transliteration_max","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|glot500_with_transliteration_max|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/glot500-with-transliteration-max
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_minangkabau_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_minangkabau_pipeline_en.md
new file mode 100644
index 00000000000000..f1a5b058185453
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-glot500_with_transliteration_minangkabau_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English glot500_with_transliteration_minangkabau_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: glot500_with_transliteration_minangkabau_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glot500_with_transliteration_minangkabau_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_minangkabau_pipeline_en_5.5.0_3.0_1725342960347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_minangkabau_pipeline_en_5.5.0_3.0_1725342960347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("glot500_with_transliteration_minangkabau_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("glot500_with_transliteration_minangkabau_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|glot500_with_transliteration_minangkabau_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/glot500-with-transliteration-min
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_test_1_aba799_en.md b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_test_1_aba799_en.md
new file mode 100644
index 00000000000000..33c5865f006e5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_test_1_aba799_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpl_e5_base_test_1_aba799 E5Embeddings from rithwik-db
+author: John Snow Labs
+name: gpl_e5_base_test_1_aba799
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_test_1_aba799` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_test_1_aba799_en_5.5.0_3.0_1725344159704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_test_1_aba799_en_5.5.0_3.0_1725344159704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("gpl_e5_base_test_1_aba799","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("gpl_e5_base_test_1_aba799","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpl_e5_base_test_1_aba799|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|388.6 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/gpl-e5-base-test-1-aba799
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_test_1_aba799_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_test_1_aba799_pipeline_en.md
new file mode 100644
index 00000000000000..52f53552b1f5b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_test_1_aba799_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpl_e5_base_test_1_aba799_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: gpl_e5_base_test_1_aba799_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_test_1_aba799_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_test_1_aba799_pipeline_en_5.5.0_3.0_1725344184340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_test_1_aba799_pipeline_en_5.5.0_3.0_1725344184340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpl_e5_base_test_1_aba799_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpl_e5_base_test_1_aba799_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpl_e5_base_test_1_aba799_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|388.6 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/gpl-e5-base-test-1-aba799
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_arguana_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_arguana_1_pipeline_en.md
new file mode 100644
index 00000000000000..2ea7863ddde9b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_arguana_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpl_e5_base_unsupervised_arguana_1_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: gpl_e5_base_unsupervised_arguana_1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_unsupervised_arguana_1_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_arguana_1_pipeline_en_5.5.0_3.0_1725341221196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_arguana_1_pipeline_en_5.5.0_3.0_1725341221196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpl_e5_base_unsupervised_arguana_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpl_e5_base_unsupervised_arguana_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpl_e5_base_unsupervised_arguana_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|400.3 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/gpl-e5-base-unsupervised-arguana-1
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_curated_2_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_curated_2_small_pipeline_en.md
new file mode 100644
index 00000000000000..63e378b4fb611c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_curated_2_small_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpl_e5_base_unsupervised_curated_2_small_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: gpl_e5_base_unsupervised_curated_2_small_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_unsupervised_curated_2_small_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_curated_2_small_pipeline_en_5.5.0_3.0_1725340487979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_curated_2_small_pipeline_en_5.5.0_3.0_1725340487979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpl_e5_base_unsupervised_curated_2_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpl_e5_base_unsupervised_curated_2_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpl_e5_base_unsupervised_curated_2_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|388.6 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/gpl-e5-base-unsupervised-curated-2-small
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_test_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_test_1_pipeline_en.md
new file mode 100644
index 00000000000000..f99f59e9084f11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-gpl_e5_base_unsupervised_test_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpl_e5_base_unsupervised_test_1_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: gpl_e5_base_unsupervised_test_1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpl_e5_base_unsupervised_test_1_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_test_1_pipeline_en_5.5.0_3.0_1725340248769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpl_e5_base_unsupervised_test_1_pipeline_en_5.5.0_3.0_1725340248769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpl_e5_base_unsupervised_test_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpl_e5_base_unsupervised_test_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpl_e5_base_unsupervised_test_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|388.5 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/gpl-e5-base-unsupervised-test-1
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-gujibert_jian_en.md b/docs/_posts/ahmedlone127/2024-09-03-gujibert_jian_en.md
new file mode 100644
index 00000000000000..9394547b0a0d75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-gujibert_jian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gujibert_jian BertEmbeddings from hsc748NLP
+author: John Snow Labs
+name: gujibert_jian
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gujibert_jian` is a English model originally trained by hsc748NLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gujibert_jian_en_5.5.0_3.0_1725323960153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gujibert_jian_en_5.5.0_3.0_1725323960153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("gujibert_jian","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("gujibert_jian","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gujibert_jian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|420.2 MB|
+
+## References
+
+https://huggingface.co/hsc748NLP/GujiBERT_jian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-hel_english_french_4_layers_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-hel_english_french_4_layers_pipeline_en.md
new file mode 100644
index 00000000000000..386873c32a8c9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-hel_english_french_4_layers_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hel_english_french_4_layers_pipeline pipeline MarianTransformer from Momo200519
+author: John Snow Labs
+name: hel_english_french_4_layers_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hel_english_french_4_layers_pipeline` is a English model originally trained by Momo200519.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hel_english_french_4_layers_pipeline_en_5.5.0_3.0_1725346446210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hel_english_french_4_layers_pipeline_en_5.5.0_3.0_1725346446210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hel_english_french_4_layers_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hel_english_french_4_layers_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hel_english_french_4_layers_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/Momo200519/hel_en_fr_4_layers
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-helsinki_altp_indonesian_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-helsinki_altp_indonesian_english_pipeline_en.md
new file mode 100644
index 00000000000000..942b559d62e978
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-helsinki_altp_indonesian_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_altp_indonesian_english_pipeline pipeline MarianTransformer from Mikask
+author: John Snow Labs
+name: helsinki_altp_indonesian_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_altp_indonesian_english_pipeline` is a English model originally trained by Mikask.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_altp_indonesian_english_pipeline_en_5.5.0_3.0_1725403969781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_altp_indonesian_english_pipeline_en_5.5.0_3.0_1725403969781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("helsinki_altp_indonesian_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_altp_indonesian_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_altp_indonesian_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|480.6 MB|
+
+## References
+
+https://huggingface.co/Mikask/helsinki-altp-id-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-helsinki_danish_swedish_v15_en.md b/docs/_posts/ahmedlone127/2024-09-03-helsinki_danish_swedish_v15_en.md
new file mode 100644
index 00000000000000..faa92e93929963
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-helsinki_danish_swedish_v15_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_danish_swedish_v15 MarianTransformer from Danieljacobsen
+author: John Snow Labs
+name: helsinki_danish_swedish_v15
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_danish_swedish_v15` is a English model originally trained by Danieljacobsen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_v15_en_5.5.0_3.0_1725405144934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_v15_en_5.5.0_3.0_1725405144934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_danish_swedish_v15","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_danish_swedish_v15","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_danish_swedish_v15|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|496.8 MB|
+
+## References
+
+https://huggingface.co/Danieljacobsen/Helsinki-DA-SV-v15
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-helsinki_danish_swedish_v15_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-helsinki_danish_swedish_v15_pipeline_en.md
new file mode 100644
index 00000000000000..a149eb0be69572
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-helsinki_danish_swedish_v15_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_danish_swedish_v15_pipeline pipeline MarianTransformer from Danieljacobsen
+author: John Snow Labs
+name: helsinki_danish_swedish_v15_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_danish_swedish_v15_pipeline` is a English model originally trained by Danieljacobsen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_v15_pipeline_en_5.5.0_3.0_1725405172768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_v15_pipeline_en_5.5.0_3.0_1725405172768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("helsinki_danish_swedish_v15_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_danish_swedish_v15_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_danish_swedish_v15_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|497.3 MB|
+
+## References
+
+https://huggingface.co/Danieljacobsen/Helsinki-DA-SV-v15
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_en.md b/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_en.md
new file mode 100644
index 00000000000000..f377e0ba04b10d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune MarianTransformer from MikolajDeja
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune` is a English model originally trained by MikolajDeja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_en_5.5.0_3.0_1725404324430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_en_5.5.0_3.0_1725404324430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|531.7 MB|
+
+## References
+
+https://huggingface.co/MikolajDeja/Helsinki-NLP-opus-mt-en-mul-yhavinga-ccmatrix-finetune
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline_en.md
new file mode 100644
index 00000000000000..3f4c3964879d8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline pipeline MarianTransformer from MikolajDeja
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline` is a English model originally trained by MikolajDeja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline_en_5.5.0_3.0_1725404353354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline_en_5.5.0_3.0_1725404353354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_english_multiple_languages_yhavinga_ccmatrix_finetune_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|532.2 MB|
+
+## References
+
+https://huggingface.co/MikolajDeja/Helsinki-NLP-opus-mt-en-mul-yhavinga-ccmatrix-finetune
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..2b6772d94e3c99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline pipeline MarianTransformer from MikolajDeja
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline` is a English model originally trained by MikolajDeja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline_en_5.5.0_3.0_1725404615753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline_en_5.5.0_3.0_1725404615753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_multiple_languages_english_opus100_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.5 MB|
+
+## References
+
+https://huggingface.co/MikolajDeja/Helsinki-NLP-opus-mt-mul-en-opus100-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-hindi_roberta_hi.md b/docs/_posts/ahmedlone127/2024-09-03-hindi_roberta_hi.md
new file mode 100644
index 00000000000000..8190efdd370931
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-hindi_roberta_hi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hindi hindi_roberta XlmRoBertaEmbeddings from l3cube-pune
+author: John Snow Labs
+name: hindi_roberta
+date: 2024-09-03
+tags: [hi, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hindi_roberta` is a Hindi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hindi_roberta_hi_5.5.0_3.0_1725390599672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindi_roberta_hi_5.5.0_3.0_1725390599672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("hindi_roberta","hi") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("hindi_roberta","hi") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hindi_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|hi|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hindi-roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-hindi_roberta_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-03-hindi_roberta_pipeline_hi.md
new file mode 100644
index 00000000000000..7afa3d7e063402
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-hindi_roberta_pipeline_hi.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hindi hindi_roberta_pipeline pipeline XlmRoBertaEmbeddings from l3cube-pune
+author: John Snow Labs
+name: hindi_roberta_pipeline
+date: 2024-09-03
+tags: [hi, open_source, pipeline, onnx]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hindi_roberta_pipeline` is a Hindi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hindi_roberta_pipeline_hi_5.5.0_3.0_1725390654491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindi_roberta_pipeline_hi_5.5.0_3.0_1725390654491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hindi_roberta_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hindi_roberta_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hindi_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hindi-roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-hrbert_mini_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-hrbert_mini_pipeline_xx.md
new file mode 100644
index 00000000000000..d1e25df189fe62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-hrbert_mini_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual hrbert_mini_pipeline pipeline RoBertaEmbeddings from RabotaRu
+author: John Snow Labs
+name: hrbert_mini_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hrbert_mini_pipeline` is a Multilingual model originally trained by RabotaRu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hrbert_mini_pipeline_xx_5.5.0_3.0_1725381746862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hrbert_mini_pipeline_xx_5.5.0_3.0_1725381746862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hrbert_mini_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hrbert_mini_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hrbert_mini_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|298.3 MB|
+
+## References
+
+https://huggingface.co/RabotaRu/HRBert-mini
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-hrbert_mini_xx.md b/docs/_posts/ahmedlone127/2024-09-03-hrbert_mini_xx.md
new file mode 100644
index 00000000000000..27ee52009f81bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-hrbert_mini_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual hrbert_mini RoBertaEmbeddings from RabotaRu
+author: John Snow Labs
+name: hrbert_mini
+date: 2024-09-03
+tags: [xx, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hrbert_mini` is a Multilingual model originally trained by RabotaRu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hrbert_mini_xx_5.5.0_3.0_1725381729763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hrbert_mini_xx_5.5.0_3.0_1725381729763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("hrbert_mini","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("hrbert_mini","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hrbert_mini|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|xx|
+|Size:|298.3 MB|
+
+## References
+
+https://huggingface.co/RabotaRu/HRBert-mini
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-indic_bert_finetuned_non_code_mixed_ds_en.md b/docs/_posts/ahmedlone127/2024-09-03-indic_bert_finetuned_non_code_mixed_ds_en.md
new file mode 100644
index 00000000000000..860f6ebc52ae71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-indic_bert_finetuned_non_code_mixed_ds_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_finetuned_non_code_mixed_ds AlbertForSequenceClassification from IIIT-L
+author: John Snow Labs
+name: indic_bert_finetuned_non_code_mixed_ds
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_finetuned_non_code_mixed_ds` is a English model originally trained by IIIT-L.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_non_code_mixed_ds_en_5.5.0_3.0_1725385900368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_non_code_mixed_ds_en_5.5.0_3.0_1725385900368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_finetuned_non_code_mixed_ds","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_finetuned_non_code_mixed_ds", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_finetuned_non_code_mixed_ds|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/IIIT-L/indic-bert-finetuned-non-code-mixed-DS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-indic_bert_finetuned_non_code_mixed_ds_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-indic_bert_finetuned_non_code_mixed_ds_pipeline_en.md
new file mode 100644
index 00000000000000..078565634c8f95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-indic_bert_finetuned_non_code_mixed_ds_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indic_bert_finetuned_non_code_mixed_ds_pipeline pipeline AlbertForSequenceClassification from IIIT-L
+author: John Snow Labs
+name: indic_bert_finetuned_non_code_mixed_ds_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_finetuned_non_code_mixed_ds_pipeline` is a English model originally trained by IIIT-L.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_non_code_mixed_ds_pipeline_en_5.5.0_3.0_1725385906718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_non_code_mixed_ds_pipeline_en_5.5.0_3.0_1725385906718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indic_bert_finetuned_non_code_mixed_ds_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indic_bert_finetuned_non_code_mixed_ds_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_finetuned_non_code_mixed_ds_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/IIIT-L/indic-bert-finetuned-non-code-mixed-DS
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-indic_hindi_telugu_mlm_squad_tydi_mlqa_hi.md b/docs/_posts/ahmedlone127/2024-09-03-indic_hindi_telugu_mlm_squad_tydi_mlqa_hi.md
new file mode 100644
index 00000000000000..69def4f22caf35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-indic_hindi_telugu_mlm_squad_tydi_mlqa_hi.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Hindi indic_hindi_telugu_mlm_squad_tydi_mlqa AlbertForQuestionAnswering from hapandya
+author: John Snow Labs
+name: indic_hindi_telugu_mlm_squad_tydi_mlqa
+date: 2024-09-03
+tags: [hi, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_hindi_telugu_mlm_squad_tydi_mlqa` is a Hindi model originally trained by hapandya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_hindi_telugu_mlm_squad_tydi_mlqa_hi_5.5.0_3.0_1725341759981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_hindi_telugu_mlm_squad_tydi_mlqa_hi_5.5.0_3.0_1725341759981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("indic_hindi_telugu_mlm_squad_tydi_mlqa","hi") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("indic_hindi_telugu_mlm_squad_tydi_mlqa", "hi")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_hindi_telugu_mlm_squad_tydi_mlqa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|hi|
+|Size:|123.1 MB|
+
+## References
+
+https://huggingface.co/hapandya/indic-hi-te-MLM-SQuAD-TyDi-MLQA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-03-indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi.md
new file mode 100644
index 00000000000000..cab030b023e0df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hindi indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline pipeline AlbertForQuestionAnswering from hapandya
+author: John Snow Labs
+name: indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline
+date: 2024-09-03
+tags: [hi, open_source, pipeline, onnx]
+task: Question Answering
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline` is a Hindi model originally trained by hapandya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi_5.5.0_3.0_1725341766824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi_5.5.0_3.0_1725341766824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_hindi_telugu_mlm_squad_tydi_mlqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|123.1 MB|
+
+## References
+
+https://huggingface.co/hapandya/indic-hi-te-MLM-SQuAD-TyDi-MLQA
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-indonesian_roberta_base_id.md b/docs/_posts/ahmedlone127/2024-09-03-indonesian_roberta_base_id.md
new file mode 100644
index 00000000000000..c6208219f8a2b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-indonesian_roberta_base_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian indonesian_roberta_base RoBertaEmbeddings from flax-community
+author: John Snow Labs
+name: indonesian_roberta_base
+date: 2024-09-03
+tags: [id, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_roberta_base` is a Indonesian model originally trained by flax-community.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_roberta_base_id_5.5.0_3.0_1725375394315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_roberta_base_id_5.5.0_3.0_1725375394315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("indonesian_roberta_base","id") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("indonesian_roberta_base","id") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|id|
+|Size:|465.4 MB|
+
+## References
+
+https://huggingface.co/flax-community/indonesian-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-indonesian_roberta_base_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-03-indonesian_roberta_base_pipeline_id.md
new file mode 100644
index 00000000000000..2f353aa116d53d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-indonesian_roberta_base_pipeline_id.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Indonesian indonesian_roberta_base_pipeline pipeline RoBertaEmbeddings from flax-community
+author: John Snow Labs
+name: indonesian_roberta_base_pipeline
+date: 2024-09-03
+tags: [id, open_source, pipeline, onnx]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_roberta_base_pipeline` is a Indonesian model originally trained by flax-community.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_roberta_base_pipeline_id_5.5.0_3.0_1725375419657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_roberta_base_pipeline_id_5.5.0_3.0_1725375419657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indonesian_roberta_base_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indonesian_roberta_base_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|465.5 MB|
+
+## References
+
+https://huggingface.co/flax-community/indonesian-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-jmedroberta_base_sentencepiece_vocab50000_ja.md b/docs/_posts/ahmedlone127/2024-09-03-jmedroberta_base_sentencepiece_vocab50000_ja.md
new file mode 100644
index 00000000000000..4c181ccae3159e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-jmedroberta_base_sentencepiece_vocab50000_ja.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Japanese jmedroberta_base_sentencepiece_vocab50000 BertEmbeddings from alabnii
+author: John Snow Labs
+name: jmedroberta_base_sentencepiece_vocab50000
+date: 2024-09-03
+tags: [ja, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jmedroberta_base_sentencepiece_vocab50000` is a Japanese model originally trained by alabnii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jmedroberta_base_sentencepiece_vocab50000_ja_5.5.0_3.0_1725324199338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jmedroberta_base_sentencepiece_vocab50000_ja_5.5.0_3.0_1725324199338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("jmedroberta_base_sentencepiece_vocab50000","ja") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("jmedroberta_base_sentencepiece_vocab50000","ja") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jmedroberta_base_sentencepiece_vocab50000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|ja|
+|Size:|464.0 MB|
+
+## References
+
+https://huggingface.co/alabnii/jmedroberta-base-sentencepiece-vocab50000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-kde4_english_vietnamese_test_en.md b/docs/_posts/ahmedlone127/2024-09-03-kde4_english_vietnamese_test_en.md
new file mode 100644
index 00000000000000..23803ed90d0653
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-kde4_english_vietnamese_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kde4_english_vietnamese_test MarianTransformer from choidf
+author: John Snow Labs
+name: kde4_english_vietnamese_test
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kde4_english_vietnamese_test` is a English model originally trained by choidf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kde4_english_vietnamese_test_en_5.5.0_3.0_1725404959936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kde4_english_vietnamese_test_en_5.5.0_3.0_1725404959936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("kde4_english_vietnamese_test","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("kde4_english_vietnamese_test","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kde4_english_vietnamese_test|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|474.4 MB|
+
+## References
+
+https://huggingface.co/choidf/kde4-en-vi-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-kde4_english_vietnamese_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-kde4_english_vietnamese_test_pipeline_en.md
new file mode 100644
index 00000000000000..f0ebae54d5ccc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-kde4_english_vietnamese_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kde4_english_vietnamese_test_pipeline pipeline MarianTransformer from choidf
+author: John Snow Labs
+name: kde4_english_vietnamese_test_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kde4_english_vietnamese_test_pipeline` is a English model originally trained by choidf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kde4_english_vietnamese_test_pipeline_en_5.5.0_3.0_1725404992662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kde4_english_vietnamese_test_pipeline_en_5.5.0_3.0_1725404992662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kde4_english_vietnamese_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kde4_english_vietnamese_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kde4_english_vietnamese_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|475.0 MB|
+
+## References
+
+https://huggingface.co/choidf/kde4-en-vi-test
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-khmer_xlm_roberta_base_km.md b/docs/_posts/ahmedlone127/2024-09-03-khmer_xlm_roberta_base_km.md
new file mode 100644
index 00000000000000..baa8bb44362b6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-khmer_xlm_roberta_base_km.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Central Khmer, Khmer khmer_xlm_roberta_base XlmRoBertaEmbeddings from channudam
+author: John Snow Labs
+name: khmer_xlm_roberta_base
+date: 2024-09-03
+tags: [km, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: km
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`khmer_xlm_roberta_base` is a Central Khmer, Khmer model originally trained by channudam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/khmer_xlm_roberta_base_km_5.5.0_3.0_1725391562214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/khmer_xlm_roberta_base_km_5.5.0_3.0_1725391562214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("khmer_xlm_roberta_base","km") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("khmer_xlm_roberta_base","km") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|khmer_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|km|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/channudam/khmer-xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-kpc_cf_en.md b/docs/_posts/ahmedlone127/2024-09-03-kpc_cf_en.md
new file mode 100644
index 00000000000000..781669c3707e0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-kpc_cf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kpc_cf XlmRoBertaForSequenceClassification from KorABSA
+author: John Snow Labs
+name: kpc_cf
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kpc_cf` is a English model originally trained by KorABSA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kpc_cf_en_5.5.0_3.0_1725395641845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kpc_cf_en_5.5.0_3.0_1725395641845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("kpc_cf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("kpc_cf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kpc_cf|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|838.9 MB|
+
+## References
+
+https://huggingface.co/KorABSA/KPC-cF
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-kpc_cf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-kpc_cf_pipeline_en.md
new file mode 100644
index 00000000000000..01f1c72f0ab905
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-kpc_cf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kpc_cf_pipeline pipeline XlmRoBertaForSequenceClassification from KorABSA
+author: John Snow Labs
+name: kpc_cf_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kpc_cf_pipeline` is a English model originally trained by KorABSA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kpc_cf_pipeline_en_5.5.0_3.0_1725395724882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kpc_cf_pipeline_en_5.5.0_3.0_1725395724882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kpc_cf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kpc_cf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kpc_cf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|838.9 MB|
+
+## References
+
+https://huggingface.co/KorABSA/KPC-cF
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-lab1_random_coloteong_en.md b/docs/_posts/ahmedlone127/2024-09-03-lab1_random_coloteong_en.md
new file mode 100644
index 00000000000000..2d0d2726d09556
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-lab1_random_coloteong_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab1_random_coloteong MarianTransformer from coloteong
+author: John Snow Labs
+name: lab1_random_coloteong
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_random_coloteong` is a English model originally trained by coloteong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab1_random_coloteong_en_5.5.0_3.0_1725404779963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_random_coloteong_en_5.5.0_3.0_1725404779963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab1_random_coloteong","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab1_random_coloteong","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_random_coloteong|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.2 MB|
+
+## References
+
+https://huggingface.co/coloteong/lab1_random
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-language_detection_fine_tuned_on_xlm_roberta_base_ivanlau_en.md b/docs/_posts/ahmedlone127/2024-09-03-language_detection_fine_tuned_on_xlm_roberta_base_ivanlau_en.md
new file mode 100644
index 00000000000000..f7b4c54725020c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-language_detection_fine_tuned_on_xlm_roberta_base_ivanlau_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English language_detection_fine_tuned_on_xlm_roberta_base_ivanlau XlmRoBertaForSequenceClassification from ivanlau
+author: John Snow Labs
+name: language_detection_fine_tuned_on_xlm_roberta_base_ivanlau
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_fine_tuned_on_xlm_roberta_base_ivanlau` is a English model originally trained by ivanlau.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/language_detection_fine_tuned_on_xlm_roberta_base_ivanlau_en_5.5.0_3.0_1725327841519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_fine_tuned_on_xlm_roberta_base_ivanlau_en_5.5.0_3.0_1725327841519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("language_detection_fine_tuned_on_xlm_roberta_base_ivanlau","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("language_detection_fine_tuned_on_xlm_roberta_base_ivanlau", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection_fine_tuned_on_xlm_roberta_base_ivanlau|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|844.0 MB|
+
+## References
+
+https://huggingface.co/ivanlau/language-detection-fine-tuned-on-xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-legalevalrr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-legalevalrr_pipeline_en.md
new file mode 100644
index 00000000000000..b1422bedb4d707
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-legalevalrr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English legalevalrr_pipeline pipeline MPNetEmbeddings from simplexico
+author: John Snow Labs
+name: legalevalrr_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legalevalrr_pipeline` is a English model originally trained by simplexico.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legalevalrr_pipeline_en_5.5.0_3.0_1725350938303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legalevalrr_pipeline_en_5.5.0_3.0_1725350938303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legalevalrr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legalevalrr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legalevalrr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/simplexico/legalevalrr
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-legalro_bert_for_rhetorical_role_labeling_en.md b/docs/_posts/ahmedlone127/2024-09-03-legalro_bert_for_rhetorical_role_labeling_en.md
new file mode 100644
index 00000000000000..66912a4aea2353
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-legalro_bert_for_rhetorical_role_labeling_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English legalro_bert_for_rhetorical_role_labeling RoBertaForSequenceClassification from engineersaloni159
+author: John Snow Labs
+name: legalro_bert_for_rhetorical_role_labeling
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legalro_bert_for_rhetorical_role_labeling` is a English model originally trained by engineersaloni159.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legalro_bert_for_rhetorical_role_labeling_en_5.5.0_3.0_1725402992901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legalro_bert_for_rhetorical_role_labeling_en_5.5.0_3.0_1725402992901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("legalro_bert_for_rhetorical_role_labeling","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("legalro_bert_for_rhetorical_role_labeling", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legalro_bert_for_rhetorical_role_labeling|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/engineersaloni159/LegalRo-BERt_for_rhetorical_role_labeling
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-legalro_bert_for_rhetorical_role_labeling_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-legalro_bert_for_rhetorical_role_labeling_pipeline_en.md
new file mode 100644
index 00000000000000..ab0010762a8b43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-legalro_bert_for_rhetorical_role_labeling_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English legalro_bert_for_rhetorical_role_labeling_pipeline pipeline RoBertaForSequenceClassification from engineersaloni159
+author: John Snow Labs
+name: legalro_bert_for_rhetorical_role_labeling_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legalro_bert_for_rhetorical_role_labeling_pipeline` is a English model originally trained by engineersaloni159.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legalro_bert_for_rhetorical_role_labeling_pipeline_en_5.5.0_3.0_1725403020813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legalro_bert_for_rhetorical_role_labeling_pipeline_en_5.5.0_3.0_1725403020813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legalro_bert_for_rhetorical_role_labeling_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legalro_bert_for_rhetorical_role_labeling_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legalro_bert_for_rhetorical_role_labeling_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/engineersaloni159/LegalRo-BERt_for_rhetorical_role_labeling
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-literaturetyp_recognizer_en.md b/docs/_posts/ahmedlone127/2024-09-03-literaturetyp_recognizer_en.md
new file mode 100644
index 00000000000000..c5b387d3016b99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-literaturetyp_recognizer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English literaturetyp_recognizer DistilBertForSequenceClassification from LaLaf93
+author: John Snow Labs
+name: literaturetyp_recognizer
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`literaturetyp_recognizer` is a English model originally trained by LaLaf93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/literaturetyp_recognizer_en_5.5.0_3.0_1725329793386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/literaturetyp_recognizer_en_5.5.0_3.0_1725329793386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("literaturetyp_recognizer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("literaturetyp_recognizer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|literaturetyp_recognizer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LaLaf93/LiteratureTyp_recognizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-lithuanian_patentcluster_years_en.md b/docs/_posts/ahmedlone127/2024-09-03-lithuanian_patentcluster_years_en.md
new file mode 100644
index 00000000000000..589d51141df98b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-lithuanian_patentcluster_years_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lithuanian_patentcluster_years MPNetEmbeddings from matthewleechen
+author: John Snow Labs
+name: lithuanian_patentcluster_years
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lithuanian_patentcluster_years` is a English model originally trained by matthewleechen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lithuanian_patentcluster_years_en_5.5.0_3.0_1725350753619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lithuanian_patentcluster_years_en_5.5.0_3.0_1725350753619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("lithuanian_patentcluster_years","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("lithuanian_patentcluster_years","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lithuanian_patentcluster_years|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/matthewleechen/lt_patentcluster_years
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-lithuanian_patentcluster_years_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-lithuanian_patentcluster_years_pipeline_en.md
new file mode 100644
index 00000000000000..753ad1f10aea5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-lithuanian_patentcluster_years_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lithuanian_patentcluster_years_pipeline pipeline MPNetEmbeddings from matthewleechen
+author: John Snow Labs
+name: lithuanian_patentcluster_years_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lithuanian_patentcluster_years_pipeline` is a English model originally trained by matthewleechen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lithuanian_patentcluster_years_pipeline_en_5.5.0_3.0_1725350777552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lithuanian_patentcluster_years_pipeline_en_5.5.0_3.0_1725350777552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lithuanian_patentcluster_years_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lithuanian_patentcluster_years_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lithuanian_patentcluster_years_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/matthewleechen/lt_patentcluster_years
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_n4_it.md b/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_n4_it.md
new file mode 100644
index 00000000000000..00cd54178487eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_n4_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian lld_valbadia_ita_loresmt_n4 MarianTransformer from sfrontull
+author: John Snow Labs
+name: lld_valbadia_ita_loresmt_n4
+date: 2024-09-03
+tags: [it, open_source, onnx, translation, marian]
+task: Translation
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lld_valbadia_ita_loresmt_n4` is a Italian model originally trained by sfrontull.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lld_valbadia_ita_loresmt_n4_it_5.5.0_3.0_1725347144175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lld_valbadia_ita_loresmt_n4_it_5.5.0_3.0_1725347144175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lld_valbadia_ita_loresmt_n4","it") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lld_valbadia_ita_loresmt_n4","it") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lld_valbadia_ita_loresmt_n4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|it|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/sfrontull/lld_valbadia-ita-loresmt-N4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_n4_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_n4_pipeline_it.md
new file mode 100644
index 00000000000000..d4b69896766d66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_n4_pipeline_it.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Italian lld_valbadia_ita_loresmt_n4_pipeline pipeline MarianTransformer from sfrontull
+author: John Snow Labs
+name: lld_valbadia_ita_loresmt_n4_pipeline
+date: 2024-09-03
+tags: [it, open_source, pipeline, onnx]
+task: Translation
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lld_valbadia_ita_loresmt_n4_pipeline` is a Italian model originally trained by sfrontull.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lld_valbadia_ita_loresmt_n4_pipeline_it_5.5.0_3.0_1725347164425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lld_valbadia_ita_loresmt_n4_pipeline_it_5.5.0_3.0_1725347164425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lld_valbadia_ita_loresmt_n4_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lld_valbadia_ita_loresmt_n4_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lld_valbadia_ita_loresmt_n4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|410.9 MB|
+
+## References
+
+https://huggingface.co/sfrontull/lld_valbadia-ita-loresmt-N4
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_r4_it.md b/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_r4_it.md
new file mode 100644
index 00000000000000..fccc8523a634eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_r4_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian lld_valbadia_ita_loresmt_r4 MarianTransformer from sfrontull
+author: John Snow Labs
+name: lld_valbadia_ita_loresmt_r4
+date: 2024-09-03
+tags: [it, open_source, onnx, translation, marian]
+task: Translation
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lld_valbadia_ita_loresmt_r4` is a Italian model originally trained by sfrontull.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lld_valbadia_ita_loresmt_r4_it_5.5.0_3.0_1725347062978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lld_valbadia_ita_loresmt_r4_it_5.5.0_3.0_1725347062978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lld_valbadia_ita_loresmt_r4","it") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lld_valbadia_ita_loresmt_r4","it") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lld_valbadia_ita_loresmt_r4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|it|
+|Size:|410.5 MB|
+
+## References
+
+https://huggingface.co/sfrontull/lld_valbadia-ita-loresmt-R4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_r4_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_r4_pipeline_it.md
new file mode 100644
index 00000000000000..d18cd09bac7a78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-lld_valbadia_ita_loresmt_r4_pipeline_it.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Italian lld_valbadia_ita_loresmt_r4_pipeline pipeline MarianTransformer from sfrontull
+author: John Snow Labs
+name: lld_valbadia_ita_loresmt_r4_pipeline
+date: 2024-09-03
+tags: [it, open_source, pipeline, onnx]
+task: Translation
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lld_valbadia_ita_loresmt_r4_pipeline` is a Italian model originally trained by sfrontull.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lld_valbadia_ita_loresmt_r4_pipeline_it_5.5.0_3.0_1725347084633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lld_valbadia_ita_loresmt_r4_pipeline_it_5.5.0_3.0_1725347084633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lld_valbadia_ita_loresmt_r4_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lld_valbadia_ita_loresmt_r4_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lld_valbadia_ita_loresmt_r4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|411.0 MB|
+
+## References
+
+https://huggingface.co/sfrontull/lld_valbadia-ita-loresmt-R4
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-luganda_ner_v6_conrad747_en.md b/docs/_posts/ahmedlone127/2024-09-03-luganda_ner_v6_conrad747_en.md
new file mode 100644
index 00000000000000..3c8a795d482f37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-luganda_ner_v6_conrad747_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English luganda_ner_v6_conrad747 XlmRoBertaForTokenClassification from Conrad747
+author: John Snow Labs
+name: luganda_ner_v6_conrad747
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`luganda_ner_v6_conrad747` is a English model originally trained by Conrad747.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/luganda_ner_v6_conrad747_en_5.5.0_3.0_1725373242625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/luganda_ner_v6_conrad747_en_5.5.0_3.0_1725373242625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("luganda_ner_v6_conrad747","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("luganda_ner_v6_conrad747", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|luganda_ner_v6_conrad747|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|797.5 MB|
+
+## References
+
+https://huggingface.co/Conrad747/luganda-ner-v6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-luganda_ner_v6_conrad747_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-luganda_ner_v6_conrad747_pipeline_en.md
new file mode 100644
index 00000000000000..3209ca9353f904
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-luganda_ner_v6_conrad747_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English luganda_ner_v6_conrad747_pipeline pipeline XlmRoBertaForTokenClassification from Conrad747
+author: John Snow Labs
+name: luganda_ner_v6_conrad747_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`luganda_ner_v6_conrad747_pipeline` is a English model originally trained by Conrad747.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/luganda_ner_v6_conrad747_pipeline_en_5.5.0_3.0_1725373373858.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/luganda_ner_v6_conrad747_pipeline_en_5.5.0_3.0_1725373373858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("luganda_ner_v6_conrad747_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("luganda_ner_v6_conrad747_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|luganda_ner_v6_conrad747_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|797.6 MB|
+
+## References
+
+https://huggingface.co/Conrad747/luganda-ner-v6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-maltese_coref_english_spanish_coref_exp_en.md b/docs/_posts/ahmedlone127/2024-09-03-maltese_coref_english_spanish_coref_exp_en.md
new file mode 100644
index 00000000000000..84b90d924dde1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-maltese_coref_english_spanish_coref_exp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_coref_english_spanish_coref_exp MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_spanish_coref_exp
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_spanish_coref_exp` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_spanish_coref_exp_en_5.5.0_3.0_1725404832048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_spanish_coref_exp_en_5.5.0_3.0_1725404832048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_coref_english_spanish_coref_exp","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_coref_english_spanish_coref_exp","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_spanish_coref_exp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|540.3 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_es_coref_exp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-maltese_coref_english_spanish_coref_exp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-maltese_coref_english_spanish_coref_exp_pipeline_en.md
new file mode 100644
index 00000000000000..e55c5b10583320
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-maltese_coref_english_spanish_coref_exp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English maltese_coref_english_spanish_coref_exp_pipeline pipeline MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_spanish_coref_exp_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_spanish_coref_exp_pipeline` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_spanish_coref_exp_pipeline_en_5.5.0_3.0_1725404861533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_spanish_coref_exp_pipeline_en_5.5.0_3.0_1725404861533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("maltese_coref_english_spanish_coref_exp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("maltese_coref_english_spanish_coref_exp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_spanish_coref_exp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.8 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_es_coref_exp
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_en.md
new file mode 100644
index 00000000000000..44b1fa5fa77fdc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256 MarianTransformer from ac729735256
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256` is a English model originally trained by ac729735256.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_en_5.5.0_3.0_1725403804011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_en_5.5.0_3.0_1725403804011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.2 MB|
+
+## References
+
+https://huggingface.co/ac729735256/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline_en.md
new file mode 100644
index 00000000000000..23e9aed1f977a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline pipeline MarianTransformer from ac729735256
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline` is a English model originally trained by ac729735256.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline_en_5.5.0_3.0_1725403831821.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline_en_5.5.0_3.0_1725403831821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_ac729735256_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/ac729735256/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_en.md
new file mode 100644
index 00000000000000..54c9ca2d0c1920
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke MarianTransformer from IreNkweke
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke` is a English model originally trained by IreNkweke.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_en_5.5.0_3.0_1725404411155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_en_5.5.0_3.0_1725404411155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.2 MB|
+
+## References
+
+https://huggingface.co/IreNkweke/marian-finetuned-kde4-en-to-fr-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline_en.md
new file mode 100644
index 00000000000000..536e6bce8e405e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline pipeline MarianTransformer from IreNkweke
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline` is a English model originally trained by IreNkweke.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline_en_5.5.0_3.0_1725404439321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline_en_5.5.0_3.0_1725404439321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_irenkweke_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/IreNkweke/marian-finetuned-kde4-en-to-fr-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_en.md
new file mode 100644
index 00000000000000..be8d44b0331f46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger MarianTransformer from cleverbrugger
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger` is a English model originally trained by cleverbrugger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_en_5.5.0_3.0_1725405219256.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_en_5.5.0_3.0_1725405219256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/cleverbrugger/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline_en.md
new file mode 100644
index 00000000000000..015f352b20f46d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline pipeline MarianTransformer from cleverbrugger
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline` is a English model originally trained by cleverbrugger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline_en_5.5.0_3.0_1725405246600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline_en_5.5.0_3.0_1725405246600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_cleverbrugger_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/cleverbrugger/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_en.md
new file mode 100644
index 00000000000000..03a70dec3d0820
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim MarianTransformer from JakeYunwooKim
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim` is a English model originally trained by JakeYunwooKim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_en_5.5.0_3.0_1725404943448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_en_5.5.0_3.0_1725404943448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/JakeYunwooKim/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline_en.md
new file mode 100644
index 00000000000000..ea55debc066db5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline pipeline MarianTransformer from JakeYunwooKim
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline` is a English model originally trained by JakeYunwooKim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline_en_5.5.0_3.0_1725404970708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline_en_5.5.0_3.0_1725404970708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_jakeyunwookim_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/JakeYunwooKim/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda_en.md
new file mode 100644
index 00000000000000..764892f59d5771
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda MarianTransformer from icep0ps
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda` is a English model originally trained by icep0ps.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda_en_5.5.0_3.0_1725403723323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda_en_5.5.0_3.0_1725403723323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_kinyarwanda|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|210.5 MB|
+
+## References
+
+https://huggingface.co/icep0ps/marian-finetuned-kde4-en-to-rw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_german_grammar_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_german_grammar_en.md
new file mode 100644
index 00000000000000..f5f24ac5963d13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_german_grammar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_german_grammar MarianTransformer from aware-ai
+author: John Snow Labs
+name: marian_german_grammar
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_german_grammar` is a English model originally trained by aware-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_german_grammar_en_5.5.0_3.0_1725404766358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_german_grammar_en_5.5.0_3.0_1725404766358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_german_grammar","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_german_grammar","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_german_grammar|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|499.4 MB|
+
+## References
+
+https://huggingface.co/aware-ai/marian-german-grammar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marian_german_grammar_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-marian_german_grammar_pipeline_en.md
new file mode 100644
index 00000000000000..ce7c10e8458803
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marian_german_grammar_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_german_grammar_pipeline pipeline MarianTransformer from aware-ai
+author: John Snow Labs
+name: marian_german_grammar_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_german_grammar_pipeline` is a English model originally trained by aware-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_german_grammar_pipeline_en_5.5.0_3.0_1725404793819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_german_grammar_pipeline_en_5.5.0_3.0_1725404793819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_german_grammar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_german_grammar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_german_grammar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|499.9 MB|
+
+## References
+
+https://huggingface.co/aware-ai/marian-german-grammar
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_large_en.md b/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_large_en.md
new file mode 100644
index 00000000000000..ad8906c66a3222
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mariancg_conala_large MarianTransformer from AhmedSSoliman
+author: John Snow Labs
+name: mariancg_conala_large
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariancg_conala_large` is a English model originally trained by AhmedSSoliman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mariancg_conala_large_en_5.5.0_3.0_1725405138787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariancg_conala_large_en_5.5.0_3.0_1725405138787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("mariancg_conala_large","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("mariancg_conala_large","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mariancg_conala_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|548.1 MB|
+
+## References
+
+https://huggingface.co/AhmedSSoliman/MarianCG-CoNaLa-Large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_large_pipeline_en.md
new file mode 100644
index 00000000000000..316c602260e4c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mariancg_conala_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mariancg_conala_large_pipeline pipeline MarianTransformer from AhmedSSoliman
+author: John Snow Labs
+name: mariancg_conala_large_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariancg_conala_large_pipeline` is a English model originally trained by AhmedSSoliman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mariancg_conala_large_pipeline_en_5.5.0_3.0_1725405168827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariancg_conala_large_pipeline_en_5.5.0_3.0_1725405168827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mariancg_conala_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mariancg_conala_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mariancg_conala_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|548.6 MB|
+
+## References
+
+https://huggingface.co/AhmedSSoliman/MarianCG-CoNaLa-Large
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marianmt_tatoeba_enru_en.md b/docs/_posts/ahmedlone127/2024-09-03-marianmt_tatoeba_enru_en.md
new file mode 100644
index 00000000000000..7f9d815ac7beb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marianmt_tatoeba_enru_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marianmt_tatoeba_enru MarianTransformer from DeepPavlov
+author: John Snow Labs
+name: marianmt_tatoeba_enru
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_tatoeba_enru` is a English model originally trained by DeepPavlov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_tatoeba_enru_en_5.5.0_3.0_1725346537409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_tatoeba_enru_en_5.5.0_3.0_1725346537409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marianmt_tatoeba_enru","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marianmt_tatoeba_enru","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marianmt_tatoeba_enru|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|527.6 MB|
+
+## References
+
+https://huggingface.co/DeepPavlov/marianmt-tatoeba-enru
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mariannmt_tatoeba_luxembourgish_english_lb.md b/docs/_posts/ahmedlone127/2024-09-03-mariannmt_tatoeba_luxembourgish_english_lb.md
new file mode 100644
index 00000000000000..0741ab83ce6f8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mariannmt_tatoeba_luxembourgish_english_lb.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Letzeburgesch, Luxembourgish mariannmt_tatoeba_luxembourgish_english MarianTransformer from mbarnig
+author: John Snow Labs
+name: mariannmt_tatoeba_luxembourgish_english
+date: 2024-09-03
+tags: [lb, open_source, onnx, translation, marian]
+task: Translation
+language: lb
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariannmt_tatoeba_luxembourgish_english` is a Letzeburgesch, Luxembourgish model originally trained by mbarnig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mariannmt_tatoeba_luxembourgish_english_lb_5.5.0_3.0_1725404608318.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariannmt_tatoeba_luxembourgish_english_lb_5.5.0_3.0_1725404608318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("mariannmt_tatoeba_luxembourgish_english","lb") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("mariannmt_tatoeba_luxembourgish_english","lb") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mariannmt_tatoeba_luxembourgish_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|lb|
+|Size:|284.9 MB|
+
+## References
+
+https://huggingface.co/mbarnig/marianNMT-tatoeba-lb-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mariannmt_tatoeba_luxembourgish_english_pipeline_lb.md b/docs/_posts/ahmedlone127/2024-09-03-mariannmt_tatoeba_luxembourgish_english_pipeline_lb.md
new file mode 100644
index 00000000000000..f14326da52486c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mariannmt_tatoeba_luxembourgish_english_pipeline_lb.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Letzeburgesch, Luxembourgish mariannmt_tatoeba_luxembourgish_english_pipeline pipeline MarianTransformer from mbarnig
+author: John Snow Labs
+name: mariannmt_tatoeba_luxembourgish_english_pipeline
+date: 2024-09-03
+tags: [lb, open_source, pipeline, onnx]
+task: Translation
+language: lb
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariannmt_tatoeba_luxembourgish_english_pipeline` is a Letzeburgesch, Luxembourgish model originally trained by mbarnig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mariannmt_tatoeba_luxembourgish_english_pipeline_lb_5.5.0_3.0_1725404698276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariannmt_tatoeba_luxembourgish_english_pipeline_lb_5.5.0_3.0_1725404698276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mariannmt_tatoeba_luxembourgish_english_pipeline", lang = "lb")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mariannmt_tatoeba_luxembourgish_english_pipeline", lang = "lb")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mariannmt_tatoeba_luxembourgish_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|lb|
+|Size:|285.4 MB|
+
+## References
+
+https://huggingface.co/mbarnig/marianNMT-tatoeba-lb-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marsilia_embeddings_english_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-marsilia_embeddings_english_base_en.md
new file mode 100644
index 00000000000000..ff49337fb43b61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marsilia_embeddings_english_base_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English marsilia_embeddings_english_base BGEEmbeddings from sujet-ai
+author: John Snow Labs
+name: marsilia_embeddings_english_base
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marsilia_embeddings_english_base` is a English model originally trained by sujet-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marsilia_embeddings_english_base_en_5.5.0_3.0_1725356527062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marsilia_embeddings_english_base_en_5.5.0_3.0_1725356527062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("marsilia_embeddings_english_base","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("marsilia_embeddings_english_base","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marsilia_embeddings_english_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|393.9 MB|
+
+## References
+
+https://huggingface.co/sujet-ai/Marsilia-Embeddings-EN-Base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-marsilia_embeddings_english_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-marsilia_embeddings_english_base_pipeline_en.md
new file mode 100644
index 00000000000000..25efc0e468af2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-marsilia_embeddings_english_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English marsilia_embeddings_english_base_pipeline pipeline BGEEmbeddings from sujet-ai
+author: John Snow Labs
+name: marsilia_embeddings_english_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marsilia_embeddings_english_base_pipeline` is a English model originally trained by sujet-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marsilia_embeddings_english_base_pipeline_en_5.5.0_3.0_1725356550724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marsilia_embeddings_english_base_pipeline_en_5.5.0_3.0_1725356550724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marsilia_embeddings_english_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marsilia_embeddings_english_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marsilia_embeddings_english_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|393.9 MB|
+
+## References
+
+https://huggingface.co/sujet-ai/Marsilia-Embeddings-EN-Base
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-math_structure_deberta_en.md b/docs/_posts/ahmedlone127/2024-09-03-math_structure_deberta_en.md
new file mode 100644
index 00000000000000..3d5891942518f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-math_structure_deberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English math_structure_deberta DeBertaEmbeddings from ddrg
+author: John Snow Labs
+name: math_structure_deberta
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, deberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`math_structure_deberta` is a English model originally trained by ddrg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/math_structure_deberta_en_5.5.0_3.0_1725330697093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/math_structure_deberta_en_5.5.0_3.0_1725330697093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("math_structure_deberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("math_structure_deberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|math_structure_deberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|en|
+|Size:|690.5 MB|
+
+## References
+
+https://huggingface.co/ddrg/math_structure_deberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mbti_en.md b/docs/_posts/ahmedlone127/2024-09-03-mbti_en.md
new file mode 100644
index 00000000000000..dce3952d7353fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mbti_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mbti RoBertaForSequenceClassification from dwancin
+author: John Snow Labs
+name: mbti
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbti` is a English model originally trained by dwancin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbti_en_5.5.0_3.0_1725368793007.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbti_en_5.5.0_3.0_1725368793007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("mbti","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("mbti", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbti|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/dwancin/mbti
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mbti_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mbti_pipeline_en.md
new file mode 100644
index 00000000000000..bdbdbe4652dc40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mbti_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mbti_pipeline pipeline RoBertaForSequenceClassification from dwancin
+author: John Snow Labs
+name: mbti_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbti_pipeline` is a English model originally trained by dwancin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbti_pipeline_en_5.5.0_3.0_1725368819324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbti_pipeline_en_5.5.0_3.0_1725368819324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mbti_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbti_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbti_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/dwancin/mbti
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_expl_extraction_multi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_expl_extraction_multi_pipeline_en.md
new file mode 100644
index 00000000000000..bc791fd8e41294
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_expl_extraction_multi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_expl_extraction_multi_pipeline pipeline DeBertaForTokenClassification from HiTZ
+author: John Snow Labs
+name: mdeberta_expl_extraction_multi_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_expl_extraction_multi_pipeline` is a English model originally trained by HiTZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_expl_extraction_multi_pipeline_en_5.5.0_3.0_1725387496966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_expl_extraction_multi_pipeline_en_5.5.0_3.0_1725387496966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_expl_extraction_multi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_expl_extraction_multi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_expl_extraction_multi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|918.6 MB|
+
+## References
+
+https://huggingface.co/HiTZ/mdeberta-expl-extraction-multi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..9444b25a5b3103
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_finetuned_imdb DeBertaEmbeddings from msthil2
+author: John Snow Labs
+name: mdeberta_v3_base_finetuned_imdb
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, deberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_finetuned_imdb` is a English model originally trained by msthil2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuned_imdb_en_5.5.0_3.0_1725377014149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuned_imdb_en_5.5.0_3.0_1725377014149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("mdeberta_v3_base_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("mdeberta_v3_base_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|en|
+|Size:|679.7 MB|
+
+## References
+
+https://huggingface.co/msthil2/mdeberta-v3-base-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..87969722368744
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_finetuned_imdb_pipeline pipeline DeBertaEmbeddings from msthil2
+author: John Snow Labs
+name: mdeberta_v3_base_finetuned_imdb_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_finetuned_imdb_pipeline` is a English model originally trained by msthil2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuned_imdb_pipeline_en_5.5.0_3.0_1725377211243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuned_imdb_pipeline_en_5.5.0_3.0_1725377211243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|679.7 MB|
+
+## References
+
+https://huggingface.co/msthil2/mdeberta-v3-base-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_sayula_popoluca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_sayula_popoluca_pipeline_en.md
new file mode 100644
index 00000000000000..8948bd73857cdb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_finetuned_sayula_popoluca_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_finetuned_sayula_popoluca_pipeline pipeline DeBertaForTokenClassification from Emanuel
+author: John Snow Labs
+name: mdeberta_v3_base_finetuned_sayula_popoluca_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_finetuned_sayula_popoluca_pipeline` is a English model originally trained by Emanuel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuned_sayula_popoluca_pipeline_en_5.5.0_3.0_1725401056047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuned_sayula_popoluca_pipeline_en_5.5.0_3.0_1725401056047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_finetuned_sayula_popoluca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_finetuned_sayula_popoluca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_finetuned_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|852.3 MB|
+
+## References
+
+https://huggingface.co/Emanuel/mdeberta-v3-base-finetuned-pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_nubes_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_nubes_pipeline_es.md
new file mode 100644
index 00000000000000..4a335b7a62e3ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_nubes_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish mdeberta_v3_base_nubes_pipeline pipeline DeBertaForTokenClassification from IIC
+author: John Snow Labs
+name: mdeberta_v3_base_nubes_pipeline
+date: 2024-09-03
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_nubes_pipeline` is a Castilian, Spanish model originally trained by IIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_nubes_pipeline_es_5.5.0_3.0_1725400866341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_nubes_pipeline_es_5.5.0_3.0_1725400866341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_nubes_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_nubes_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_nubes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|797.4 MB|
+
+## References
+
+https://huggingface.co/IIC/mdeberta-v3-base-nubes
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_offensive_mlm_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_offensive_mlm_pipeline_tr.md
new file mode 100644
index 00000000000000..723d44574ea8fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_offensive_mlm_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish mdeberta_v3_base_offensive_mlm_pipeline pipeline DeBertaEmbeddings from Overfit-GM
+author: John Snow Labs
+name: mdeberta_v3_base_offensive_mlm_pipeline
+date: 2024-09-03
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_offensive_mlm_pipeline` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_offensive_mlm_pipeline_tr_5.5.0_3.0_1725377347324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_offensive_mlm_pipeline_tr_5.5.0_3.0_1725377347324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_offensive_mlm_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_offensive_mlm_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_offensive_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Overfit-GM/mdeberta-v3-base-offensive-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_offensive_mlm_tr.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_offensive_mlm_tr.md
new file mode 100644
index 00000000000000..aaaf2bec9babe6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_offensive_mlm_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish mdeberta_v3_base_offensive_mlm DeBertaEmbeddings from Overfit-GM
+author: John Snow Labs
+name: mdeberta_v3_base_offensive_mlm
+date: 2024-09-03
+tags: [tr, open_source, onnx, embeddings, deberta]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_offensive_mlm` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_offensive_mlm_tr_5.5.0_3.0_1725377292586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_offensive_mlm_tr_5.5.0_3.0_1725377292586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("mdeberta_v3_base_offensive_mlm","tr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("mdeberta_v3_base_offensive_mlm","tr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_offensive_mlm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|tr|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Overfit-GM/mdeberta-v3-base-offensive-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_socialdisner_es.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_socialdisner_es.md
new file mode 100644
index 00000000000000..4fc3a78792aabf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_socialdisner_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish mdeberta_v3_base_socialdisner DeBertaForTokenClassification from IIC
+author: John Snow Labs
+name: mdeberta_v3_base_socialdisner
+date: 2024-09-03
+tags: [es, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_socialdisner` is a Castilian, Spanish model originally trained by IIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_socialdisner_es_5.5.0_3.0_1725387851819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_socialdisner_es_5.5.0_3.0_1725387851819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_socialdisner","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_socialdisner", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_socialdisner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|805.9 MB|
+
+## References
+
+https://huggingface.co/IIC/mdeberta-v3-base-socialdisner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_socialdisner_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_socialdisner_pipeline_es.md
new file mode 100644
index 00000000000000..5faedc9959f35a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mdeberta_v3_base_socialdisner_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish mdeberta_v3_base_socialdisner_pipeline pipeline DeBertaForTokenClassification from IIC
+author: John Snow Labs
+name: mdeberta_v3_base_socialdisner_pipeline
+date: 2024-09-03
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_socialdisner_pipeline` is a Castilian, Spanish model originally trained by IIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_socialdisner_pipeline_es_5.5.0_3.0_1725387997916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_socialdisner_pipeline_es_5.5.0_3.0_1725387997916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_socialdisner_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_socialdisner_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_socialdisner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|805.9 MB|
+
+## References
+
+https://huggingface.co/IIC/mdeberta-v3-base-socialdisner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-medical_english_chinese_8_29_en.md b/docs/_posts/ahmedlone127/2024-09-03-medical_english_chinese_8_29_en.md
new file mode 100644
index 00000000000000..4892fa5b25fe5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-medical_english_chinese_8_29_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English medical_english_chinese_8_29 MarianTransformer from DogGoesBark
+author: John Snow Labs
+name: medical_english_chinese_8_29
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_english_chinese_8_29` is a English model originally trained by DogGoesBark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_english_chinese_8_29_en_5.5.0_3.0_1725346731223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_english_chinese_8_29_en_5.5.0_3.0_1725346731223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("medical_english_chinese_8_29","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("medical_english_chinese_8_29","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medical_english_chinese_8_29|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|541.3 MB|
+
+## References
+
+https://huggingface.co/DogGoesBark/medical_en_zh_8_29
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-medical_english_chinese_8_29_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-medical_english_chinese_8_29_pipeline_en.md
new file mode 100644
index 00000000000000..c567d059ec2385
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-medical_english_chinese_8_29_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English medical_english_chinese_8_29_pipeline pipeline MarianTransformer from DogGoesBark
+author: John Snow Labs
+name: medical_english_chinese_8_29_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_english_chinese_8_29_pipeline` is a English model originally trained by DogGoesBark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_english_chinese_8_29_pipeline_en_5.5.0_3.0_1725346758698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_english_chinese_8_29_pipeline_en_5.5.0_3.0_1725346758698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medical_english_chinese_8_29_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medical_english_chinese_8_29_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medical_english_chinese_8_29_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|541.8 MB|
+
+## References
+
+https://huggingface.co/DogGoesBark/medical_en_zh_8_29
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-medical_pubmed_8_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-medical_pubmed_8_2_pipeline_en.md
new file mode 100644
index 00000000000000..21355380a86170
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-medical_pubmed_8_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English medical_pubmed_8_2_pipeline pipeline MarianTransformer from DogGoesBark
+author: John Snow Labs
+name: medical_pubmed_8_2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_pubmed_8_2_pipeline` is a English model originally trained by DogGoesBark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_pubmed_8_2_pipeline_en_5.5.0_3.0_1725404720223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_pubmed_8_2_pipeline_en_5.5.0_3.0_1725404720223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medical_pubmed_8_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medical_pubmed_8_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medical_pubmed_8_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.6 MB|
+
+## References
+
+https://huggingface.co/DogGoesBark/medical_pubmed_8_2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-medrurobertalarge_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-03-medrurobertalarge_pipeline_ru.md
new file mode 100644
index 00000000000000..36b644c16cb809
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-medrurobertalarge_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian medrurobertalarge_pipeline pipeline RoBertaEmbeddings from DmitryPogrebnoy
+author: John Snow Labs
+name: medrurobertalarge_pipeline
+date: 2024-09-03
+tags: [ru, open_source, pipeline, onnx]
+task: Embeddings
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medrurobertalarge_pipeline` is a Russian model originally trained by DmitryPogrebnoy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medrurobertalarge_pipeline_ru_5.5.0_3.0_1725375743433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medrurobertalarge_pipeline_ru_5.5.0_3.0_1725375743433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medrurobertalarge_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medrurobertalarge_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medrurobertalarge_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/DmitryPogrebnoy/MedRuRobertaLarge
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-memo_model_2500_en.md b/docs/_posts/ahmedlone127/2024-09-03-memo_model_2500_en.md
new file mode 100644
index 00000000000000..2c31df71f11182
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-memo_model_2500_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English memo_model_2500 XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: memo_model_2500
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_model_2500` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_model_2500_en_5.5.0_3.0_1725352771507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_model_2500_en_5.5.0_3.0_1725352771507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("memo_model_2500","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("memo_model_2500","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_model_2500|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_model_2500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-memo_model_2500_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-memo_model_2500_pipeline_en.md
new file mode 100644
index 00000000000000..b545c6edbec22f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-memo_model_2500_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English memo_model_2500_pipeline pipeline XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: memo_model_2500_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_model_2500_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_model_2500_pipeline_en_5.5.0_3.0_1725352824965.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_model_2500_pipeline_en_5.5.0_3.0_1725352824965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("memo_model_2500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("memo_model_2500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_model_2500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_model_2500
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mi_roberta_base_finetuned_mental_health_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mi_roberta_base_finetuned_mental_health_pipeline_en.md
new file mode 100644
index 00000000000000..a6c9704614a928
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mi_roberta_base_finetuned_mental_health_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mi_roberta_base_finetuned_mental_health_pipeline pipeline RoBertaForSequenceClassification from mavinsao
+author: John Snow Labs
+name: mi_roberta_base_finetuned_mental_health_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mi_roberta_base_finetuned_mental_health_pipeline` is a English model originally trained by mavinsao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mi_roberta_base_finetuned_mental_health_pipeline_en_5.5.0_3.0_1725336752271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mi_roberta_base_finetuned_mental_health_pipeline_en_5.5.0_3.0_1725336752271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mi_roberta_base_finetuned_mental_health_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mi_roberta_base_finetuned_mental_health_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mi_roberta_base_finetuned_mental_health_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/mavinsao/mi-roberta-base-finetuned-mental-health
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs_en.md b/docs/_posts/ahmedlone127/2024-09-03-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs_en.md
new file mode 100644
index 00000000000000..e5df19d96a82a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs_en_5.5.0_3.0_1725387671057.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs_en_5.5.0_3.0_1725387671057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_30_docs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-breast-without-castellon-castellon-30-docs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline_en.md
new file mode 100644
index 00000000000000..0bc5693a1f1c0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline pipeline DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline_en_5.5.0_3.0_1725400815087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline_en_5.5.0_3.0_1725400815087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_conll2003_latin_fe_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-la-fe-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mimic_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-mimic_roberta_base_en.md
new file mode 100644
index 00000000000000..6e655f58aed92a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mimic_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mimic_roberta_base RoBertaEmbeddings from xdai
+author: John Snow Labs
+name: mimic_roberta_base
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mimic_roberta_base` is a English model originally trained by xdai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mimic_roberta_base_en_5.5.0_3.0_1725382440018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mimic_roberta_base_en_5.5.0_3.0_1725382440018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("mimic_roberta_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("mimic_roberta_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mimic_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/xdai/mimic_roberta_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mimic_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mimic_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..383951762a84fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mimic_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mimic_roberta_base_pipeline pipeline RoBertaEmbeddings from xdai
+author: John Snow Labs
+name: mimic_roberta_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mimic_roberta_base_pipeline` is a English model originally trained by xdai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mimic_roberta_base_pipeline_en_5.5.0_3.0_1725382467502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mimic_roberta_base_pipeline_en_5.5.0_3.0_1725382467502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mimic_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mimic_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mimic_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/xdai/mimic_roberta_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mini_legal_distillbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-mini_legal_distillbert_en.md
new file mode 100644
index 00000000000000..43063ad1c59c14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mini_legal_distillbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mini_legal_distillbert DistilBertForSequenceClassification from engineersaloni159
+author: John Snow Labs
+name: mini_legal_distillbert
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mini_legal_distillbert` is a English model originally trained by engineersaloni159.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mini_legal_distillbert_en_5.5.0_3.0_1725330283164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mini_legal_distillbert_en_5.5.0_3.0_1725330283164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("mini_legal_distillbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("mini_legal_distillbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mini_legal_distillbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/engineersaloni159/mini_legal_distillbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mini_legal_distillbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mini_legal_distillbert_pipeline_en.md
new file mode 100644
index 00000000000000..b4c0808afe14ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mini_legal_distillbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mini_legal_distillbert_pipeline pipeline DistilBertForSequenceClassification from engineersaloni159
+author: John Snow Labs
+name: mini_legal_distillbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mini_legal_distillbert_pipeline` is a English model originally trained by engineersaloni159.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mini_legal_distillbert_pipeline_en_5.5.0_3.0_1725330295363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mini_legal_distillbert_pipeline_en_5.5.0_3.0_1725330295363.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mini_legal_distillbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mini_legal_distillbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mini_legal_distillbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/engineersaloni159/mini_legal_distillbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mlm_xlmr_base_vlsp_en.md b/docs/_posts/ahmedlone127/2024-09-03-mlm_xlmr_base_vlsp_en.md
new file mode 100644
index 00000000000000..0962b7056349b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mlm_xlmr_base_vlsp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mlm_xlmr_base_vlsp XlmRoBertaEmbeddings from vietn
+author: John Snow Labs
+name: mlm_xlmr_base_vlsp
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_xlmr_base_vlsp` is a English model originally trained by vietn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_xlmr_base_vlsp_en_5.5.0_3.0_1725390352970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_xlmr_base_vlsp_en_5.5.0_3.0_1725390352970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("mlm_xlmr_base_vlsp","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("mlm_xlmr_base_vlsp","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_xlmr_base_vlsp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/vietn/mlm-xlmr_base-vlsp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mlm_xlmr_base_vlsp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mlm_xlmr_base_vlsp_pipeline_en.md
new file mode 100644
index 00000000000000..b6eb6036e860ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mlm_xlmr_base_vlsp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mlm_xlmr_base_vlsp_pipeline pipeline XlmRoBertaEmbeddings from vietn
+author: John Snow Labs
+name: mlm_xlmr_base_vlsp_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_xlmr_base_vlsp_pipeline` is a English model originally trained by vietn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_xlmr_base_vlsp_pipeline_en_5.5.0_3.0_1725390411204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_xlmr_base_vlsp_pipeline_en_5.5.0_3.0_1725390411204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mlm_xlmr_base_vlsp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mlm_xlmr_base_vlsp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_xlmr_base_vlsp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/vietn/mlm-xlmr_base-vlsp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline_en.md
new file mode 100644
index 00000000000000..f47a6581f22155
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline pipeline XlmRoBertaForSequenceClassification from nreimers
+author: John Snow Labs
+name: mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline` is a English model originally trained by nreimers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline_en_5.5.0_3.0_1725328286914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline_en_5.5.0_3.0_1725328286914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mmarco_mminilmv2_l12_h384_v1_nreimers_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|399.6 MB|
+
+## References
+
+https://huggingface.co/nreimers/mmarco-mMiniLMv2-L12-H384-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mminilm_l6_v2_mmarco_v2_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-03-mminilm_l6_v2_mmarco_v2_pipeline_pt.md
new file mode 100644
index 00000000000000..532ff1f0198a68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mminilm_l6_v2_mmarco_v2_pipeline_pt.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Portuguese mminilm_l6_v2_mmarco_v2_pipeline pipeline XlmRoBertaForSequenceClassification from unicamp-dl
+author: John Snow Labs
+name: mminilm_l6_v2_mmarco_v2_pipeline
+date: 2024-09-03
+tags: [pt, open_source, pipeline, onnx]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_mmarco_v2_pipeline` is a Portuguese model originally trained by unicamp-dl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_mmarco_v2_pipeline_pt_5.5.0_3.0_1725396666381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_mmarco_v2_pipeline_pt_5.5.0_3.0_1725396666381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mminilm_l6_v2_mmarco_v2_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mminilm_l6_v2_mmarco_v2_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mminilm_l6_v2_mmarco_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|368.5 MB|
+
+## References
+
+https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-mmarco-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mminilm_l6_v2_mmarco_v2_pt.md b/docs/_posts/ahmedlone127/2024-09-03-mminilm_l6_v2_mmarco_v2_pt.md
new file mode 100644
index 00000000000000..72763c31e9a0b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mminilm_l6_v2_mmarco_v2_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese mminilm_l6_v2_mmarco_v2 XlmRoBertaForSequenceClassification from unicamp-dl
+author: John Snow Labs
+name: mminilm_l6_v2_mmarco_v2
+date: 2024-09-03
+tags: [pt, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_mmarco_v2` is a Portuguese model originally trained by unicamp-dl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_mmarco_v2_pt_5.5.0_3.0_1725396644761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_mmarco_v2_pt_5.5.0_3.0_1725396644761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("mminilm_l6_v2_mmarco_v2","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mminilm_l6_v2_mmarco_v2", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mminilm_l6_v2_mmarco_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|pt|
+|Size:|368.5 MB|
+
+## References
+
+https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-mmarco-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_en.md b/docs/_posts/ahmedlone127/2024-09-03-mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_en.md
new file mode 100644
index 00000000000000..fa2d86d57c22cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers XlmRoBertaEmbeddings from nreimers
+author: John Snow Labs
+name: mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers` is a English model originally trained by nreimers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_en_5.5.0_3.0_1725390635868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_en_5.5.0_3.0_1725390635868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|257.3 MB|
+
+## References
+
+https://huggingface.co/nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline_en.md
new file mode 100644
index 00000000000000..8943dc3c3c13fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline pipeline XlmRoBertaEmbeddings from nreimers
+author: John Snow Labs
+name: mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline` is a English model originally trained by nreimers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline_en_5.5.0_3.0_1725390713013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline_en_5.5.0_3.0_1725390713013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mminilmv2_l6_h384_distilled_from_xlmr_large_nreimers_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|257.3 MB|
+
+## References
+
+https://huggingface.co/nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mobilebert_uncased_squad_v1_en.md b/docs/_posts/ahmedlone127/2024-09-03-mobilebert_uncased_squad_v1_en.md
new file mode 100644
index 00000000000000..57637e7aa3a3d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mobilebert_uncased_squad_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mobilebert_uncased_squad_v1 BertForQuestionAnswering from csarron
+author: John Snow Labs
+name: mobilebert_uncased_squad_v1
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_uncased_squad_v1` is a English model originally trained by csarron.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v1_en_5.5.0_3.0_1725351798095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v1_en_5.5.0_3.0_1725351798095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("mobilebert_uncased_squad_v1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("mobilebert_uncased_squad_v1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mobilebert_uncased_squad_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|92.5 MB|
+
+## References
+
+https://huggingface.co/csarron/mobilebert-uncased-squad-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mobilebert_uncased_squad_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mobilebert_uncased_squad_v1_pipeline_en.md
new file mode 100644
index 00000000000000..aafcd4156fef08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mobilebert_uncased_squad_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mobilebert_uncased_squad_v1_pipeline pipeline BertForQuestionAnswering from csarron
+author: John Snow Labs
+name: mobilebert_uncased_squad_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_uncased_squad_v1_pipeline` is a English model originally trained by csarron.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v1_pipeline_en_5.5.0_3.0_1725351802985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v1_pipeline_en_5.5.0_3.0_1725351802985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mobilebert_uncased_squad_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mobilebert_uncased_squad_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mobilebert_uncased_squad_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|92.5 MB|
+
+## References
+
+https://huggingface.co/csarron/mobilebert-uncased-squad-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-model_spanish_quechua_en.md b/docs/_posts/ahmedlone127/2024-09-03-model_spanish_quechua_en.md
new file mode 100644
index 00000000000000..2b9ed8214b05b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-model_spanish_quechua_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_spanish_quechua MarianTransformer from iBarb
+author: John Snow Labs
+name: model_spanish_quechua
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_spanish_quechua` is a English model originally trained by iBarb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_spanish_quechua_en_5.5.0_3.0_1725345875695.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_spanish_quechua_en_5.5.0_3.0_1725345875695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("model_spanish_quechua","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("model_spanish_quechua","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_spanish_quechua|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.0 MB|
+
+## References
+
+https://huggingface.co/iBarb/Model-es-qu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-model_spanish_quechua_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-model_spanish_quechua_pipeline_en.md
new file mode 100644
index 00000000000000..10973135dd8d6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-model_spanish_quechua_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_spanish_quechua_pipeline pipeline MarianTransformer from iBarb
+author: John Snow Labs
+name: model_spanish_quechua_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_spanish_quechua_pipeline` is a English model originally trained by iBarb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_spanish_quechua_pipeline_en_5.5.0_3.0_1725345905360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_spanish_quechua_pipeline_en_5.5.0_3.0_1725345905360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_spanish_quechua_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_spanish_quechua_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_spanish_quechua_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|539.5 MB|
+
+## References
+
+https://huggingface.co/iBarb/Model-es-qu
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_nli_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_nli_matryoshka_en.md
new file mode 100644
index 00000000000000..7017f62819809f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_nli_matryoshka_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mpnet_base_nli_matryoshka MPNetForSequenceClassification from imvladikon
+author: John Snow Labs
+name: mpnet_base_nli_matryoshka
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_nli_matryoshka` is a English model originally trained by imvladikon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_en_5.5.0_3.0_1725386540357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_en_5.5.0_3.0_1725386540357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("mpnet_base_nli_matryoshka","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("mpnet_base_nli_matryoshka", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_nli_matryoshka|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|406.6 MB|
+
+## References
+
+https://huggingface.co/imvladikon/mpnet-base-nli-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_nli_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_nli_matryoshka_pipeline_en.md
new file mode 100644
index 00000000000000..30e0e6e32388cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_nli_matryoshka_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mpnet_base_nli_matryoshka_pipeline pipeline MPNetForSequenceClassification from imvladikon
+author: John Snow Labs
+name: mpnet_base_nli_matryoshka_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_nli_matryoshka_pipeline` is a English model originally trained by imvladikon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_pipeline_en_5.5.0_3.0_1725386563492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_pipeline_en_5.5.0_3.0_1725386563492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mpnet_base_nli_matryoshka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_base_nli_matryoshka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_nli_matryoshka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.6 MB|
+
+## References
+
+https://huggingface.co/imvladikon/mpnet-base-nli-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_snli_mnli_finetuned_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_snli_mnli_finetuned_mnli_en.md
new file mode 100644
index 00000000000000..4ec757050b69ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mpnet_base_snli_mnli_finetuned_mnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mpnet_base_snli_mnli_finetuned_mnli MPNetForSequenceClassification from NicolasLe
+author: John Snow Labs
+name: mpnet_base_snli_mnli_finetuned_mnli
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_snli_mnli_finetuned_mnli` is a English model originally trained by NicolasLe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_snli_mnli_finetuned_mnli_en_5.5.0_3.0_1725387072830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_snli_mnli_finetuned_mnli_en_5.5.0_3.0_1725387072830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("mpnet_base_snli_mnli_finetuned_mnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("mpnet_base_snli_mnli_finetuned_mnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_snli_mnli_finetuned_mnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/NicolasLe/mpnet-base-snli-mnli-finetuned-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mpnet_classification_10ksamples_en.md b/docs/_posts/ahmedlone127/2024-09-03-mpnet_classification_10ksamples_en.md
new file mode 100644
index 00000000000000..449cb492f5ddbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mpnet_classification_10ksamples_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mpnet_classification_10ksamples MPNetForSequenceClassification from jayavibhav
+author: John Snow Labs
+name: mpnet_classification_10ksamples
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_classification_10ksamples` is a English model originally trained by jayavibhav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_classification_10ksamples_en_5.5.0_3.0_1725386489115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_classification_10ksamples_en_5.5.0_3.0_1725386489115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("mpnet_classification_10ksamples","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("mpnet_classification_10ksamples", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_classification_10ksamples|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/jayavibhav/mpnet-classification-10ksamples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mpnet_classification_10ksamples_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mpnet_classification_10ksamples_pipeline_en.md
new file mode 100644
index 00000000000000..260c93e9ce5c00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mpnet_classification_10ksamples_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mpnet_classification_10ksamples_pipeline pipeline MPNetForSequenceClassification from jayavibhav
+author: John Snow Labs
+name: mpnet_classification_10ksamples_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_classification_10ksamples_pipeline` is a English model originally trained by jayavibhav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_classification_10ksamples_pipeline_en_5.5.0_3.0_1725386511690.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_classification_10ksamples_pipeline_en_5.5.0_3.0_1725386511690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mpnet_classification_10ksamples_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_classification_10ksamples_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_classification_10ksamples_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/jayavibhav/mpnet-classification-10ksamples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline_en.md
new file mode 100644
index 00000000000000..89f743e7cd4a23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline pipeline MPNetEmbeddings from luiz-and-robert-thesis
+author: John Snow Labs
+name: mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline` is a English model originally trained by luiz-and-robert-thesis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline_en_5.5.0_3.0_1725350774571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline_en_5.5.0_3.0_1725350774571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_frozen_newtriplets_v2_lr_2e_5_m_1_e_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/luiz-and-robert-thesis/mpnet-frozen-newtriplets-v2-lr-2e-5-m-1-e-3
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-multilingual_ili_detection_bernice_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-multilingual_ili_detection_bernice_pipeline_xx.md
new file mode 100644
index 00000000000000..a3fddcc8f094a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-multilingual_ili_detection_bernice_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_ili_detection_bernice_pipeline pipeline XlmRoBertaForSequenceClassification from nitimkc
+author: John Snow Labs
+name: multilingual_ili_detection_bernice_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_ili_detection_bernice_pipeline` is a Multilingual model originally trained by nitimkc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_ili_detection_bernice_pipeline_xx_5.5.0_3.0_1725396799817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_ili_detection_bernice_pipeline_xx_5.5.0_3.0_1725396799817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_ili_detection_bernice_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_ili_detection_bernice_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_ili_detection_bernice_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|799.5 MB|
+
+## References
+
+https://huggingface.co/nitimkc/multilingual-ili-detection-bernice
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-multilingual_ili_detection_bernice_xx.md b/docs/_posts/ahmedlone127/2024-09-03-multilingual_ili_detection_bernice_xx.md
new file mode 100644
index 00000000000000..71b2898b318718
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-multilingual_ili_detection_bernice_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_ili_detection_bernice XlmRoBertaForSequenceClassification from nitimkc
+author: John Snow Labs
+name: multilingual_ili_detection_bernice
+date: 2024-09-03
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_ili_detection_bernice` is a Multilingual model originally trained by nitimkc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_ili_detection_bernice_xx_5.5.0_3.0_1725396655341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_ili_detection_bernice_xx_5.5.0_3.0_1725396655341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("multilingual_ili_detection_bernice","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("multilingual_ili_detection_bernice", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_ili_detection_bernice|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|799.5 MB|
+
+## References
+
+https://huggingface.co/nitimkc/multilingual-ili-detection-bernice
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_en.md b/docs/_posts/ahmedlone127/2024-09-03-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_en.md
new file mode 100644
index 00000000000000..a6adc9a1f213c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English multilinguswahili_bge_small_english_v1_5_nli_matryoshka BGEEmbeddings from Mollel
+author: John Snow Labs
+name: multilinguswahili_bge_small_english_v1_5_nli_matryoshka
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilinguswahili_bge_small_english_v1_5_nli_matryoshka` is a English model originally trained by Mollel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilinguswahili_bge_small_english_v1_5_nli_matryoshka_en_5.5.0_3.0_1725356653219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilinguswahili_bge_small_english_v1_5_nli_matryoshka_en_5.5.0_3.0_1725356653219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("multilinguswahili_bge_small_english_v1_5_nli_matryoshka","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("multilinguswahili_bge_small_english_v1_5_nli_matryoshka","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilinguswahili_bge_small_english_v1_5_nli_matryoshka|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|122.8 MB|
+
+## References
+
+https://huggingface.co/Mollel/MultiLinguSwahili-bge-small-en-v1.5-nli-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_en.md
new file mode 100644
index 00000000000000..cd46db77f9c610
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline pipeline BGEEmbeddings from Mollel
+author: John Snow Labs
+name: multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline` is a English model originally trained by Mollel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_en_5.5.0_3.0_1725356660120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline_en_5.5.0_3.0_1725356660120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilinguswahili_bge_small_english_v1_5_nli_matryoshka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|122.9 MB|
+
+## References
+
+https://huggingface.co/Mollel/MultiLinguSwahili-bge-small-en-v1.5-nli-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ner_ner_random1_seed2_bernice_en.md b/docs/_posts/ahmedlone127/2024-09-03-ner_ner_random1_seed2_bernice_en.md
new file mode 100644
index 00000000000000..18e442e85f1e9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ner_ner_random1_seed2_bernice_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ner_random1_seed2_bernice XlmRoBertaForTokenClassification from tweettemposhift
+author: John Snow Labs
+name: ner_ner_random1_seed2_bernice
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ner_random1_seed2_bernice` is a English model originally trained by tweettemposhift.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ner_random1_seed2_bernice_en_5.5.0_3.0_1725373154019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ner_random1_seed2_bernice_en_5.5.0_3.0_1725373154019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("ner_ner_random1_seed2_bernice","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner_ner_random1_seed2_bernice", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ner_random1_seed2_bernice|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|802.7 MB|
+
+## References
+
+https://huggingface.co/tweettemposhift/ner-ner_random1_seed2-bernice
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ner_ner_random1_seed2_bernice_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-ner_ner_random1_seed2_bernice_pipeline_en.md
new file mode 100644
index 00000000000000..276484f87e15a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ner_ner_random1_seed2_bernice_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ner_random1_seed2_bernice_pipeline pipeline XlmRoBertaForTokenClassification from tweettemposhift
+author: John Snow Labs
+name: ner_ner_random1_seed2_bernice_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ner_random1_seed2_bernice_pipeline` is a English model originally trained by tweettemposhift.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ner_random1_seed2_bernice_pipeline_en_5.5.0_3.0_1725373308554.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ner_random1_seed2_bernice_pipeline_en_5.5.0_3.0_1725373308554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ner_random1_seed2_bernice_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ner_random1_seed2_bernice_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ner_random1_seed2_bernice_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|802.7 MB|
+
+## References
+
+https://huggingface.co/tweettemposhift/ner-ner_random1_seed2-bernice
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ner_xlm_roberta_base_ne.md b/docs/_posts/ahmedlone127/2024-09-03-ner_xlm_roberta_base_ne.md
new file mode 100644
index 00000000000000..b5f997fe916b4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ner_xlm_roberta_base_ne.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Nepali (macrolanguage) ner_xlm_roberta_base XlmRoBertaForTokenClassification from bishaldpande
+author: John Snow Labs
+name: ner_xlm_roberta_base
+date: 2024-09-03
+tags: [ne, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: ne
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_xlm_roberta_base` is a Nepali (macrolanguage) model originally trained by bishaldpande.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_xlm_roberta_base_ne_5.5.0_3.0_1725349592243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_xlm_roberta_base_ne_5.5.0_3.0_1725349592243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("ner_xlm_roberta_base","ne") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner_xlm_roberta_base", "ne")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ne|
+|Size:|839.4 MB|
+
+## References
+
+https://huggingface.co/bishaldpande/Ner-xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ner_xlm_roberta_base_pipeline_ne.md b/docs/_posts/ahmedlone127/2024-09-03-ner_xlm_roberta_base_pipeline_ne.md
new file mode 100644
index 00000000000000..a5f45e0fd09f51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ner_xlm_roberta_base_pipeline_ne.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Nepali (macrolanguage) ner_xlm_roberta_base_pipeline pipeline XlmRoBertaForTokenClassification from bishaldpande
+author: John Snow Labs
+name: ner_xlm_roberta_base_pipeline
+date: 2024-09-03
+tags: [ne, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ne
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_xlm_roberta_base_pipeline` is a Nepali (macrolanguage) model originally trained by bishaldpande.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_xlm_roberta_base_pipeline_ne_5.5.0_3.0_1725349659500.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_xlm_roberta_base_pipeline_ne_5.5.0_3.0_1725349659500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_xlm_roberta_base_pipeline", lang = "ne")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_xlm_roberta_base_pipeline", lang = "ne")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ne|
+|Size:|839.4 MB|
+
+## References
+
+https://huggingface.co/bishaldpande/Ner-xlm-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-nerel_bio_rubioroberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-nerel_bio_rubioroberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..995af71c51de5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-nerel_bio_rubioroberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nerel_bio_rubioroberta_base_pipeline pipeline RoBertaForTokenClassification from ekaterinatao
+author: John Snow Labs
+name: nerel_bio_rubioroberta_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nerel_bio_rubioroberta_base_pipeline` is a English model originally trained by ekaterinatao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nerel_bio_rubioroberta_base_pipeline_en_5.5.0_3.0_1725384046148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nerel_bio_rubioroberta_base_pipeline_en_5.5.0_3.0_1725384046148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nerel_bio_rubioroberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nerel_bio_rubioroberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nerel_bio_rubioroberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ekaterinatao/nerel-bio-RuBioRoBERTa-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-newsentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-03-newsentiment_analysis_en.md
new file mode 100644
index 00000000000000..837738bf7bf459
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-newsentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English newsentiment_analysis DistilBertForSequenceClassification from 1gen23dec
+author: John Snow Labs
+name: newsentiment_analysis
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newsentiment_analysis` is a English model originally trained by 1gen23dec.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newsentiment_analysis_en_5.5.0_3.0_1725329758312.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newsentiment_analysis_en_5.5.0_3.0_1725329758312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("newsentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("newsentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|newsentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/1gen23dec/newsentiment_analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-newspapers_classifier_colonial_en.md b/docs/_posts/ahmedlone127/2024-09-03-newspapers_classifier_colonial_en.md
new file mode 100644
index 00000000000000..03208bb3436478
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-newspapers_classifier_colonial_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English newspapers_classifier_colonial RoBertaForSequenceClassification from imperial-science
+author: John Snow Labs
+name: newspapers_classifier_colonial
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newspapers_classifier_colonial` is a English model originally trained by imperial-science.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newspapers_classifier_colonial_en_5.5.0_3.0_1725402425468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newspapers_classifier_colonial_en_5.5.0_3.0_1725402425468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("newspapers_classifier_colonial","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("newspapers_classifier_colonial", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|newspapers_classifier_colonial|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/imperial-science/newspapers_classifier_colonial
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-newspapers_classifier_colonial_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-newspapers_classifier_colonial_pipeline_en.md
new file mode 100644
index 00000000000000..0b7dc83ce923b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-newspapers_classifier_colonial_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English newspapers_classifier_colonial_pipeline pipeline RoBertaForSequenceClassification from imperial-science
+author: John Snow Labs
+name: newspapers_classifier_colonial_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newspapers_classifier_colonial_pipeline` is a English model originally trained by imperial-science.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newspapers_classifier_colonial_pipeline_en_5.5.0_3.0_1725402505655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newspapers_classifier_colonial_pipeline_en_5.5.0_3.0_1725402505655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("newspapers_classifier_colonial_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("newspapers_classifier_colonial_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|newspapers_classifier_colonial_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/imperial-science/newspapers_classifier_colonial
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-nlpcw_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-nlpcw_ner_pipeline_en.md
new file mode 100644
index 00000000000000..22a6be0df45fdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-nlpcw_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlpcw_ner_pipeline pipeline RoBertaForTokenClassification from cogniveon
+author: John Snow Labs
+name: nlpcw_ner_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlpcw_ner_pipeline` is a English model originally trained by cogniveon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlpcw_ner_pipeline_en_5.5.0_3.0_1725326068854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlpcw_ner_pipeline_en_5.5.0_3.0_1725326068854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlpcw_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlpcw_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlpcw_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/cogniveon/nlpcw-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-norwegian_bokml_whisper_medium_nbailab_no.md b/docs/_posts/ahmedlone127/2024-09-03-norwegian_bokml_whisper_medium_nbailab_no.md
new file mode 100644
index 00000000000000..7391de507d0477
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-norwegian_bokml_whisper_medium_nbailab_no.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Norwegian norwegian_bokml_whisper_medium_nbailab WhisperForCTC from NbAiLab
+author: John Snow Labs
+name: norwegian_bokml_whisper_medium_nbailab
+date: 2024-09-03
+tags: ["no", open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: "no"
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_whisper_medium_nbailab` is a Norwegian model originally trained by NbAiLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_medium_nbailab_no_5.5.0_3.0_1725366883085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_whisper_medium_nbailab_no_5.5.0_3.0_1725366883085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("norwegian_bokml_whisper_medium_nbailab","no") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("norwegian_bokml_whisper_medium_nbailab", "no")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|norwegian_bokml_whisper_medium_nbailab|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|no|
+|Size:|4.8 GB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-whisper-medium
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-novel_chinese_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-novel_chinese_english_en.md
new file mode 100644
index 00000000000000..41a4f2ef8eb583
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-novel_chinese_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English novel_chinese_english MarianTransformer from penpen
+author: John Snow Labs
+name: novel_chinese_english
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`novel_chinese_english` is a English model originally trained by penpen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/novel_chinese_english_en_5.5.0_3.0_1725345506730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/novel_chinese_english_en_5.5.0_3.0_1725345506730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("novel_chinese_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("novel_chinese_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|novel_chinese_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|535.7 MB|
+
+## References
+
+https://huggingface.co/penpen/novel-zh-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-novel_chinese_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-novel_chinese_english_pipeline_en.md
new file mode 100644
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+---
+layout: model
+title: English novel_chinese_english_pipeline pipeline MarianTransformer from penpen
+author: John Snow Labs
+name: novel_chinese_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`novel_chinese_english_pipeline` is a English model originally trained by penpen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/novel_chinese_english_pipeline_en_5.5.0_3.0_1725345538410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/novel_chinese_english_pipeline_en_5.5.0_3.0_1725345538410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("novel_chinese_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("novel_chinese_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|novel_chinese_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|536.2 MB|
+
+## References
+
+https://huggingface.co/penpen/novel-zh-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-nuner_v2_0_en.md b/docs/_posts/ahmedlone127/2024-09-03-nuner_v2_0_en.md
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+---
+layout: model
+title: English nuner_v2_0 RoBertaForTokenClassification from numind
+author: John Snow Labs
+name: nuner_v2_0
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuner_v2_0` is a English model originally trained by numind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nuner_v2_0_en_5.5.0_3.0_1725383003514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuner_v2_0_en_5.5.0_3.0_1725383003514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("nuner_v2_0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("nuner_v2_0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuner_v2_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|464.8 MB|
+
+## References
+
+https://huggingface.co/numind/NuNER-v2.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ofa_multi_768_en.md b/docs/_posts/ahmedlone127/2024-09-03-ofa_multi_768_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ofa_multi_768 XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: ofa_multi_768
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ofa_multi_768` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ofa_multi_768_en_5.5.0_3.0_1725353418832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ofa_multi_768_en_5.5.0_3.0_1725353418832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("ofa_multi_768","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("ofa_multi_768","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ofa_multi_768|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/ofa-multi-768
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-ofa_multi_768_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-ofa_multi_768_pipeline_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-ofa_multi_768_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ofa_multi_768_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: ofa_multi_768_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ofa_multi_768_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ofa_multi_768_pipeline_en_5.5.0_3.0_1725353493541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ofa_multi_768_pipeline_en_5.5.0_3.0_1725353493541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ofa_multi_768_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ofa_multi_768_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ofa_multi_768_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/ofa-multi-768
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-oorito_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-oorito_pipeline_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,70 @@
+---
+layout: model
+title: English oorito_pipeline pipeline MarianTransformer from LRJ1981
+author: John Snow Labs
+name: oorito_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`oorito_pipeline` is a English model originally trained by LRJ1981.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/oorito_pipeline_en_5.5.0_3.0_1725404193781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/oorito_pipeline_en_5.5.0_3.0_1725404193781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("oorito_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("oorito_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|oorito_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.2 MB|
+
+## References
+
+https://huggingface.co/LRJ1981/OORito
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_doc_v2_distill_en.md b/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_doc_v2_distill_en.md
new file mode 100644
index 00000000000000..ad7961bea99ad3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_doc_v2_distill_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opensearch_neural_sparse_encoding_doc_v2_distill DistilBertEmbeddings from opensearch-project
+author: John Snow Labs
+name: opensearch_neural_sparse_encoding_doc_v2_distill
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opensearch_neural_sparse_encoding_doc_v2_distill` is a English model originally trained by opensearch-project.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opensearch_neural_sparse_encoding_doc_v2_distill_en_5.5.0_3.0_1725384784097.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opensearch_neural_sparse_encoding_doc_v2_distill_en_5.5.0_3.0_1725384784097.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("opensearch_neural_sparse_encoding_doc_v2_distill","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("opensearch_neural_sparse_encoding_doc_v2_distill","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opensearch_neural_sparse_encoding_doc_v2_distill|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_v2_distill_en.md b/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_v2_distill_en.md
new file mode 100644
index 00000000000000..bc02b6afaf816f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_v2_distill_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opensearch_neural_sparse_encoding_v2_distill DistilBertEmbeddings from opensearch-project
+author: John Snow Labs
+name: opensearch_neural_sparse_encoding_v2_distill
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opensearch_neural_sparse_encoding_v2_distill` is a English model originally trained by opensearch-project.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opensearch_neural_sparse_encoding_v2_distill_en_5.5.0_3.0_1725384762374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opensearch_neural_sparse_encoding_v2_distill_en_5.5.0_3.0_1725384762374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("opensearch_neural_sparse_encoding_v2_distill","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("opensearch_neural_sparse_encoding_v2_distill","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opensearch_neural_sparse_encoding_v2_distill|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/opensearch-project/opensearch-neural-sparse-encoding-v2-distill
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-optimalspamdetect_en.md b/docs/_posts/ahmedlone127/2024-09-03-optimalspamdetect_en.md
new file mode 100644
index 00000000000000..121a15b017a9b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-optimalspamdetect_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English optimalspamdetect RoBertaForSequenceClassification from JustHuggingFaces
+author: John Snow Labs
+name: optimalspamdetect
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`optimalspamdetect` is a English model originally trained by JustHuggingFaces.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/optimalspamdetect_en_5.5.0_3.0_1725369621179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/optimalspamdetect_en_5.5.0_3.0_1725369621179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("optimalspamdetect","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("optimalspamdetect", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|optimalspamdetect|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|457.8 MB|
+
+## References
+
+https://huggingface.co/JustHuggingFaces/OptimalSpamDetect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-optimalspamdetect_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-optimalspamdetect_pipeline_en.md
new file mode 100644
index 00000000000000..10f3c879e8e5b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-optimalspamdetect_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English optimalspamdetect_pipeline pipeline RoBertaForSequenceClassification from JustHuggingFaces
+author: John Snow Labs
+name: optimalspamdetect_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`optimalspamdetect_pipeline` is a English model originally trained by JustHuggingFaces.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/optimalspamdetect_pipeline_en_5.5.0_3.0_1725369650667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/optimalspamdetect_pipeline_en_5.5.0_3.0_1725369650667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("optimalspamdetect_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("optimalspamdetect_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|optimalspamdetect_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|457.8 MB|
+
+## References
+
+https://huggingface.co/JustHuggingFaces/OptimalSpamDetect
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_en.md
new file mode 100644
index 00000000000000..6766315a40c319
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai MarianTransformer from MaryaAI
+author: John Snow Labs
+name: opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai` is a English model originally trained by MaryaAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_en_5.5.0_3.0_1725404452720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_en_5.5.0_3.0_1725404452720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|527.9 MB|
+
+## References
+
+https://huggingface.co/MaryaAI/opus-mt-ar-en-finetuned-ar-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline_en.md
new file mode 100644
index 00000000000000..236b0f6b09694c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline pipeline MarianTransformer from MaryaAI
+author: John Snow Labs
+name: opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline` is a English model originally trained by MaryaAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline_en_5.5.0_3.0_1725404481684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline_en_5.5.0_3.0_1725404481684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_maryaai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.5 MB|
+
+## References
+
+https://huggingface.co/MaryaAI/opus-mt-ar-en-finetuned-ar-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_en.md
new file mode 100644
index 00000000000000..6fd21f528d22a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16 MarianTransformer from shurafa16
+author: John Snow Labs
+name: opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16` is a English model originally trained by shurafa16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_en_5.5.0_3.0_1725345502532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_en_5.5.0_3.0_1725345502532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|527.9 MB|
+
+## References
+
+https://huggingface.co/shurafa16/opus-mt-ar-en-finetuned-ar-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline_en.md
new file mode 100644
index 00000000000000..6bf03cd9de643f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline pipeline MarianTransformer from shurafa16
+author: John Snow Labs
+name: opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline` is a English model originally trained by shurafa16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline_en_5.5.0_3.0_1725345530799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline_en_5.5.0_3.0_1725345530799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_arabic_english_finetuned_arabic_tonga_tonga_islands_english_shurafa16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.4 MB|
+
+## References
+
+https://huggingface.co/shurafa16/opus-mt-ar-en-finetuned-ar-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_en.md
new file mode 100644
index 00000000000000..814b88f70e8f48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic MarianTransformer from MaryaAI
+author: John Snow Labs
+name: opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic` is a English model originally trained by MaryaAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_en_5.5.0_3.0_1725347227970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_en_5.5.0_3.0_1725347227970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.3 MB|
+
+## References
+
+https://huggingface.co/MaryaAI/opus-mt-en-ar-finetuned-Math-13-10-en-to-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline_en.md
new file mode 100644
index 00000000000000..f68139896cc0e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline pipeline MarianTransformer from MaryaAI
+author: John Snow Labs
+name: opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline` is a English model originally trained by MaryaAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline_en_5.5.0_3.0_1725347257628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline_en_5.5.0_3.0_1725347257628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_arabic_finetuned_math_13_10_english_tonga_tonga_islands_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.8 MB|
+
+## References
+
+https://huggingface.co/MaryaAI/opus-mt-en-ar-finetuned-Math-13-10-en-to-ar
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_final_37_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_final_37_en.md
new file mode 100644
index 00000000000000..27e415fdb14609
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_final_37_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_bkm_final_37 MarianTransformer from kalese
+author: John Snow Labs
+name: opus_maltese_english_bkm_final_37
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bkm_final_37` is a English model originally trained by kalese.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_final_37_en_5.5.0_3.0_1725403861742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_final_37_en_5.5.0_3.0_1725403861742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_bkm_final_37","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_bkm_final_37","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_bkm_final_37|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.4 MB|
+
+## References
+
+https://huggingface.co/kalese/opus-mt-en-bkm-Final-37
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_final_37_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_final_37_pipeline_en.md
new file mode 100644
index 00000000000000..fe7a3d9b6bb1fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_bkm_final_37_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_bkm_final_37_pipeline pipeline MarianTransformer from kalese
+author: John Snow Labs
+name: opus_maltese_english_bkm_final_37_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bkm_final_37_pipeline` is a English model originally trained by kalese.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_final_37_pipeline_en_5.5.0_3.0_1725403889175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_final_37_pipeline_en_5.5.0_3.0_1725403889175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_bkm_final_37_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_bkm_final_37_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_bkm_final_37_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.9 MB|
+
+## References
+
+https://huggingface.co/kalese/opus-mt-en-bkm-Final-37
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_en.md
new file mode 100644
index 00000000000000..9cb373d4436b34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld MarianTransformer from wandemberg-eld
+author: John Snow Labs
+name: opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld` is a English model originally trained by wandemberg-eld.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_en_5.5.0_3.0_1725345662214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_en_5.5.0_3.0_1725345662214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|499.5 MB|
+
+## References
+
+https://huggingface.co/wandemberg-eld/opus-mt-en-de-finetuned-en-to-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline_en.md
new file mode 100644
index 00000000000000..976a9a3b876f07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline pipeline MarianTransformer from wandemberg-eld
+author: John Snow Labs
+name: opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline` is a English model originally trained by wandemberg-eld.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline_en_5.5.0_3.0_1725345687475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline_en_5.5.0_3.0_1725345687475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_wandemberg_eld_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|500.0 MB|
+
+## References
+
+https://huggingface.co/wandemberg-eld/opus-mt-en-de-finetuned-en-to-de
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_en.md
new file mode 100644
index 00000000000000..6f8a795e3c2ac9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai MarianTransformer from enimai
+author: John Snow Labs
+name: opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai` is a English model originally trained by enimai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_en_5.5.0_3.0_1725346076429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_en_5.5.0_3.0_1725346076429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|523.1 MB|
+
+## References
+
+https://huggingface.co/enimai/opus-mt-en-hi-finetuned-en-to-hi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline_en.md
new file mode 100644
index 00000000000000..29ba837b97d365
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline pipeline MarianTransformer from enimai
+author: John Snow Labs
+name: opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline` is a English model originally trained by enimai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline_en_5.5.0_3.0_1725346104826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline_en_5.5.0_3.0_1725346104826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_hindi_finetuned_english_tonga_tonga_islands_hindi_enimai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.6 MB|
+
+## References
+
+https://huggingface.co/enimai/opus-mt-en-hi-finetuned-en-to-hi
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai_en.md
new file mode 100644
index 00000000000000..d7d5e5b32e8a49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai MarianTransformer from enimai
+author: John Snow Labs
+name: opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai` is a English model originally trained by enimai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai_en_5.5.0_3.0_1725403955929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai_en_5.5.0_3.0_1725403955929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_enimai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|623.0 MB|
+
+## References
+
+https://huggingface.co/enimai/opus-mt-en-it-finetuned-en-to-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline_en.md
new file mode 100644
index 00000000000000..9905b84c50d92c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline pipeline MarianTransformer from VFiona
+author: John Snow Labs
+name: opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline` is a English model originally trained by VFiona.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline_en_5.5.0_3.0_1725347261693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline_en_5.5.0_3.0_1725347261693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_italian_finetuned_english_tonga_tonga_islands_italian_vfiona_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|623.5 MB|
+
+## References
+
+https://huggingface.co/VFiona/opus-mt-en-it-finetuned-en-to-it
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline_en.md
new file mode 100644
index 00000000000000..4a9e7a8b4593d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline pipeline MarianTransformer from Dwayne
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline` is a English model originally trained by Dwayne.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline_en_5.5.0_3.0_1725347253477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline_en_5.5.0_3.0_1725347253477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_dwayne_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.2 MB|
+
+## References
+
+https://huggingface.co/Dwayne/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_en.md
new file mode 100644
index 00000000000000..db67d52ffde47b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312 MarianTransformer from hongjing0312
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312` is a English model originally trained by hongjing0312.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_en_5.5.0_3.0_1725404513830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_en_5.5.0_3.0_1725404513830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/hongjing0312/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline_en.md
new file mode 100644
index 00000000000000..675067b4003719
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline pipeline MarianTransformer from hongjing0312
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline` is a English model originally trained by hongjing0312.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline_en_5.5.0_3.0_1725404541988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline_en_5.5.0_3.0_1725404541988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_hongjing0312_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.2 MB|
+
+## References
+
+https://huggingface.co/hongjing0312/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini_en.md
new file mode 100644
index 00000000000000..3c8a4c7ac913e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini MarianTransformer from Tejaswini
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini` is a English model originally trained by Tejaswini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini_en_5.5.0_3.0_1725404113156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini_en_5.5.0_3.0_1725404113156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_tejaswini|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/Tejaswini/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_en.md
new file mode 100644
index 00000000000000..b542259119892d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs MarianTransformer from ilevs
+author: John Snow Labs
+name: opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs` is a English model originally trained by ilevs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_en_5.5.0_3.0_1725404782398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_en_5.5.0_3.0_1725404782398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|525.2 MB|
+
+## References
+
+https://huggingface.co/ilevs/opus-mt-en-ru-finetuned-en-to-ru
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline_en.md
new file mode 100644
index 00000000000000..34490d36b57457
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline pipeline MarianTransformer from ilevs
+author: John Snow Labs
+name: opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline` is a English model originally trained by ilevs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline_en_5.5.0_3.0_1725404813924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline_en_5.5.0_3.0_1725404813924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_ilevs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|525.8 MB|
+
+## References
+
+https://huggingface.co/ilevs/opus-mt-en-ru-finetuned-en-to-ru
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_en.md
new file mode 100644
index 00000000000000..9c2e4d327689af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan MarianTransformer from mabidan
+author: John Snow Labs
+name: opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan` is a English model originally trained by mabidan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_en_5.5.0_3.0_1725404576177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_en_5.5.0_3.0_1725404576177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|525.6 MB|
+
+## References
+
+https://huggingface.co/mabidan/opus-mt-en-ru-finetuned-en-to-ru
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline_en.md
new file mode 100644
index 00000000000000..b63b05ddf8f011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline pipeline MarianTransformer from mabidan
+author: John Snow Labs
+name: opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline` is a English model originally trained by mabidan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline_en_5.5.0_3.0_1725404604882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline_en_5.5.0_3.0_1725404604882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_mabidan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|526.1 MB|
+
+## References
+
+https://huggingface.co/mabidan/opus-mt-en-ru-finetuned-en-to-ru
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_en.md
new file mode 100644
index 00000000000000..38a83cee446f8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu MarianTransformer from mekjr1
+author: John Snow Labs
+name: opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu` is a English model originally trained by mekjr1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_en_5.5.0_3.0_1725404284783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_en_5.5.0_3.0_1725404284783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.9 MB|
+
+## References
+
+https://huggingface.co/mekjr1/opus-mt-en-es-finetuned-es-to-ngu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline_en.md
new file mode 100644
index 00000000000000..f40288d6f538e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline pipeline MarianTransformer from mekjr1
+author: John Snow Labs
+name: opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline` is a English model originally trained by mekjr1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline_en_5.5.0_3.0_1725404316721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline_en_5.5.0_3.0_1725404316721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_ngu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.4 MB|
+
+## References
+
+https://huggingface.co/mekjr1/opus-mt-en-es-finetuned-es-to-ngu
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..32056b8470a156
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english MarianTransformer from KitoEver
+author: John Snow Labs
+name: opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english` is a English model originally trained by KitoEver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_en_5.5.0_3.0_1725403753165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_en_5.5.0_3.0_1725403753165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|511.9 MB|
+
+## References
+
+https://huggingface.co/KitoEver/opus-mt-lg-en-finetuned-rm-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline_en.md
new file mode 100644
index 00000000000000..a5b4bce59088f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from KitoEver
+author: John Snow Labs
+name: opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline` is a English model originally trained by KitoEver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725403787029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725403787029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_ganda_english_finetuned_romansh_tonga_tonga_islands_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|512.4 MB|
+
+## References
+
+https://huggingface.co/KitoEver/opus-mt-lg-en-finetuned-rm-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline_en.md
new file mode 100644
index 00000000000000..0a8b7098989351
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline pipeline MarianTransformer from Culmenus
+author: John Snow Labs
+name: opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline` is a English model originally trained by Culmenus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline_en_5.5.0_3.0_1725346387611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline_en_5.5.0_3.0_1725346387611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_german_icelandic_finetuned_german_tonga_tonga_islands_icelandic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.1 MB|
+
+## References
+
+https://huggingface.co/Culmenus/opus-mt-de-is-finetuned-de-to-is
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..2ecd6817963ef3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english MarianTransformer from PontifexMaximus
+author: John Snow Labs
+name: opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english` is a English model originally trained by PontifexMaximus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_en_5.5.0_3.0_1725346255869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_en_5.5.0_3.0_1725346255869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|523.1 MB|
+
+## References
+
+https://huggingface.co/PontifexMaximus/opus-mt-iir-en-finetuned-fa-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md
new file mode 100644
index 00000000000000..6ae437f29262ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from PontifexMaximus
+author: John Snow Labs
+name: opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline` is a English model originally trained by PontifexMaximus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725346282098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725346282098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.6 MB|
+
+## References
+
+https://huggingface.co/PontifexMaximus/opus-mt-iir-en-finetuned-fa-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en.md
new file mode 100644
index 00000000000000..2455d353241c8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish MarianTransformer from oguzhanmeteozturk
+author: John Snow Labs
+name: opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish` is a English model originally trained by oguzhanmeteozturk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en_5.5.0_3.0_1725346796600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en_5.5.0_3.0_1725346796600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/oguzhanmeteozturk/opus-mt-tc-big-en-tr-finetuned-en-to-tr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md
new file mode 100644
index 00000000000000..095d46df05b27e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline pipeline MarianTransformer from oguzhanmeteozturk
+author: John Snow Labs
+name: opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline` is a English model originally trained by oguzhanmeteozturk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en_5.5.0_3.0_1725346863579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en_5.5.0_3.0_1725346863579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_tc_big_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/oguzhanmeteozturk/opus-mt-tc-big-en-tr-finetuned-en-to-tr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline_en.md
new file mode 100644
index 00000000000000..4408b62024565a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline pipeline MarianTransformer from Theetawat
+author: John Snow Labs
+name: opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline` is a English model originally trained by Theetawat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline_en_5.5.0_3.0_1725345532690.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline_en_5.5.0_3.0_1725345532690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_theetawat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|524.7 MB|
+
+## References
+
+https://huggingface.co/Theetawat/opus-mt-th-en-finetuned-en-to-th
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..b677d6a0c8b9ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english MarianTransformer from PontifexMaximus
+author: John Snow Labs
+name: opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english` is a English model originally trained by PontifexMaximus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_en_5.5.0_3.0_1725347064314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english_en_5.5.0_3.0_1725347064314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_urdu_english_finetuned_persian_farsi_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|520.8 MB|
+
+## References
+
+https://huggingface.co/PontifexMaximus/opus-mt-ur-en-finetuned-fa-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en.md
new file mode 100644
index 00000000000000..12c60c164fa89f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish MarianTransformer from verach3n
+author: John Snow Labs
+name: opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish` is a English model originally trained by verach3n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en_5.5.0_3.0_1725404979750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_en_5.5.0_3.0_1725404979750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|509.8 MB|
+
+## References
+
+https://huggingface.co/verach3n/opus-tatoeba-en-tr-finetuned-en-to-tr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md
new file mode 100644
index 00000000000000..e5873078873fb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline pipeline MarianTransformer from verach3n
+author: John Snow Labs
+name: opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline` is a English model originally trained by verach3n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en_5.5.0_3.0_1725405010820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline_en_5.5.0_3.0_1725405010820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_tatoeba_english_turkish_finetuned_english_tonga_tonga_islands_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|510.4 MB|
+
+## References
+
+https://huggingface.co/verach3n/opus-tatoeba-en-tr-finetuned-en-to-tr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_finetuned_polifact_en.md b/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_finetuned_polifact_en.md
new file mode 100644
index 00000000000000..5ea9a5c06643b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_finetuned_polifact_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English paraphrase_mpnet_base_v2_finetuned_polifact MPNetEmbeddings from anuj55
+author: John Snow Labs
+name: paraphrase_mpnet_base_v2_finetuned_polifact
+date: 2024-09-03
+tags: [mpnet, en, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_finetuned_polifact` is a English model originally trained by anuj55.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_finetuned_polifact_en_5.5.0_3.0_1725386792545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_finetuned_polifact_en_5.5.0_3.0_1725386792545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_finetuned_polifact","en") \
+            .setInputCols(["documents"]) \
+            .setOutputCol("mpnet_embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("documents")
+    
+val embeddings = MPNetEmbeddings 
+    .pretrained("paraphrase_mpnet_base_v2_finetuned_polifact", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("mpnet_embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|paraphrase_mpnet_base_v2_finetuned_polifact|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/anuj55/paraphrase-mpnet-base-v2-finetuned-polifact
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_finetuned_polifact_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_finetuned_polifact_pipeline_en.md
new file mode 100644
index 00000000000000..fd6b3e9e92d891
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_finetuned_polifact_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English paraphrase_mpnet_base_v2_finetuned_polifact_pipeline pipeline MPNetForSequenceClassification from anuj55
+author: John Snow Labs
+name: paraphrase_mpnet_base_v2_finetuned_polifact_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_finetuned_polifact_pipeline` is a English model originally trained by anuj55.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_finetuned_polifact_pipeline_en_5.5.0_3.0_1725386815383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_finetuned_polifact_pipeline_en_5.5.0_3.0_1725386815383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("paraphrase_mpnet_base_v2_finetuned_polifact_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("paraphrase_mpnet_base_v2_finetuned_polifact_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|paraphrase_mpnet_base_v2_finetuned_polifact_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/anuj55/paraphrase-mpnet-base-v2-finetuned-polifact
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_mbti_full_en.md b/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_mbti_full_en.md
new file mode 100644
index 00000000000000..687bd7e81bb03b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_mbti_full_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English paraphrase_mpnet_base_v2_mbti_full MPNetForSequenceClassification from ClaudiaRichard
+author: John Snow Labs
+name: paraphrase_mpnet_base_v2_mbti_full
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_mbti_full` is a English model originally trained by ClaudiaRichard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_mbti_full_en_5.5.0_3.0_1725386952493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_mbti_full_en_5.5.0_3.0_1725386952493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("paraphrase_mpnet_base_v2_mbti_full","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("paraphrase_mpnet_base_v2_mbti_full", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|paraphrase_mpnet_base_v2_mbti_full|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/ClaudiaRichard/paraphrase-mpnet-base-v2_mbti_full
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_mbti_full_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_mbti_full_pipeline_en.md
new file mode 100644
index 00000000000000..c383e8de0e2956
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-paraphrase_mpnet_base_v2_mbti_full_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English paraphrase_mpnet_base_v2_mbti_full_pipeline pipeline MPNetForSequenceClassification from ClaudiaRichard
+author: John Snow Labs
+name: paraphrase_mpnet_base_v2_mbti_full_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_mbti_full_pipeline` is a English model originally trained by ClaudiaRichard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_mbti_full_pipeline_en_5.5.0_3.0_1725386974377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_mbti_full_pipeline_en_5.5.0_3.0_1725386974377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("paraphrase_mpnet_base_v2_mbti_full_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("paraphrase_mpnet_base_v2_mbti_full_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|paraphrase_mpnet_base_v2_mbti_full_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/ClaudiaRichard/paraphrase-mpnet-base-v2_mbti_full
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-pharo_keymessages_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-03-pharo_keymessages_classifier_en.md
new file mode 100644
index 00000000000000..16f6d8722c9a46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-pharo_keymessages_classifier_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English pharo_keymessages_classifier MPNetEmbeddings from AISE-TUDelft
+author: John Snow Labs
+name: pharo_keymessages_classifier
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pharo_keymessages_classifier` is a English model originally trained by AISE-TUDelft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pharo_keymessages_classifier_en_5.5.0_3.0_1725350122717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pharo_keymessages_classifier_en_5.5.0_3.0_1725350122717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("pharo_keymessages_classifier","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("pharo_keymessages_classifier","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pharo_keymessages_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/AISE-TUDelft/pharo-keymessages-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-pharo_keymessages_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-pharo_keymessages_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..cc0fb3fff00875
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-pharo_keymessages_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English pharo_keymessages_classifier_pipeline pipeline MPNetEmbeddings from AISE-TUDelft
+author: John Snow Labs
+name: pharo_keymessages_classifier_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pharo_keymessages_classifier_pipeline` is a English model originally trained by AISE-TUDelft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pharo_keymessages_classifier_pipeline_en_5.5.0_3.0_1725350145049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pharo_keymessages_classifier_pipeline_en_5.5.0_3.0_1725350145049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pharo_keymessages_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pharo_keymessages_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pharo_keymessages_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/AISE-TUDelft/pharo-keymessages-classifier
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-phishing_email_detection_final_2_en.md b/docs/_posts/ahmedlone127/2024-09-03-phishing_email_detection_final_2_en.md
new file mode 100644
index 00000000000000..afba63520b5261
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-phishing_email_detection_final_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English phishing_email_detection_final_2 DistilBertForSequenceClassification from kamikaze20
+author: John Snow Labs
+name: phishing_email_detection_final_2
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phishing_email_detection_final_2` is a English model originally trained by kamikaze20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phishing_email_detection_final_2_en_5.5.0_3.0_1725394376419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phishing_email_detection_final_2_en_5.5.0_3.0_1725394376419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("phishing_email_detection_final_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("phishing_email_detection_final_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|phishing_email_detection_final_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/kamikaze20/phishing-email-detection_final_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-phishing_email_detection_final_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-phishing_email_detection_final_2_pipeline_en.md
new file mode 100644
index 00000000000000..5d4a2c654f56d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-phishing_email_detection_final_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English phishing_email_detection_final_2_pipeline pipeline DistilBertForSequenceClassification from kamikaze20
+author: John Snow Labs
+name: phishing_email_detection_final_2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phishing_email_detection_final_2_pipeline` is a English model originally trained by kamikaze20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phishing_email_detection_final_2_pipeline_en_5.5.0_3.0_1725394389860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phishing_email_detection_final_2_pipeline_en_5.5.0_3.0_1725394389860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("phishing_email_detection_final_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("phishing_email_detection_final_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|phishing_email_detection_final_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/kamikaze20/phishing-email-detection_final_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-pii_detection_roberta_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-pii_detection_roberta_v2_pipeline_en.md
new file mode 100644
index 00000000000000..c13b1995d66c74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-pii_detection_roberta_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pii_detection_roberta_v2_pipeline pipeline RoBertaForTokenClassification from zmilczarek
+author: John Snow Labs
+name: pii_detection_roberta_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_detection_roberta_v2_pipeline` is a English model originally trained by zmilczarek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pii_detection_roberta_v2_pipeline_en_5.5.0_3.0_1725384018072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_detection_roberta_v2_pipeline_en_5.5.0_3.0_1725384018072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pii_detection_roberta_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pii_detection_roberta_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pii_detection_roberta_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|450.6 MB|
+
+## References
+
+https://huggingface.co/zmilczarek/pii-detection-roberta-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-platzi_distilroberta_base_mrpc_glue_jose_alcocer_en.md b/docs/_posts/ahmedlone127/2024-09-03-platzi_distilroberta_base_mrpc_glue_jose_alcocer_en.md
new file mode 100644
index 00000000000000..e431b3e1c39a56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-platzi_distilroberta_base_mrpc_glue_jose_alcocer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English platzi_distilroberta_base_mrpc_glue_jose_alcocer RoBertaForSequenceClassification from platzi
+author: John Snow Labs
+name: platzi_distilroberta_base_mrpc_glue_jose_alcocer
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`platzi_distilroberta_base_mrpc_glue_jose_alcocer` is a English model originally trained by platzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_jose_alcocer_en_5.5.0_3.0_1725403005453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_jose_alcocer_en_5.5.0_3.0_1725403005453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("platzi_distilroberta_base_mrpc_glue_jose_alcocer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("platzi_distilroberta_base_mrpc_glue_jose_alcocer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|platzi_distilroberta_base_mrpc_glue_jose_alcocer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/platzi/platzi-distilroberta-base-mrpc-glue-jose-alcocer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline_en.md
new file mode 100644
index 00000000000000..009fd536aec4ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline pipeline RoBertaForSequenceClassification from platzi
+author: John Snow Labs
+name: platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline` is a English model originally trained by platzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline_en_5.5.0_3.0_1725403021813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline_en_5.5.0_3.0_1725403021813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|platzi_distilroberta_base_mrpc_glue_jose_alcocer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/platzi/platzi-distilroberta-base-mrpc-glue-jose-alcocer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-policy_qa_burmese_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-policy_qa_burmese_finetuned_en.md
new file mode 100644
index 00000000000000..fca6712efd2831
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-policy_qa_burmese_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English policy_qa_burmese_finetuned BertForQuestionAnswering from poojithat96
+author: John Snow Labs
+name: policy_qa_burmese_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`policy_qa_burmese_finetuned` is a English model originally trained by poojithat96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/policy_qa_burmese_finetuned_en_5.5.0_3.0_1725351591281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/policy_qa_burmese_finetuned_en_5.5.0_3.0_1725351591281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("policy_qa_burmese_finetuned","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("policy_qa_burmese_finetuned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|policy_qa_burmese_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/poojithat96/policy_qa_my_finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-policy_qa_burmese_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-policy_qa_burmese_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..04a08ea1df4c2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-policy_qa_burmese_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English policy_qa_burmese_finetuned_pipeline pipeline BertForQuestionAnswering from poojithat96
+author: John Snow Labs
+name: policy_qa_burmese_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`policy_qa_burmese_finetuned_pipeline` is a English model originally trained by poojithat96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/policy_qa_burmese_finetuned_pipeline_en_5.5.0_3.0_1725351653206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/policy_qa_burmese_finetuned_pipeline_en_5.5.0_3.0_1725351653206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("policy_qa_burmese_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("policy_qa_burmese_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|policy_qa_burmese_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/poojithat96/policy_qa_my_finetuned
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-pretrained_xlm_portuguese_e8_select_en.md b/docs/_posts/ahmedlone127/2024-09-03-pretrained_xlm_portuguese_e8_select_en.md
new file mode 100644
index 00000000000000..700077826dc462
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-pretrained_xlm_portuguese_e8_select_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pretrained_xlm_portuguese_e8_select XlmRoBertaEmbeddings from harish
+author: John Snow Labs
+name: pretrained_xlm_portuguese_e8_select
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pretrained_xlm_portuguese_e8_select` is a English model originally trained by harish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrained_xlm_portuguese_e8_select_en_5.5.0_3.0_1725399641442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrained_xlm_portuguese_e8_select_en_5.5.0_3.0_1725399641442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("pretrained_xlm_portuguese_e8_select","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("pretrained_xlm_portuguese_e8_select","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pretrained_xlm_portuguese_e8_select|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/harish/preTrained-xlm-pt-e8-select
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-pretrained_xlm_portuguese_e8_select_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-pretrained_xlm_portuguese_e8_select_pipeline_en.md
new file mode 100644
index 00000000000000..4d97d77cc10088
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-pretrained_xlm_portuguese_e8_select_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pretrained_xlm_portuguese_e8_select_pipeline pipeline XlmRoBertaEmbeddings from harish
+author: John Snow Labs
+name: pretrained_xlm_portuguese_e8_select_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pretrained_xlm_portuguese_e8_select_pipeline` is a English model originally trained by harish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrained_xlm_portuguese_e8_select_pipeline_en_5.5.0_3.0_1725399695807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrained_xlm_portuguese_e8_select_pipeline_en_5.5.0_3.0_1725399695807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pretrained_xlm_portuguese_e8_select_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pretrained_xlm_portuguese_e8_select_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pretrained_xlm_portuguese_e8_select_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/harish/preTrained-xlm-pt-e8-select
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_17_en.md b/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_17_en.md
new file mode 100644
index 00000000000000..ca8384d7b01d43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_17_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_redaction_nov1_17 XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_redaction_nov1_17
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_redaction_nov1_17` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_redaction_nov1_17_en_5.5.0_3.0_1725380472665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_redaction_nov1_17_en_5.5.0_3.0_1725380472665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_redaction_nov1_17","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_redaction_nov1_17", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_redaction_nov1_17|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|797.5 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_REDACTION_NOV1_17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_17_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_17_pipeline_en.md
new file mode 100644
index 00000000000000..9b1a3242eecd94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_17_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_redaction_nov1_17_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_redaction_nov1_17_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_redaction_nov1_17_pipeline` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_redaction_nov1_17_pipeline_en_5.5.0_3.0_1725380596892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_redaction_nov1_17_pipeline_en_5.5.0_3.0_1725380596892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_redaction_nov1_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_redaction_nov1_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_redaction_nov1_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|797.5 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_REDACTION_NOV1_17
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_en.md b/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_en.md
new file mode 100644
index 00000000000000..5d409544311fea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-qa_redaction_nov1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_redaction_nov1 XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_redaction_nov1
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_redaction_nov1` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_redaction_nov1_en_5.5.0_3.0_1725380569684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_redaction_nov1_en_5.5.0_3.0_1725380569684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_redaction_nov1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_redaction_nov1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_redaction_nov1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|796.7 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_REDACTION_NOV1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-qa_synth_29_sept_with_finetune_1_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-qa_synth_29_sept_with_finetune_1_1_en.md
new file mode 100644
index 00000000000000..69cb79961fa532
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-qa_synth_29_sept_with_finetune_1_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_synth_29_sept_with_finetune_1_1 XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synth_29_sept_with_finetune_1_1
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_29_sept_with_finetune_1_1` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_29_sept_with_finetune_1_1_en_5.5.0_3.0_1725380665408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_29_sept_with_finetune_1_1_en_5.5.0_3.0_1725380665408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_29_sept_with_finetune_1_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_29_sept_with_finetune_1_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synth_29_sept_with_finetune_1_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|804.6 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTH_29_SEPT_WITH_FINETUNE_1.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-qa_synth_data_with_unanswerable_24_aug_en.md b/docs/_posts/ahmedlone127/2024-09-03-qa_synth_data_with_unanswerable_24_aug_en.md
new file mode 100644
index 00000000000000..ffce5b4d6ff8e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-qa_synth_data_with_unanswerable_24_aug_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_synth_data_with_unanswerable_24_aug XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synth_data_with_unanswerable_24_aug
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_data_with_unanswerable_24_aug` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_data_with_unanswerable_24_aug_en_5.5.0_3.0_1725380919207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_data_with_unanswerable_24_aug_en_5.5.0_3.0_1725380919207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_data_with_unanswerable_24_aug","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_data_with_unanswerable_24_aug", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synth_data_with_unanswerable_24_aug|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|803.3 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTH_DATA_WITH_UNANSWERABLE_24_AUG
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-qa_synth_data_with_unanswerable_24_aug_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-qa_synth_data_with_unanswerable_24_aug_pipeline_en.md
new file mode 100644
index 00000000000000..452f8f80254854
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-qa_synth_data_with_unanswerable_24_aug_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_synth_data_with_unanswerable_24_aug_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synth_data_with_unanswerable_24_aug_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_data_with_unanswerable_24_aug_pipeline` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_data_with_unanswerable_24_aug_pipeline_en_5.5.0_3.0_1725381040534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_data_with_unanswerable_24_aug_pipeline_en_5.5.0_3.0_1725381040534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_synth_data_with_unanswerable_24_aug_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_synth_data_with_unanswerable_24_aug_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synth_data_with_unanswerable_24_aug_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|803.3 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTH_DATA_WITH_UNANSWERABLE_24_AUG
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-readability_spanish_benchmark_bertin_spanish_paragraphs_3class_en.md b/docs/_posts/ahmedlone127/2024-09-03-readability_spanish_benchmark_bertin_spanish_paragraphs_3class_en.md
new file mode 100644
index 00000000000000..1ef82317174270
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-readability_spanish_benchmark_bertin_spanish_paragraphs_3class_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English readability_spanish_benchmark_bertin_spanish_paragraphs_3class RoBertaForSequenceClassification from lmvasque
+author: John Snow Labs
+name: readability_spanish_benchmark_bertin_spanish_paragraphs_3class
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`readability_spanish_benchmark_bertin_spanish_paragraphs_3class` is a English model originally trained by lmvasque.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/readability_spanish_benchmark_bertin_spanish_paragraphs_3class_en_5.5.0_3.0_1725369429652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/readability_spanish_benchmark_bertin_spanish_paragraphs_3class_en_5.5.0_3.0_1725369429652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("readability_spanish_benchmark_bertin_spanish_paragraphs_3class","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("readability_spanish_benchmark_bertin_spanish_paragraphs_3class", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|readability_spanish_benchmark_bertin_spanish_paragraphs_3class|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|464.5 MB|
+
+## References
+
+https://huggingface.co/lmvasque/readability-es-benchmark-bertin-es-paragraphs-3class
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline_en.md
new file mode 100644
index 00000000000000..4a295a01b81c3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline pipeline RoBertaForSequenceClassification from lmvasque
+author: John Snow Labs
+name: readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline` is a English model originally trained by lmvasque.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline_en_5.5.0_3.0_1725369456932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline_en_5.5.0_3.0_1725369456932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|readability_spanish_benchmark_bertin_spanish_paragraphs_3class_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.5 MB|
+
+## References
+
+https://huggingface.co/lmvasque/readability-es-benchmark-bertin-es-paragraphs-3class
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-resume_sentence_classification_en.md b/docs/_posts/ahmedlone127/2024-09-03-resume_sentence_classification_en.md
new file mode 100644
index 00000000000000..2d52f1b9996510
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-resume_sentence_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English resume_sentence_classification DistilBertForSequenceClassification from oussama120
+author: John Snow Labs
+name: resume_sentence_classification
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`resume_sentence_classification` is a English model originally trained by oussama120.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/resume_sentence_classification_en_5.5.0_3.0_1725330369175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/resume_sentence_classification_en_5.5.0_3.0_1725330369175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("resume_sentence_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("resume_sentence_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|resume_sentence_classification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/oussama120/Resume_Sentence_Classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-resume_sentence_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-resume_sentence_classification_pipeline_en.md
new file mode 100644
index 00000000000000..ad305e0954ba73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-resume_sentence_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English resume_sentence_classification_pipeline pipeline DistilBertForSequenceClassification from oussama120
+author: John Snow Labs
+name: resume_sentence_classification_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`resume_sentence_classification_pipeline` is a English model originally trained by oussama120.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/resume_sentence_classification_pipeline_en_5.5.0_3.0_1725330380804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/resume_sentence_classification_pipeline_en_5.5.0_3.0_1725330380804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("resume_sentence_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("resume_sentence_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|resume_sentence_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/oussama120/Resume_Sentence_Classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-robbert_2023_dutch_base_cross_encoder_en.md b/docs/_posts/ahmedlone127/2024-09-03-robbert_2023_dutch_base_cross_encoder_en.md
new file mode 100644
index 00000000000000..3b61230852959f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-robbert_2023_dutch_base_cross_encoder_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English robbert_2023_dutch_base_cross_encoder RoBertaForSequenceClassification from NetherlandsForensicInstitute
+author: John Snow Labs
+name: robbert_2023_dutch_base_cross_encoder
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_2023_dutch_base_cross_encoder` is a English model originally trained by NetherlandsForensicInstitute.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_base_cross_encoder_en_5.5.0_3.0_1725368614449.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_base_cross_encoder_en_5.5.0_3.0_1725368614449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("robbert_2023_dutch_base_cross_encoder","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("robbert_2023_dutch_base_cross_encoder", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_2023_dutch_base_cross_encoder|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/NetherlandsForensicInstitute/robbert-2023-dutch-base-cross-encoder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-robbert_2023_dutch_base_cross_encoder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-robbert_2023_dutch_base_cross_encoder_pipeline_en.md
new file mode 100644
index 00000000000000..0c7f5c20315049
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-robbert_2023_dutch_base_cross_encoder_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English robbert_2023_dutch_base_cross_encoder_pipeline pipeline RoBertaForSequenceClassification from NetherlandsForensicInstitute
+author: John Snow Labs
+name: robbert_2023_dutch_base_cross_encoder_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_2023_dutch_base_cross_encoder_pipeline` is a English model originally trained by NetherlandsForensicInstitute.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_base_cross_encoder_pipeline_en_5.5.0_3.0_1725368658566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_base_cross_encoder_pipeline_en_5.5.0_3.0_1725368658566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("robbert_2023_dutch_base_cross_encoder_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robbert_2023_dutch_base_cross_encoder_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_2023_dutch_base_cross_encoder_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/NetherlandsForensicInstitute/robbert-2023-dutch-base-cross-encoder
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_clinical_spanish_squad2_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_clinical_spanish_squad2_spanish_es.md
new file mode 100644
index 00000000000000..ce81ab66219a20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_clinical_spanish_squad2_spanish_es.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_clinical_spanish_squad2_spanish RoBertaForQuestionAnswering from somosnlp-hackathon-2022
+author: John Snow Labs
+name: roberta_base_biomedical_clinical_spanish_squad2_spanish
+date: 2024-09-03
+tags: [es, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_clinical_spanish_squad2_spanish` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_squad2_spanish_es_5.5.0_3.0_1725370700913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_squad2_spanish_es_5.5.0_3.0_1725370700913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_biomedical_clinical_spanish_squad2_spanish","es") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_biomedical_clinical_spanish_squad2_spanish", "es")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_clinical_spanish_squad2_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/somosnlp-hackathon-2022/roberta-base-biomedical-clinical-es-squad2-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..86033c53962a7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline pipeline RoBertaForQuestionAnswering from somosnlp-hackathon-2022
+author: John Snow Labs
+name: roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline
+date: 2024-09-03
+tags: [es, open_source, pipeline, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline_es_5.5.0_3.0_1725370728994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline_es_5.5.0_3.0_1725370728994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_clinical_spanish_squad2_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/somosnlp-hackathon-2022/roberta-base-biomedical-clinical-es-squad2-es
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_spanish_squad2_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_spanish_squad2_spanish_es.md
new file mode 100644
index 00000000000000..231e5fc93eeb60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_spanish_squad2_spanish_es.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_spanish_squad2_spanish RoBertaForQuestionAnswering from somosnlp-hackathon-2022
+author: John Snow Labs
+name: roberta_base_biomedical_spanish_squad2_spanish
+date: 2024-09-03
+tags: [es, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_spanish_squad2_spanish` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_squad2_spanish_es_5.5.0_3.0_1725371131270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_squad2_spanish_es_5.5.0_3.0_1725371131270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_biomedical_spanish_squad2_spanish","es") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_biomedical_spanish_squad2_spanish", "es")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_spanish_squad2_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|464.7 MB|
+
+## References
+
+https://huggingface.co/somosnlp-hackathon-2022/roberta-base-biomedical-es-squad2-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_spanish_squad2_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_spanish_squad2_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..d3c73a92567290
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_biomedical_spanish_squad2_spanish_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_spanish_squad2_spanish_pipeline pipeline RoBertaForQuestionAnswering from somosnlp-hackathon-2022
+author: John Snow Labs
+name: roberta_base_biomedical_spanish_squad2_spanish_pipeline
+date: 2024-09-03
+tags: [es, open_source, pipeline, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_spanish_squad2_spanish_pipeline` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_squad2_spanish_pipeline_es_5.5.0_3.0_1725371171564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_squad2_spanish_pipeline_es_5.5.0_3.0_1725371171564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_biomedical_spanish_squad2_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_biomedical_spanish_squad2_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_spanish_squad2_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|464.7 MB|
+
+## References
+
+https://huggingface.co/somosnlp-hackathon-2022/roberta-base-biomedical-es-squad2-es
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_chatgpt_qa_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_chatgpt_qa_en.md
new file mode 100644
index 00000000000000..4c52d0f01ed622
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_chatgpt_qa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_chatgpt_qa RoBertaForSequenceClassification from fahrialfiansyah
+author: John Snow Labs
+name: roberta_base_chatgpt_qa
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_chatgpt_qa` is a English model originally trained by fahrialfiansyah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_chatgpt_qa_en_5.5.0_3.0_1725368618413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_chatgpt_qa_en_5.5.0_3.0_1725368618413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_chatgpt_qa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_chatgpt_qa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_chatgpt_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|436.5 MB|
+
+## References
+
+https://huggingface.co/fahrialfiansyah/roberta-base_chatgpt_qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_chatgpt_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_chatgpt_qa_pipeline_en.md
new file mode 100644
index 00000000000000..5eff7a1b45c6bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_chatgpt_qa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_chatgpt_qa_pipeline pipeline RoBertaForSequenceClassification from fahrialfiansyah
+author: John Snow Labs
+name: roberta_base_chatgpt_qa_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_chatgpt_qa_pipeline` is a English model originally trained by fahrialfiansyah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_chatgpt_qa_pipeline_en_5.5.0_3.0_1725368662327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_chatgpt_qa_pipeline_en_5.5.0_3.0_1725368662327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_chatgpt_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_chatgpt_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_chatgpt_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|436.6 MB|
+
+## References
+
+https://huggingface.co/fahrialfiansyah/roberta-base_chatgpt_qa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_danish_da.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_danish_da.md
new file mode 100644
index 00000000000000..a3f402c00bc399
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_danish_da.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Danish roberta_base_danish RoBertaEmbeddings from DDSC
+author: John Snow Labs
+name: roberta_base_danish
+date: 2024-09-03
+tags: [da, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_danish` is a Danish model originally trained by DDSC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_danish_da_5.5.0_3.0_1725382073695.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_danish_da_5.5.0_3.0_1725382073695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_danish","da") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_danish","da") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_danish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|da|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/DDSC/roberta-base-danish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_english_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_english_mnli_en.md
new file mode 100644
index 00000000000000..67e92186e0d07b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_english_mnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_english_mnli RoBertaForSequenceClassification from hyunwoongko
+author: John Snow Labs
+name: roberta_base_english_mnli
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_english_mnli` is a English model originally trained by hyunwoongko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_english_mnli_en_5.5.0_3.0_1725403211013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_english_mnli_en_5.5.0_3.0_1725403211013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_english_mnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_english_mnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_english_mnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|299.8 MB|
+
+## References
+
+https://huggingface.co/hyunwoongko/roberta-base-en-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_english_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_english_mnli_pipeline_en.md
new file mode 100644
index 00000000000000..3c2f70ed05523a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_english_mnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_english_mnli_pipeline pipeline RoBertaForSequenceClassification from hyunwoongko
+author: John Snow Labs
+name: roberta_base_english_mnli_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_english_mnli_pipeline` is a English model originally trained by hyunwoongko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_english_mnli_pipeline_en_5.5.0_3.0_1725403302306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_english_mnli_pipeline_en_5.5.0_3.0_1725403302306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_english_mnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_english_mnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_english_mnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|299.8 MB|
+
+## References
+
+https://huggingface.co/hyunwoongko/roberta-base-en-mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_exp_8_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_exp_8_pipeline_xx.md
new file mode 100644
index 00000000000000..e7356de6ed9a65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_exp_8_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual roberta_base_exp_8_pipeline pipeline XlmRoBertaEmbeddings from pere
+author: John Snow Labs
+name: roberta_base_exp_8_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_exp_8_pipeline` is a Multilingual model originally trained by pere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_exp_8_pipeline_xx_5.5.0_3.0_1725353681218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_exp_8_pipeline_xx_5.5.0_3.0_1725353681218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_exp_8_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_exp_8_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_exp_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/pere/roberta-base-exp-8
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_exp_8_xx.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_exp_8_xx.md
new file mode 100644
index 00000000000000..48b500ae2cb63e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_exp_8_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual roberta_base_exp_8 XlmRoBertaEmbeddings from pere
+author: John Snow Labs
+name: roberta_base_exp_8
+date: 2024-09-03
+tags: [xx, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_exp_8` is a Multilingual model originally trained by pere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_exp_8_xx_5.5.0_3.0_1725353625998.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_exp_8_xx_5.5.0_3.0_1725353625998.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("roberta_base_exp_8","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("roberta_base_exp_8","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_exp_8|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/pere/roberta-base-exp-8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline_en.md
new file mode 100644
index 00000000000000..ffaca14c4bfd2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline pipeline XlmRoBertaForSequenceClassification from akshatmehta98
+author: John Snow Labs
+name: roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline` is a English model originally trained by akshatmehta98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline_en_5.5.0_3.0_1725327473396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline_en_5.5.0_3.0_1725327473396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_fine_tuned_flipkart_reviews_amharic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/akshatmehta98/roberta-base-fine-tuned-flipkart-reviews-am
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_finetuned_squad_ozgurkk_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_finetuned_squad_ozgurkk_en.md
new file mode 100644
index 00000000000000..83e71c567abae2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_finetuned_squad_ozgurkk_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_base_finetuned_squad_ozgurkk RoBertaForQuestionAnswering from ozgurkk
+author: John Snow Labs
+name: roberta_base_finetuned_squad_ozgurkk
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_squad_ozgurkk` is a English model originally trained by ozgurkk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_ozgurkk_en_5.5.0_3.0_1725371583781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_ozgurkk_en_5.5.0_3.0_1725371583781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_finetuned_squad_ozgurkk","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_finetuned_squad_ozgurkk", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_squad_ozgurkk|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|462.0 MB|
+
+## References
+
+https://huggingface.co/ozgurkk/roberta-base-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_finetuned_squad_ozgurkk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_finetuned_squad_ozgurkk_pipeline_en.md
new file mode 100644
index 00000000000000..d60e81292ccc25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_finetuned_squad_ozgurkk_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_finetuned_squad_ozgurkk_pipeline pipeline RoBertaForQuestionAnswering from ozgurkk
+author: John Snow Labs
+name: roberta_base_finetuned_squad_ozgurkk_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_squad_ozgurkk_pipeline` is a English model originally trained by ozgurkk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_ozgurkk_pipeline_en_5.5.0_3.0_1725371610282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squad_ozgurkk_pipeline_en_5.5.0_3.0_1725371610282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_finetuned_squad_ozgurkk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_finetuned_squad_ozgurkk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_squad_ozgurkk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.0 MB|
+
+## References
+
+https://huggingface.co/ozgurkk/roberta-base-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_go_emotions_thiagohersan_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_go_emotions_thiagohersan_en.md
new file mode 100644
index 00000000000000..c85441b236321f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_go_emotions_thiagohersan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_go_emotions_thiagohersan RoBertaForSequenceClassification from thiagohersan
+author: John Snow Labs
+name: roberta_base_go_emotions_thiagohersan
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_go_emotions_thiagohersan` is a English model originally trained by thiagohersan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_go_emotions_thiagohersan_en_5.5.0_3.0_1725368615440.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_go_emotions_thiagohersan_en_5.5.0_3.0_1725368615440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_go_emotions_thiagohersan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_go_emotions_thiagohersan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_go_emotions_thiagohersan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|455.5 MB|
+
+## References
+
+https://huggingface.co/thiagohersan/roberta-base-go_emotions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_go_emotions_thiagohersan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_go_emotions_thiagohersan_pipeline_en.md
new file mode 100644
index 00000000000000..e14252a04e85c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_go_emotions_thiagohersan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_go_emotions_thiagohersan_pipeline pipeline RoBertaForSequenceClassification from thiagohersan
+author: John Snow Labs
+name: roberta_base_go_emotions_thiagohersan_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_go_emotions_thiagohersan_pipeline` is a English model originally trained by thiagohersan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_go_emotions_thiagohersan_pipeline_en_5.5.0_3.0_1725368658522.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_go_emotions_thiagohersan_pipeline_en_5.5.0_3.0_1725368658522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_go_emotions_thiagohersan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_go_emotions_thiagohersan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_go_emotions_thiagohersan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|455.5 MB|
+
+## References
+
+https://huggingface.co/thiagohersan/roberta-base-go_emotions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mnli_two_stage_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mnli_two_stage_en.md
new file mode 100644
index 00000000000000..0b197fb3704456
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mnli_two_stage_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_mnli_two_stage RoBertaEmbeddings from ji-xin
+author: John Snow Labs
+name: roberta_base_mnli_two_stage
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_mnli_two_stage` is a English model originally trained by ji-xin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_mnli_two_stage_en_5.5.0_3.0_1725381925868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_mnli_two_stage_en_5.5.0_3.0_1725381925868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_mnli_two_stage","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_mnli_two_stage","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_mnli_two_stage|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|460.3 MB|
+
+## References
+
+https://huggingface.co/ji-xin/roberta_base-MNLI-two_stage
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mnli_two_stage_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mnli_two_stage_pipeline_en.md
new file mode 100644
index 00000000000000..353646bbfaffec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mnli_two_stage_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_mnli_two_stage_pipeline pipeline RoBertaEmbeddings from ji-xin
+author: John Snow Labs
+name: roberta_base_mnli_two_stage_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_mnli_two_stage_pipeline` is a English model originally trained by ji-xin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_mnli_two_stage_pipeline_en_5.5.0_3.0_1725381952953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_mnli_two_stage_pipeline_en_5.5.0_3.0_1725381952953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_mnli_two_stage_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_mnli_two_stage_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_mnli_two_stage_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|460.3 MB|
+
+## References
+
+https://huggingface.co/ji-xin/roberta_base-MNLI-two_stage
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mrpc_two_stage_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mrpc_two_stage_en.md
new file mode 100644
index 00000000000000..0b2100de5333ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mrpc_two_stage_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_mrpc_two_stage RoBertaForSequenceClassification from ji-xin
+author: John Snow Labs
+name: roberta_base_mrpc_two_stage
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_mrpc_two_stage` is a English model originally trained by ji-xin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_mrpc_two_stage_en_5.5.0_3.0_1725402914991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_mrpc_two_stage_en_5.5.0_3.0_1725402914991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_mrpc_two_stage","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_mrpc_two_stage", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_mrpc_two_stage|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|415.6 MB|
+
+## References
+
+https://huggingface.co/ji-xin/roberta_base-MRPC-two_stage
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mrpc_two_stage_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mrpc_two_stage_pipeline_en.md
new file mode 100644
index 00000000000000..90f9f9740cb043
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_mrpc_two_stage_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_mrpc_two_stage_pipeline pipeline RoBertaForSequenceClassification from ji-xin
+author: John Snow Labs
+name: roberta_base_mrpc_two_stage_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_mrpc_two_stage_pipeline` is a English model originally trained by ji-xin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_mrpc_two_stage_pipeline_en_5.5.0_3.0_1725402960663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_mrpc_two_stage_pipeline_en_5.5.0_3.0_1725402960663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_mrpc_two_stage_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_mrpc_two_stage_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_mrpc_two_stage_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|415.7 MB|
+
+## References
+
+https://huggingface.co/ji-xin/roberta_base-MRPC-two_stage
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_ner_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_ner_en.md
new file mode 100644
index 00000000000000..9ff02530fd46db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_ner XlmRoBertaForTokenClassification from Tirendaz
+author: John Snow Labs
+name: roberta_base_ner
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner` is a English model originally trained by Tirendaz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_en_5.5.0_3.0_1725373436816.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_en_5.5.0_3.0_1725373436816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("roberta_base_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("roberta_base_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|813.7 MB|
+
+## References
+
+https://huggingface.co/Tirendaz/roberta-base-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_ner_pipeline_en.md
new file mode 100644
index 00000000000000..43da0bc2da6f6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_ner_pipeline pipeline XlmRoBertaForTokenClassification from Tirendaz
+author: John Snow Labs
+name: roberta_base_ner_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_pipeline` is a English model originally trained by Tirendaz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_pipeline_en_5.5.0_3.0_1725373565265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_pipeline_en_5.5.0_3.0_1725373565265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|813.7 MB|
+
+## References
+
+https://huggingface.co/Tirendaz/roberta-base-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_russian_v0_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_russian_v0_pipeline_ru.md
new file mode 100644
index 00000000000000..d6e94597c1d336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_russian_v0_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian roberta_base_russian_v0_pipeline pipeline RoBertaEmbeddings from blinoff
+author: John Snow Labs
+name: roberta_base_russian_v0_pipeline
+date: 2024-09-03
+tags: [ru, open_source, pipeline, onnx]
+task: Embeddings
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_russian_v0_pipeline` is a Russian model originally trained by blinoff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_russian_v0_pipeline_ru_5.5.0_3.0_1725375125977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_russian_v0_pipeline_ru_5.5.0_3.0_1725375125977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_russian_v0_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_russian_v0_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_russian_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|465.1 MB|
+
+## References
+
+https://huggingface.co/blinoff/roberta-base-russian-v0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sentiment_cardiffnlp_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sentiment_cardiffnlp_en.md
new file mode 100644
index 00000000000000..be8ea698cc8af4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sentiment_cardiffnlp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_sentiment_cardiffnlp RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: roberta_base_sentiment_cardiffnlp
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_sentiment_cardiffnlp` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_sentiment_cardiffnlp_en_5.5.0_3.0_1725337364027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_sentiment_cardiffnlp_en_5.5.0_3.0_1725337364027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_sentiment_cardiffnlp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_sentiment_cardiffnlp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_sentiment_cardiffnlp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|455.1 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/roberta-base-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sst_2_16_13_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sst_2_16_13_en.md
new file mode 100644
index 00000000000000..01ffb8d7d07ef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sst_2_16_13_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_sst_2_16_13 RoBertaForSequenceClassification from simonycl
+author: John Snow Labs
+name: roberta_base_sst_2_16_13
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_sst_2_16_13` is a English model originally trained by simonycl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_sst_2_16_13_en_5.5.0_3.0_1725403287784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_sst_2_16_13_en_5.5.0_3.0_1725403287784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_sst_2_16_13","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_sst_2_16_13", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_sst_2_16_13|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|416.1 MB|
+
+## References
+
+https://huggingface.co/simonycl/roberta-base-sst-2-16-13
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_icebert_finetuned_grouped_is.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_icebert_finetuned_grouped_is.md
new file mode 100644
index 00000000000000..05b08f2cf2df61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_icebert_finetuned_grouped_is.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: Icelandic RoBertaForSequenceClassification Cased model (from ueb1)
+author: John Snow Labs
+name: roberta_classifier_icebert_finetuned_grouped
+date: 2024-09-03
+tags: [is, open_source, roberta, sequence_classification, classification, onnx]
+task: Text Classification
+language: is
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `IceBERT-finetuned-grouped` is a Icelandic model originally trained by `ueb1`.
+
+## Predicted Entities
+
+`Hulda Hólmkelsdóttir`, `Hjörvar Ólafsson`, `Birgir Þór Harðarson`, `Ásrún Brynja Ingvarsdóttir`, `Jóhanna María Einarsdóttir`, `Henry Birgir Gunnarsson`, `Kristinn Ingi Jónsson`, `Kristinn Ásgeir Gylfason`, `Birkir Blær Ingólfsson`, `Victor Pálsson`, `Magnús H. Jónasson`, `Kristín Ólafsdóttir`, `Jón Þór Kristjánsson`, `Jóhann Óli Eiðsson`, `Jón Júlíus Karlsson`, `Þorkell Gunnar Sigurbjörnsson`, `Garðar Örn Úlfarsson`, `Berghildur Erla Bernharðsdóttir`, `Oddur Ævar Gunnarsson`, `Kristján Róbert Kristjánsson`, `Kristinn Haukur Guðnason`, `Þórunn Elísabet Bogadóttir`, `Sylvía Rut Sigfúsdóttir`, `Hörður Snævar Jónsson`, `Finnur Thorlacius`, `Haukur Harðarson`, `Milla Ósk Magnúsdóttir`, `Kolbrún Bergþórsdóttir`, `Þórhildur Þorkelsdóttir`, `Kristín Sigurðardóttir`, `Magnús Hlynur Hreiðarsson`, `Tómas Þór Þórðarson`, `Einar Þór Sigurðsson`, `Erna Agnes Sigurgeirsdóttir`, `Alma Ómarsdóttir`, `Tryggvi Páll Tryggvason`, `Erla Dóra Magnúsdóttir`, `Birgir Olgeirsson`, `Máni Snær Þorláksson`, `Gunnar Hrafn Jónsson`, `Ingvi Þór Sæmundsson`, `Sylvía Hall`, `Róbert Jóhannsson`, `Arnar Geir Halldórsson`, `Þorsteinn Friðrik Halldórsson`, `Arnhildur Hálfdánardóttir`, `Eiríkur Stefán Ásgeirsson`, `Stígur Helgason`, `Valgerður Árnadóttir`, `Bjarni Pétur Jónsson`, `Óskar Ófeigur Jónsson`, `Andri Eysteinsson`, `Ingunn Lára Kristjánsdóttir`, `Einar Örn Jónsson`, `Ágúst Borgþór Sverrisson`, `Sigríður Dögg Auðunsdóttir`, `Jakob Bjarnar`, `Kolbeinn Tumi Daðason`, `Innanríkisráðuneyti`, `Bára Huld Beck`, `Ísak Hallmundarson`, `Valur Páll Eiríksson`, `Sunna Valgerðardóttir`, `Ingvar Þór Björnsson`, `Ævar Örn Jósepsson`, `Samúel Karl Ólason`, `Jón Hákon Halldórsson`, `Anna Lilja Þórisdóttir`, `Þórgnýr Einar Albertsson`, `Steindór Grétar Jónsson`, `Fjármálaráðuneyti`, `Haukur Holm`, `Forsætisráðuneyti`, `Hörður Ægisson`, `Sveinn Arnarsson`, `Margrét Helga Erlingsdóttir`, `Þorvaldur Friðriksson`, `Kristjana Arnarsdóttir`, `Atli Ísleifsson`, `Stefán Árni Pálsson`, `Sighvatur Arnmundsson`, `Anton Ingi Leifsson`, `Þórður Snær Júlíusson`, `Kristján Sigurjónsson`, `Rúnar Snær Reynisson`, `Karl Lúðvíksson`, `Birta Björnsdóttir`, `Jóhann K. Jóhannsson`, `Ari Brynjólfsson`, `Ólöf Ragnarsdóttir`, `Kristlín Dís Ingilínardóttir`, `Elín Margrét Böðvarsdóttir`, `Hólmfríður Dagný Friðjónsdóttir`, `Urður Örlygsdóttir`, `Jón Þór Stefánsson`, `Eiður Þór Árnason`, `Anna Kristín Jónsdóttir`, `Stefán Þór Hjartarson`, `Hallgrímur Indriðason`, `Ástrós Ýr Eggertsdóttir`, `Markús Þ. Þórhallsson`, `Freyr Gígja Gunnarsson`, `Kristján Már Unnarsson`, `Lovísa Arnardóttir`, `Rögnvaldur Már Helgason`, `Brynjólfur Þór Guðmundsson`, `Bergljót Baldursdóttir`, `Halla Ólafsdóttir`, `Úlla Árdal`, `Sólveig Klara Ragnarsdóttir`, `Gunnar Birgisson`, `Fanndís Birna Logadóttir`, `Sæunn Gísladóttir`, `Stefán Ó. Jónsson`, `Ásgeir Tómasson`, `Sunna Karen Sigurþórsdóttir`, `Runólfur Trausti Þórhallsson`, `Hallgerður Kolbrún E. Jónsdóttir`, `Katrín Ásmundsdóttir`, `Nadine Guðrún Yaghi`, `Andri Yrkill Valsson`, `Kjartan Kjartansson`, `Sindri Sverrisson`, `Jóhanna Vigdís Hjaltadóttir`, `Kristján Kristjánsson`, `Aðalheiður Ámundadóttir`, `Fókus`, `Jóhann Bjarni Kolbeinsson`, `Gunnþóra Gunnarsdóttir`, `Ágúst Ólafsson`, `Ása Ninna Pétursdóttir`, `Kristinn Páll Teitsson`, `Óttar Kolbeinsson Proppé`, `Kári Gylfason`, `Sunna Kristín Hilmarsdóttir`, `Þórdís Arnljótsdóttir`, `Þorvarður Pálsson`, `Guðrún Ósk Guðjónsdóttir`, `Heimir Már Pétursson`, `Vésteinn Örn Pétursson`, `Nína Hjördís Þorkelsdóttir`, `Dagný Hulda Erlendsdóttir`, `Magnús Halldórsson`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_icebert_finetuned_grouped_is_5.5.0_3.0_1725369859448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_icebert_finetuned_grouped_is_5.5.0_3.0_1725369859448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_icebert_finetuned_grouped","is") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_icebert_finetuned_grouped","is")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_classifier_icebert_finetuned_grouped|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|is|
+|Size:|463.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/ueb1/IceBERT-finetuned-grouped
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_icebert_finetuned_grouped_pipeline_is.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_icebert_finetuned_grouped_pipeline_is.md
new file mode 100644
index 00000000000000..8694dd5f6f765a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_icebert_finetuned_grouped_pipeline_is.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Icelandic roberta_classifier_icebert_finetuned_grouped_pipeline pipeline RoBertaForSequenceClassification from ueb1
+author: John Snow Labs
+name: roberta_classifier_icebert_finetuned_grouped_pipeline
+date: 2024-09-03
+tags: [is, open_source, pipeline, onnx]
+task: Text Classification
+language: is
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_icebert_finetuned_grouped_pipeline` is a Icelandic model originally trained by ueb1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_icebert_finetuned_grouped_pipeline_is_5.5.0_3.0_1725369892844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_icebert_finetuned_grouped_pipeline_is_5.5.0_3.0_1725369892844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_classifier_icebert_finetuned_grouped_pipeline", lang = "is")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_classifier_icebert_finetuned_grouped_pipeline", lang = "is")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_classifier_icebert_finetuned_grouped_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|is|
+|Size:|463.4 MB|
+
+## References
+
+https://huggingface.co/ueb1/IceBERT-finetuned-grouped
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_large_wanli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_large_wanli_pipeline_en.md
new file mode 100644
index 00000000000000..83f4cc5959fd22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_classifier_large_wanli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_classifier_large_wanli_pipeline pipeline RoBertaForSequenceClassification from alisawuffles
+author: John Snow Labs
+name: roberta_classifier_large_wanli_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_large_wanli_pipeline` is a English model originally trained by alisawuffles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_large_wanli_pipeline_en_5.5.0_3.0_1725337288863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_large_wanli_pipeline_en_5.5.0_3.0_1725337288863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_classifier_large_wanli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_classifier_large_wanli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_classifier_large_wanli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/alisawuffles/roberta-large-wanli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_cwe_classifier_kelemia_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_cwe_classifier_kelemia_en.md
new file mode 100644
index 00000000000000..618937552ccbcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_cwe_classifier_kelemia_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_cwe_classifier_kelemia RoBertaForSequenceClassification from Dunateo
+author: John Snow Labs
+name: roberta_cwe_classifier_kelemia
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_cwe_classifier_kelemia` is a English model originally trained by Dunateo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_cwe_classifier_kelemia_en_5.5.0_3.0_1725402564600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_cwe_classifier_kelemia_en_5.5.0_3.0_1725402564600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_cwe_classifier_kelemia","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_cwe_classifier_kelemia", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_cwe_classifier_kelemia|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|436.4 MB|
+
+## References
+
+https://huggingface.co/Dunateo/roberta-cwe-classifier-kelemia
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_amharic_roberta_am.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_amharic_roberta_am.md
new file mode 100644
index 00000000000000..938659c3b3d77d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_amharic_roberta_am.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Amharic roberta_embeddings_amharic_roberta RoBertaEmbeddings from uhhlt
+author: John Snow Labs
+name: roberta_embeddings_amharic_roberta
+date: 2024-09-03
+tags: [am, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: am
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_embeddings_amharic_roberta` is a Amharic model originally trained by uhhlt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_amharic_roberta_am_5.5.0_3.0_1725375181293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_amharic_roberta_am_5.5.0_3.0_1725375181293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_amharic_roberta","am") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_amharic_roberta","am") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_embeddings_amharic_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|am|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/uhhlt/am-roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_indonesian_roberta_large_id.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_indonesian_roberta_large_id.md
new file mode 100644
index 00000000000000..d2e3fa37e91924
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_indonesian_roberta_large_id.md
@@ -0,0 +1,109 @@
+---
+layout: model
+title: Indonesian RoBERTa Embeddings (Large)
+author: John Snow Labs
+name: roberta_embeddings_indonesian_roberta_large
+date: 2024-09-03
+tags: [roberta, embeddings, id, open_source, onnx]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. `indonesian-roberta-large` is a Indonesian model orginally trained by `flax-community`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_indonesian_roberta_large_id_5.5.0_3.0_1725374968190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_indonesian_roberta_large_id_5.5.0_3.0_1725374968190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+.setInputCol("text") \
+.setOutputCol("document")
+
+tokenizer = Tokenizer() \
+.setInputCols("document") \
+.setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_indonesian_roberta_large","id") \
+.setInputCols(["document", "token"]) \
+.setOutputCol("embeddings")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["Saya suka percikan NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+.setInputCol("text") 
+.setOutputCol("document")
+
+val tokenizer = new Tokenizer() 
+.setInputCols(Array("document"))
+.setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_indonesian_roberta_large","id") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("Saya suka percikan NLP").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("id.embed.indonesian_roberta_large").predict("""Saya suka percikan NLP""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_embeddings_indonesian_roberta_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|id|
+|Size:|627.1 MB|
+
+## References
+
+References
+
+- https://huggingface.co/flax-community/indonesian-roberta-large
+- https://arxiv.org/abs/1907.11692
+- https://hf.co/w11wo
+- https://hf.co/stevenlimcorn
+- https://hf.co/munggok
+- https://hf.co/chewkokwah
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_indonesian_roberta_large_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_indonesian_roberta_large_pipeline_id.md
new file mode 100644
index 00000000000000..7d7e6f530b1531
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_indonesian_roberta_large_pipeline_id.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Indonesian roberta_embeddings_indonesian_roberta_large_pipeline pipeline RoBertaEmbeddings from flax-community
+author: John Snow Labs
+name: roberta_embeddings_indonesian_roberta_large_pipeline
+date: 2024-09-03
+tags: [id, open_source, pipeline, onnx]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_embeddings_indonesian_roberta_large_pipeline` is a Indonesian model originally trained by flax-community.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_indonesian_roberta_large_pipeline_id_5.5.0_3.0_1725375194313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_indonesian_roberta_large_pipeline_id_5.5.0_3.0_1725375194313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_embeddings_indonesian_roberta_large_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_embeddings_indonesian_roberta_large_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_embeddings_indonesian_roberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|627.1 MB|
+
+## References
+
+https://huggingface.co/flax-community/indonesian-roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_muppet_roberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_muppet_roberta_large_en.md
new file mode 100644
index 00000000000000..e3271da5efba14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_muppet_roberta_large_en.md
@@ -0,0 +1,105 @@
+---
+layout: model
+title: English RoBERTa Embeddings (Large, Wikipedia and Bookcorpus datasets)
+author: John Snow Labs
+name: roberta_embeddings_muppet_roberta_large
+date: 2024-09-03
+tags: [roberta, embeddings, en, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. `muppet-roberta-large` is a English model orginally trained by `facebook`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_muppet_roberta_large_en_5.5.0_3.0_1725375819415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_muppet_roberta_large_en_5.5.0_3.0_1725375819415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+.setInputCol("text") \
+.setOutputCol("document")
+
+tokenizer = Tokenizer() \
+.setInputCols("document") \
+.setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_muppet_roberta_large","en") \
+.setInputCols(["document", "token"]) \
+.setOutputCol("embeddings")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+.setInputCol("text") 
+.setOutputCol("document")
+
+val tokenizer = new Tokenizer() 
+.setInputCols(Array("document"))
+.setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_muppet_roberta_large","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("I love Spark NLP").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.embed.muppet_roberta_large").predict("""I love Spark NLP""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_embeddings_muppet_roberta_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|843.9 MB|
+
+## References
+
+References
+
+- https://huggingface.co/facebook/muppet-roberta-large
+- https://arxiv.org/abs/2101.11038
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_muppet_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_muppet_roberta_large_pipeline_en.md
new file mode 100644
index 00000000000000..03c46d308e4c81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_embeddings_muppet_roberta_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_embeddings_muppet_roberta_large_pipeline pipeline RoBertaEmbeddings from facebook
+author: John Snow Labs
+name: roberta_embeddings_muppet_roberta_large_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_embeddings_muppet_roberta_large_pipeline` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_muppet_roberta_large_pipeline_en_5.5.0_3.0_1725376069436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_muppet_roberta_large_pipeline_en_5.5.0_3.0_1725376069436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_embeddings_muppet_roberta_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_embeddings_muppet_roberta_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_embeddings_muppet_roberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.9 MB|
+
+## References
+
+https://huggingface.co/facebook/muppet-roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_med_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_med_en.md
new file mode 100644
index 00000000000000..e3257654900ade
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_med_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_med RoBertaForQuestionAnswering from VenkateshSoni
+author: John Snow Labs
+name: roberta_finetuned_med
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_med` is a English model originally trained by VenkateshSoni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_med_en_5.5.0_3.0_1725370783625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_med_en_5.5.0_3.0_1725370783625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_med","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_med", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_med|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+https://huggingface.co/VenkateshSoni/roberta-finetuned-Med
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_med_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_med_pipeline_en.md
new file mode 100644
index 00000000000000..13cb8593b9f1b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_med_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_med_pipeline pipeline RoBertaForQuestionAnswering from VenkateshSoni
+author: John Snow Labs
+name: roberta_finetuned_med_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_med_pipeline` is a English model originally trained by VenkateshSoni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_med_pipeline_en_5.5.0_3.0_1725370810542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_med_pipeline_en_5.5.0_3.0_1725370810542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_med_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_med_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_med_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+https://huggingface.co/VenkateshSoni/roberta-finetuned-Med
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_topic_3_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_topic_3_en.md
new file mode 100644
index 00000000000000..5b5e33d2e10310
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_topic_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_finetuned_topic_3 RoBertaForSequenceClassification from MrFitzmaurice
+author: John Snow Labs
+name: roberta_finetuned_topic_3
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_topic_3` is a English model originally trained by MrFitzmaurice.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_topic_3_en_5.5.0_3.0_1725402360456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_topic_3_en_5.5.0_3.0_1725402360456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_finetuned_topic_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_finetuned_topic_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_topic_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|458.4 MB|
+
+## References
+
+https://huggingface.co/MrFitzmaurice/roberta-finetuned-topic-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_topic_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_topic_3_pipeline_en.md
new file mode 100644
index 00000000000000..b96cb0d5df231e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuned_topic_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_finetuned_topic_3_pipeline pipeline RoBertaForSequenceClassification from MrFitzmaurice
+author: John Snow Labs
+name: roberta_finetuned_topic_3_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_topic_3_pipeline` is a English model originally trained by MrFitzmaurice.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_topic_3_pipeline_en_5.5.0_3.0_1725402385410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_topic_3_pipeline_en_5.5.0_3.0_1725402385410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_topic_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_topic_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_topic_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|458.5 MB|
+
+## References
+
+https://huggingface.co/MrFitzmaurice/roberta-finetuned-topic-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuning_ner_pii_bahasa_indonesia_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuning_ner_pii_bahasa_indonesia_en.md
new file mode 100644
index 00000000000000..ccdfae578f039b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuning_ner_pii_bahasa_indonesia_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_finetuning_ner_pii_bahasa_indonesia RoBertaForTokenClassification from cindyangelira
+author: John Snow Labs
+name: roberta_finetuning_ner_pii_bahasa_indonesia
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuning_ner_pii_bahasa_indonesia` is a English model originally trained by cindyangelira.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuning_ner_pii_bahasa_indonesia_en_5.5.0_3.0_1725383735013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuning_ner_pii_bahasa_indonesia_en_5.5.0_3.0_1725383735013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_finetuning_ner_pii_bahasa_indonesia","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_finetuning_ner_pii_bahasa_indonesia", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuning_ner_pii_bahasa_indonesia|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|470.8 MB|
+
+## References
+
+https://huggingface.co/cindyangelira/roberta-finetuning-ner-pii-bahasa-indonesia
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuning_ner_pii_bahasa_indonesia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuning_ner_pii_bahasa_indonesia_pipeline_en.md
new file mode 100644
index 00000000000000..1f26d6c7ad3eb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_finetuning_ner_pii_bahasa_indonesia_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_finetuning_ner_pii_bahasa_indonesia_pipeline pipeline RoBertaForTokenClassification from cindyangelira
+author: John Snow Labs
+name: roberta_finetuning_ner_pii_bahasa_indonesia_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuning_ner_pii_bahasa_indonesia_pipeline` is a English model originally trained by cindyangelira.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuning_ner_pii_bahasa_indonesia_pipeline_en_5.5.0_3.0_1725383759784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuning_ner_pii_bahasa_indonesia_pipeline_en_5.5.0_3.0_1725383759784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuning_ner_pii_bahasa_indonesia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuning_ner_pii_bahasa_indonesia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuning_ner_pii_bahasa_indonesia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.8 MB|
+
+## References
+
+https://huggingface.co/cindyangelira/roberta-finetuning-ner-pii-bahasa-indonesia
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_capitel_ner_plantl_gob_es_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_capitel_ner_plantl_gob_es_pipeline_es.md
new file mode 100644
index 00000000000000..c41ad0013d4319
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_bne_capitel_ner_plantl_gob_es_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish roberta_large_bne_capitel_ner_plantl_gob_es_pipeline pipeline RoBertaForTokenClassification from PlanTL-GOB-ES
+author: John Snow Labs
+name: roberta_large_bne_capitel_ner_plantl_gob_es_pipeline
+date: 2024-09-03
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_bne_capitel_ner_plantl_gob_es_pipeline` is a Castilian, Spanish model originally trained by PlanTL-GOB-ES.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_bne_capitel_ner_plantl_gob_es_pipeline_es_5.5.0_3.0_1725383303379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_bne_capitel_ner_plantl_gob_es_pipeline_es_5.5.0_3.0_1725383303379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_bne_capitel_ner_plantl_gob_es_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_bne_capitel_ner_plantl_gob_es_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_bne_capitel_ner_plantl_gob_es_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/PlanTL-GOB-ES/roberta-large-bne-capitel-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_dutch_oscar23_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_dutch_oscar23_en.md
new file mode 100644
index 00000000000000..c490e5034a916c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_dutch_oscar23_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_dutch_oscar23 RoBertaEmbeddings from FremyCompany
+author: John Snow Labs
+name: roberta_large_dutch_oscar23
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_dutch_oscar23` is a English model originally trained by FremyCompany.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_dutch_oscar23_en_5.5.0_3.0_1725382369824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_dutch_oscar23_en_5.5.0_3.0_1725382369824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_dutch_oscar23","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_dutch_oscar23","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_dutch_oscar23|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/FremyCompany/roberta-large-nl-oscar23
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_dutch_oscar23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_dutch_oscar23_pipeline_en.md
new file mode 100644
index 00000000000000..d4f0cfe251bd15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_dutch_oscar23_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_dutch_oscar23_pipeline pipeline RoBertaEmbeddings from FremyCompany
+author: John Snow Labs
+name: roberta_large_dutch_oscar23_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_dutch_oscar23_pipeline` is a English model originally trained by FremyCompany.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_dutch_oscar23_pipeline_en_5.5.0_3.0_1725382439910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_dutch_oscar23_pipeline_en_5.5.0_3.0_1725382439910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_dutch_oscar23_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_dutch_oscar23_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_dutch_oscar23_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/FremyCompany/roberta-large-nl-oscar23
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_financial_news_sentiment_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_financial_news_sentiment_english_pipeline_en.md
new file mode 100644
index 00000000000000..19a2c1ced232a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_financial_news_sentiment_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_financial_news_sentiment_english_pipeline pipeline RoBertaForSequenceClassification from Jean-Baptiste
+author: John Snow Labs
+name: roberta_large_financial_news_sentiment_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_financial_news_sentiment_english_pipeline` is a English model originally trained by Jean-Baptiste.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_financial_news_sentiment_english_pipeline_en_5.5.0_3.0_1725369931985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_financial_news_sentiment_english_pipeline_en_5.5.0_3.0_1725369931985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_financial_news_sentiment_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_financial_news_sentiment_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_financial_news_sentiment_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Jean-Baptiste/roberta-large-financial-news-sentiment-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_finnish_finnish_nlp_fi.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_finnish_finnish_nlp_fi.md
new file mode 100644
index 00000000000000..79c60712803dd8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_finnish_finnish_nlp_fi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Finnish roberta_large_finnish_finnish_nlp RoBertaEmbeddings from Finnish-NLP
+author: John Snow Labs
+name: roberta_large_finnish_finnish_nlp
+date: 2024-09-03
+tags: [fi, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: fi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finnish_finnish_nlp` is a Finnish model originally trained by Finnish-NLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finnish_finnish_nlp_fi_5.5.0_3.0_1725374871705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finnish_finnish_nlp_fi_5.5.0_3.0_1725374871705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_finnish_finnish_nlp","fi") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_finnish_finnish_nlp","fi") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_finnish_finnish_nlp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|fi|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Finnish-NLP/roberta-large-finnish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_inbedder_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_inbedder_en.md
new file mode 100644
index 00000000000000..a507e6e73dbde8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_inbedder_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_inbedder RoBertaEmbeddings from BrandonZYW
+author: John Snow Labs
+name: roberta_large_inbedder
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_inbedder` is a English model originally trained by BrandonZYW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_inbedder_en_5.5.0_3.0_1725382219654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_inbedder_en_5.5.0_3.0_1725382219654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_inbedder","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_inbedder","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_inbedder|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/BrandonZYW/roberta-large-InBedder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_inbedder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_inbedder_pipeline_en.md
new file mode 100644
index 00000000000000..0451b83c0a9421
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_inbedder_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_inbedder_pipeline pipeline RoBertaEmbeddings from BrandonZYW
+author: John Snow Labs
+name: roberta_large_inbedder_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_inbedder_pipeline` is a English model originally trained by BrandonZYW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_inbedder_pipeline_en_5.5.0_3.0_1725382293583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_inbedder_pipeline_en_5.5.0_3.0_1725382293583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_inbedder_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_inbedder_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_inbedder_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/BrandonZYW/roberta-large-InBedder
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_roco_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_roco_v2_en.md
new file mode 100644
index 00000000000000..80366298d1d731
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_roco_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_roco_v2 RoBertaEmbeddings from MohamedAhmedAE
+author: John Snow Labs
+name: roberta_large_roco_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_roco_v2` is a English model originally trained by MohamedAhmedAE.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_roco_v2_en_5.5.0_3.0_1725375465725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_roco_v2_en_5.5.0_3.0_1725375465725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_roco_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_roco_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_roco_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MohamedAhmedAE/Roberta_large_Roco_V2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_large_roco_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_roco_v2_pipeline_en.md
new file mode 100644
index 00000000000000..0ad2fa30305cf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_large_roco_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_roco_v2_pipeline pipeline RoBertaEmbeddings from MohamedAhmedAE
+author: John Snow Labs
+name: roberta_large_roco_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_roco_v2_pipeline` is a English model originally trained by MohamedAhmedAE.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_roco_v2_pipeline_en_5.5.0_3.0_1725375536531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_roco_v2_pipeline_en_5.5.0_3.0_1725375536531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_roco_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_roco_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_roco_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MohamedAhmedAE/Roberta_large_Roco_V2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_llama3_1405b_twitter_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_llama3_1405b_twitter_sentiment_en.md
new file mode 100644
index 00000000000000..4a9fa0583753b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_llama3_1405b_twitter_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_llama3_1405b_twitter_sentiment RoBertaForSequenceClassification from AdamLucek
+author: John Snow Labs
+name: roberta_llama3_1405b_twitter_sentiment
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_llama3_1405b_twitter_sentiment` is a English model originally trained by AdamLucek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_llama3_1405b_twitter_sentiment_en_5.5.0_3.0_1725368834397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_llama3_1405b_twitter_sentiment_en_5.5.0_3.0_1725368834397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_llama3_1405b_twitter_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_llama3_1405b_twitter_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_llama3_1405b_twitter_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|428.9 MB|
+
+## References
+
+https://huggingface.co/AdamLucek/roberta-llama3.1405B-twitter-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_llama3_1405b_twitter_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_llama3_1405b_twitter_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..89f2e5cd6aebe9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_llama3_1405b_twitter_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_llama3_1405b_twitter_sentiment_pipeline pipeline RoBertaForSequenceClassification from AdamLucek
+author: John Snow Labs
+name: roberta_llama3_1405b_twitter_sentiment_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_llama3_1405b_twitter_sentiment_pipeline` is a English model originally trained by AdamLucek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_llama3_1405b_twitter_sentiment_pipeline_en_5.5.0_3.0_1725368875679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_llama3_1405b_twitter_sentiment_pipeline_en_5.5.0_3.0_1725368875679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_llama3_1405b_twitter_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_llama3_1405b_twitter_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_llama3_1405b_twitter_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|428.9 MB|
+
+## References
+
+https://huggingface.co/AdamLucek/roberta-llama3.1405B-twitter-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_medium_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_medium_en.md
new file mode 100644
index 00000000000000..835dc0334f8242
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_medium_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_medium RoBertaEmbeddings from JackBAI
+author: John Snow Labs
+name: roberta_medium
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_medium` is a English model originally trained by JackBAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_medium_en_5.5.0_3.0_1725374652080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_medium_en_5.5.0_3.0_1725374652080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_medium","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_medium","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_medium|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|99.0 MB|
+
+## References
+
+https://huggingface.co/JackBAI/roberta-medium
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_medium_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_medium_pipeline_en.md
new file mode 100644
index 00000000000000..edc728d07b8c42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_medium_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_medium_pipeline pipeline RoBertaEmbeddings from JackBAI
+author: John Snow Labs
+name: roberta_medium_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_medium_pipeline` is a English model originally trained by JackBAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_medium_pipeline_en_5.5.0_3.0_1725374685763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_medium_pipeline_en_5.5.0_3.0_1725374685763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_medium_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_medium_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_medium_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|99.0 MB|
+
+## References
+
+https://huggingface.co/JackBAI/roberta-medium
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_company_segment_ner_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_company_segment_ner_en.md
new file mode 100644
index 00000000000000..e106b2fd85becc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_company_segment_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_ner_company_segment_ner RoBertaForTokenClassification from wolfrage89
+author: John Snow Labs
+name: roberta_ner_company_segment_ner
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_company_segment_ner` is a English model originally trained by wolfrage89.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_company_segment_ner_en_5.5.0_3.0_1725383522948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_company_segment_ner_en_5.5.0_3.0_1725383522948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_ner_company_segment_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_ner_company_segment_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_company_segment_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/wolfrage89/company_segment_ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_company_segment_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_company_segment_ner_pipeline_en.md
new file mode 100644
index 00000000000000..307a95144a901f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_company_segment_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_ner_company_segment_ner_pipeline pipeline RoBertaForTokenClassification from wolfrage89
+author: John Snow Labs
+name: roberta_ner_company_segment_ner_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_company_segment_ner_pipeline` is a English model originally trained by wolfrage89.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_company_segment_ner_pipeline_en_5.5.0_3.0_1725383608752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_company_segment_ner_pipeline_en_5.5.0_3.0_1725383608752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_ner_company_segment_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_ner_company_segment_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_company_segment_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/wolfrage89/company_segment_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_en.md
new file mode 100644
index 00000000000000..be854ffd3f8871
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_en.md
@@ -0,0 +1,112 @@
+---
+layout: model
+title: English RobertaForTokenClassification Large Cased model (from tner)
+author: John Snow Labs
+name: roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous
+date: 2024-09-03
+tags: [bert, ner, open_source, en, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-tweetner-2020-selflabel2020-continuous` is a English model originally trained by `tner`.
+
+## Predicted Entities
+
+`group`, `creative_work`, `person`, `event`, `corporation`, `location`, `product`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_en_5.5.0_3.0_1725383343854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_en_5.5.0_3.0_1725383343854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous","en") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous","en") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.ner.roberta.tweet.tweetner_2020_selflabel2020_continuous.large.by_tner").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/tner/roberta-large-tweetner-2020-selflabel2020-continuous
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline_en.md
new file mode 100644
index 00000000000000..15822480eae6b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline pipeline RoBertaForTokenClassification from tner
+author: John Snow Labs
+name: roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline` is a English model originally trained by tner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline_en_5.5.0_3.0_1725383416158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline_en_5.5.0_3.0_1725383416158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_roberta_large_tweetner_2020_selflabel2020_continuous_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/tner/roberta-large-tweetner-2020-selflabel2020-continuous
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_offensive_junior_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_offensive_junior_en.md
new file mode 100644
index 00000000000000..6f9953f1712ed5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_offensive_junior_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_offensive_junior RoBertaForSequenceClassification from imaether
+author: John Snow Labs
+name: roberta_offensive_junior
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_offensive_junior` is a English model originally trained by imaether.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_offensive_junior_en_5.5.0_3.0_1725402159807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_offensive_junior_en_5.5.0_3.0_1725402159807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_offensive_junior","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_offensive_junior", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_offensive_junior|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|447.9 MB|
+
+## References
+
+https://huggingface.co/imaether/roberta-offensive-junior
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_offensive_junior_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_offensive_junior_pipeline_en.md
new file mode 100644
index 00000000000000..c279ecb11a3aaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_offensive_junior_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_offensive_junior_pipeline pipeline RoBertaForSequenceClassification from imaether
+author: John Snow Labs
+name: roberta_offensive_junior_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_offensive_junior_pipeline` is a English model originally trained by imaether.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_offensive_junior_pipeline_en_5.5.0_3.0_1725402184849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_offensive_junior_pipeline_en_5.5.0_3.0_1725402184849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_offensive_junior_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_offensive_junior_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_offensive_junior_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|447.9 MB|
+
+## References
+
+https://huggingface.co/imaether/roberta-offensive-junior
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_perigon200k_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_perigon200k_en.md
new file mode 100644
index 00000000000000..4a01acd749a9c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_perigon200k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_perigon200k RoBertaEmbeddings from judy93536
+author: John Snow Labs
+name: roberta_perigon200k
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_perigon200k` is a English model originally trained by judy93536.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_perigon200k_en_5.5.0_3.0_1725382069812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_perigon200k_en_5.5.0_3.0_1725382069812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_perigon200k","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_perigon200k","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_perigon200k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/judy93536/roberta-perigon200k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_perigon200k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_perigon200k_pipeline_en.md
new file mode 100644
index 00000000000000..bca31563c5957a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_perigon200k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_perigon200k_pipeline pipeline RoBertaEmbeddings from judy93536
+author: John Snow Labs
+name: roberta_perigon200k_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_perigon200k_pipeline` is a English model originally trained by judy93536.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_perigon200k_pipeline_en_5.5.0_3.0_1725382094514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_perigon200k_pipeline_en_5.5.0_3.0_1725382094514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_perigon200k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_perigon200k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_perigon200k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/judy93536/roberta-perigon200k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_base_squad_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_base_squad_finetuned_squad_en.md
new file mode 100644
index 00000000000000..a7ef903e0e8cf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_base_squad_finetuned_squad_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Base Cased model (from Swty)
+author: John Snow Labs
+name: roberta_qa_base_squad_finetuned_squad
+date: 2024-09-03
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-squad-finetuned-squad` is a English model originally trained by `Swty`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad_finetuned_squad_en_5.5.0_3.0_1725371457468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad_finetuned_squad_en_5.5.0_3.0_1725371457468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_squad_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_squad_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_base_squad_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Swty/roberta-base-squad-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_base_squad_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_base_squad_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..c8a521671da479
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_base_squad_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_base_squad_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from Swty
+author: John Snow Labs
+name: roberta_qa_base_squad_finetuned_squad_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_squad_finetuned_squad_pipeline` is a English model originally trained by Swty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad_finetuned_squad_pipeline_en_5.5.0_3.0_1725371504202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad_finetuned_squad_pipeline_en_5.5.0_3.0_1725371504202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_base_squad_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_base_squad_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_base_squad_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/Swty/roberta-base-squad-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_bertserini_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_bertserini_roberta_base_en.md
new file mode 100644
index 00000000000000..39b37a2dea13b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_bertserini_roberta_base_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from rsvp-ai)
+author: John Snow Labs
+name: roberta_qa_bertserini_roberta_base
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bertserini-roberta-base` is a English model originally trained by `rsvp-ai`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_bertserini_roberta_base_en_5.5.0_3.0_1725370751434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_bertserini_roberta_base_en_5.5.0_3.0_1725370751434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_bertserini_roberta_base","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_bertserini_roberta_base","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.roberta.base.by_rsvp-ai").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_bertserini_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|448.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/rsvp-ai/bertserini-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_bertserini_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_bertserini_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..b542e71ccbb7f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_bertserini_roberta_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_bertserini_roberta_base_pipeline pipeline RoBertaForQuestionAnswering from rsvp-ai
+author: John Snow Labs
+name: roberta_qa_bertserini_roberta_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_bertserini_roberta_base_pipeline` is a English model originally trained by rsvp-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_bertserini_roberta_base_pipeline_en_5.5.0_3.0_1725370788453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_bertserini_roberta_base_pipeline_en_5.5.0_3.0_1725370788453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_bertserini_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_bertserini_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_bertserini_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|448.6 MB|
+
+## References
+
+https://huggingface.co/rsvp-ai/bertserini-roberta-base
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_finetuned_state2_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_finetuned_state2_en.md
new file mode 100644
index 00000000000000..a0bf042209dfa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_finetuned_state2_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Cased model (from skandaonsolve)
+author: John Snow Labs
+name: roberta_qa_finetuned_state2
+date: 2024-09-03
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-finetuned-state2` is a English model originally trained by `skandaonsolve`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_state2_en_5.5.0_3.0_1725370894575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_state2_en_5.5.0_3.0_1725370894575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_state2","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_state2","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_finetuned_state2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/skandaonsolve/roberta-finetuned-state2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..8852809820c215
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Base Cased model (from AnonymousSub)
+author: John Snow Labs
+name: roberta_qa_mask_step_pretraining_base_squadv2_epochs_3
+date: 2024-09-03
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `mask_step_pretraining_roberta-base_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_en_5.5.0_3.0_1725370517249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_en_5.5.0_3.0_1725370517249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_mask_step_pretraining_base_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_mask_step_pretraining_base_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_mask_step_pretraining_base_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.9 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/mask_step_pretraining_roberta-base_squadv2_epochs_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline_en.md
new file mode 100644
index 00000000000000..f3a866a3466bff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline_en_5.5.0_3.0_1725370544123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline_en_5.5.0_3.0_1725370544123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_mask_step_pretraining_base_squadv2_epochs_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.9 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/mask_step_pretraining_roberta-base_squadv2_epochs_3
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_qanlu_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_qanlu_en.md
new file mode 100644
index 00000000000000..9b00c54502ed5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_qanlu_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from AmazonScience)
+author: John Snow Labs
+name: roberta_qa_qanlu
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `qanlu` is a English model originally trained by `AmazonScience`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_qanlu_en_5.5.0_3.0_1725370305729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_qanlu_en_5.5.0_3.0_1725370305729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_qanlu","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_qanlu","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.roberta.by_AmazonScience").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_qanlu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AmazonScience/qanlu
+- https://github.com/amazon-research/question-answering-nlu
+- https://assets.amazon.science/33/ea/800419b24a09876601d8ab99bfb9/language-model-is-all-you-need-natural-language-understanding-as-question-answering.pdf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_qanlu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_qanlu_pipeline_en.md
new file mode 100644
index 00000000000000..5efcb68a4408c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_qanlu_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_qanlu_pipeline pipeline RoBertaForQuestionAnswering from AmazonScience
+author: John Snow Labs
+name: roberta_qa_qanlu_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_qanlu_pipeline` is a English model originally trained by AmazonScience.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_qanlu_pipeline_en_5.5.0_3.0_1725370338077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_qanlu_pipeline_en_5.5.0_3.0_1725370338077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_qanlu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_qanlu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_qanlu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/AmazonScience/qanlu
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_quales_iberlef_squad_2_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_quales_iberlef_squad_2_es.md
new file mode 100644
index 00000000000000..d61f1356ed6a3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_quales_iberlef_squad_2_es.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: Spanish RobertaForQuestionAnswering Cased model (from stevemobs)
+author: John Snow Labs
+name: roberta_qa_quales_iberlef_squad_2
+date: 2024-09-03
+tags: [es, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `quales-iberlef-squad_2` is a Spanish model originally trained by `stevemobs`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_quales_iberlef_squad_2_es_5.5.0_3.0_1725370742789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_quales_iberlef_squad_2_es_5.5.0_3.0_1725370742789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_quales_iberlef_squad_2","es")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_quales_iberlef_squad_2","es")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_quales_iberlef_squad_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/stevemobs/quales-iberlef-squad_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_quales_iberlef_squad_2_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_quales_iberlef_squad_2_pipeline_es.md
new file mode 100644
index 00000000000000..195003276e41c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_quales_iberlef_squad_2_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish roberta_qa_quales_iberlef_squad_2_pipeline pipeline RoBertaForQuestionAnswering from stevemobs
+author: John Snow Labs
+name: roberta_qa_quales_iberlef_squad_2_pipeline
+date: 2024-09-03
+tags: [es, open_source, pipeline, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_quales_iberlef_squad_2_pipeline` is a Castilian, Spanish model originally trained by stevemobs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_quales_iberlef_squad_2_pipeline_es_5.5.0_3.0_1725370821541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_quales_iberlef_squad_2_pipeline_es_5.5.0_3.0_1725370821541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_quales_iberlef_squad_2_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_quales_iberlef_squad_2_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_quales_iberlef_squad_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/stevemobs/quales-iberlef-squad_2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..fff1796dc33af0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Base Cased model (from AnonymousSub)
+author: John Snow Labs
+name: roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3
+date: 2024-09-03
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_recipes-roberta-base_EASY_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_en_5.5.0_3.0_1725371647558.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_en_5.5.0_3.0_1725371647558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_recipes-roberta-base_EASY_squadv2_epochs_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline_en.md
new file mode 100644
index 00000000000000..1a2a8b843d0823
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline_en_5.5.0_3.0_1725371672934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline_en_5.5.0_3.0_1725371672934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_recipe_triplet_recipes_base_easy_squadv2_epochs_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/recipe_triplet_recipes-roberta-base_EASY_squadv2_epochs_3
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_1B_1_finetuned_squadv1_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_1B_1_finetuned_squadv1_en.md
new file mode 100644
index 00000000000000..4837f0638d62a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_1B_1_finetuned_squadv1_en.md
@@ -0,0 +1,109 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from mrm8488)
+author: John Snow Labs
+name: roberta_qa_roberta_base_1B_1_finetuned_squadv1
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-1B-1-finetuned-squadv1` is a English model originally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_1B_1_finetuned_squadv1_en_5.5.0_3.0_1725370506842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_1B_1_finetuned_squadv1_en_5.5.0_3.0_1725370506842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_1B_1_finetuned_squadv1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_1B_1_finetuned_squadv1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_1B_1_finetuned_squadv1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|446.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/roberta-base-1B-1-finetuned-squadv1
+- https://twitter.com/mrm8488
+- https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/
+- https://www.linkedin.com/in/manuel-romero-cs/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline_en.md
new file mode 100644
index 00000000000000..a44cba743ae8ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline pipeline RoBertaForQuestionAnswering from mrm8488
+author: John Snow Labs
+name: roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline_en_5.5.0_3.0_1725370538354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline_en_5.5.0_3.0_1725370538354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_1B_1_finetuned_squadv1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|446.4 MB|
+
+## References
+
+https://huggingface.co/mrm8488/roberta-base-1B-1-finetuned-squadv1
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_MITmovie_squad_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_MITmovie_squad_en.md
new file mode 100644
index 00000000000000..97eae3d0c19ce9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_MITmovie_squad_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from thatdramebaazguy)
+author: John Snow Labs
+name: roberta_qa_roberta_base_MITmovie_squad
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-MITmovie-squad` is a English model originally trained by `thatdramebaazguy`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_MITmovie_squad_en_5.5.0_3.0_1725370540600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_MITmovie_squad_en_5.5.0_3.0_1725370540600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_MITmovie_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_MITmovie_squad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.movie_squad.roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_MITmovie_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|460.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/thatdramebaazguy/roberta-base-MITmovie-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_MITmovie_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_MITmovie_squad_pipeline_en.md
new file mode 100644
index 00000000000000..bea4fbc9bf1d6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_MITmovie_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_MITmovie_squad_pipeline pipeline RoBertaForQuestionAnswering from thatdramebaazguy
+author: John Snow Labs
+name: roberta_qa_roberta_base_MITmovie_squad_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_MITmovie_squad_pipeline` is a English model originally trained by thatdramebaazguy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_MITmovie_squad_pipeline_en_5.5.0_3.0_1725370578263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_MITmovie_squad_pipeline_en_5.5.0_3.0_1725370578263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_MITmovie_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_MITmovie_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_MITmovie_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|460.7 MB|
+
+## References
+
+https://huggingface.co/thatdramebaazguy/roberta-base-MITmovie-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2_en.md
new file mode 100644
index 00000000000000..7471e190343ea2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from anas-awadalla)
+author: John Snow Labs
+name: roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-few-shot-k-1024-finetuned-squad-seed-2` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2_en_5.5.0_3.0_1725370406643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2_en_5.5.0_3.0_1725370406643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.roberta.base_1024d_seed_2").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|438.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-1024-finetuned-squad-seed-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad2_distilled_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad2_distilled_en.md
new file mode 100644
index 00000000000000..94ba6206a83542
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad2_distilled_en.md
@@ -0,0 +1,116 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from deepset)
+author: John Snow Labs
+name: roberta_qa_roberta_base_squad2_distilled
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-squad2-distilled` is a English model originally trained by `deepset`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad2_distilled_en_5.5.0_3.0_1725371071652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad2_distilled_en_5.5.0_3.0_1725371071652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_squad2_distilled","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_squad2_distilled","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.roberta.distilled_base.by_deepset").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_squad2_distilled|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|462.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/deepset/roberta-base-squad2-distilled
+- https://www.linkedin.com/company/deepset-ai/
+- https://haystack.deepset.ai/community/join
+- https://github.com/deepset-ai/FARM
+- http://www.deepset.ai/jobs
+- https://twitter.com/deepset_ai
+- https://github.com/deepset-ai/haystack/discussions
+- https://github.com/deepset-ai/haystack/
+- https://deepset.ai
+- https://deepset.ai/germanquad
+- https://deepset.ai/german-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad2_distilled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad2_distilled_pipeline_en.md
new file mode 100644
index 00000000000000..1ac3014fe9b4eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad2_distilled_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_squad2_distilled_pipeline pipeline RoBertaForQuestionAnswering from deepset
+author: John Snow Labs
+name: roberta_qa_roberta_base_squad2_distilled_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_squad2_distilled_pipeline` is a English model originally trained by deepset.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad2_distilled_pipeline_en_5.5.0_3.0_1725371098833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad2_distilled_pipeline_en_5.5.0_3.0_1725371098833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_squad2_distilled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_squad2_distilled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_squad2_distilled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.6 MB|
+
+## References
+
+https://huggingface.co/deepset/roberta-base-squad2-distilled
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad_en.md
new file mode 100644
index 00000000000000..4a2ac194c06106
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from jgammack)
+author: John Snow Labs
+name: roberta_qa_roberta_base_squad
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-squad` is a English model originally trained by `jgammack`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad_en_5.5.0_3.0_1725370636723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad_en_5.5.0_3.0_1725370636723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_squad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.roberta.base.by_jgammack").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+References
+
+- https://huggingface.co/jgammack/roberta-base-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad_pipeline_en.md
new file mode 100644
index 00000000000000..a04e4737355ef6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_base_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_squad_pipeline pipeline RoBertaForQuestionAnswering from jgammack
+author: John Snow Labs
+name: roberta_qa_roberta_base_squad_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_squad_pipeline` is a English model originally trained by jgammack.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad_pipeline_en_5.5.0_3.0_1725370663551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad_pipeline_en_5.5.0_3.0_1725370663551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+https://huggingface.co/jgammack/roberta-base-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_cuad_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_cuad_en.md
new file mode 100644
index 00000000000000..8c0ac60f00ea31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_cuad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from akdeniz27)
+author: John Snow Labs
+name: roberta_qa_roberta_large_cuad
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-cuad` is a English model originally trained by `akdeniz27`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_cuad_en_5.5.0_3.0_1725371345613.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_cuad_en_5.5.0_3.0_1725371345613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_large_cuad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_large_cuad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.cuad.roberta.large").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_large_cuad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/akdeniz27/roberta-large-cuad
+- https://github.com/TheAtticusProject/cuad
+- https://github.com/marshmellow77/cuad-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_cuad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_cuad_pipeline_en.md
new file mode 100644
index 00000000000000..da022c16e1fdab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_cuad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_large_cuad_pipeline pipeline RoBertaForQuestionAnswering from akdeniz27
+author: John Snow Labs
+name: roberta_qa_roberta_large_cuad_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_large_cuad_pipeline` is a English model originally trained by akdeniz27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_cuad_pipeline_en_5.5.0_3.0_1725371443313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_cuad_pipeline_en_5.5.0_3.0_1725371443313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_large_cuad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_large_cuad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_large_cuad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/akdeniz27/roberta-large-cuad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_0_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_0_en.md
new file mode 100644
index 00000000000000..f7675352649abc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_0_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from anas-awadalla)
+author: John Snow Labs
+name: roberta_qa_roberta_large_data_seed_0
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-data-seed-0` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_data_seed_0_en_5.5.0_3.0_1725371350218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_data_seed_0_en_5.5.0_3.0_1725371350218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_large_data_seed_0","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_large_data_seed_0","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.roberta.large_seed_0.by_anas-awadalla").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_large_data_seed_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/roberta-large-data-seed-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_0_pipeline_en.md
new file mode 100644
index 00000000000000..637c842f8ee189
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_large_data_seed_0_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: roberta_qa_roberta_large_data_seed_0_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_large_data_seed_0_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_data_seed_0_pipeline_en_5.5.0_3.0_1725371437018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_data_seed_0_pipeline_en_5.5.0_3.0_1725371437018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_large_data_seed_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_large_data_seed_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_large_data_seed_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/anas-awadalla/roberta-large-data-seed-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_4_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_4_en.md
new file mode 100644
index 00000000000000..7e1d66a392d2ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_4_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from anas-awadalla)
+author: John Snow Labs
+name: roberta_qa_roberta_large_data_seed_4
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-data-seed-4` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_data_seed_4_en_5.5.0_3.0_1725371115410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_data_seed_4_en_5.5.0_3.0_1725371115410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_large_data_seed_4","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_large_data_seed_4","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.roberta.large_seed_4").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_large_data_seed_4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/roberta-large-data-seed-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_4_pipeline_en.md
new file mode 100644
index 00000000000000..9bf2b98b55a640
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_large_data_seed_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_large_data_seed_4_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: roberta_qa_roberta_large_data_seed_4_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_large_data_seed_4_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_data_seed_4_pipeline_en_5.5.0_3.0_1725371196531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_data_seed_4_pipeline_en_5.5.0_3.0_1725371196531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_large_data_seed_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_large_data_seed_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_large_data_seed_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/anas-awadalla/roberta-large-data-seed-4
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_unaugmentedv3_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_unaugmentedv3_en.md
new file mode 100644
index 00000000000000..462be7772f8ded
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_unaugmentedv3_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from comacrae)
+author: John Snow Labs
+name: roberta_qa_roberta_unaugmentedv3
+date: 2024-09-03
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-unaugmentedv3` is a English model originally trained by `comacrae`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_unaugmentedv3_en_5.5.0_3.0_1725371004712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_unaugmentedv3_en_5.5.0_3.0_1725371004712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_unaugmentedv3","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_unaugmentedv3","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.roberta.augmented").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_unaugmentedv3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/comacrae/roberta-unaugmentedv3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_unaugmentedv3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_unaugmentedv3_pipeline_en.md
new file mode 100644
index 00000000000000..07b65ed3294615
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_roberta_unaugmentedv3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_unaugmentedv3_pipeline pipeline RoBertaForQuestionAnswering from comacrae
+author: John Snow Labs
+name: roberta_qa_roberta_unaugmentedv3_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_unaugmentedv3_pipeline` is a English model originally trained by comacrae.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_unaugmentedv3_pipeline_en_5.5.0_3.0_1725371030936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_unaugmentedv3_pipeline_en_5.5.0_3.0_1725371030936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_unaugmentedv3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_unaugmentedv3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_unaugmentedv3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+https://huggingface.co/comacrae/roberta-unaugmentedv3
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_spanish_clinical_trials_umls_7sgs_ner_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_spanish_clinical_trials_umls_7sgs_ner_en.md
new file mode 100644
index 00000000000000..702469e586c8cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_spanish_clinical_trials_umls_7sgs_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_spanish_clinical_trials_umls_7sgs_ner RoBertaForTokenClassification from medspaner
+author: John Snow Labs
+name: roberta_spanish_clinical_trials_umls_7sgs_ner
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_spanish_clinical_trials_umls_7sgs_ner` is a English model originally trained by medspaner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_spanish_clinical_trials_umls_7sgs_ner_en_5.5.0_3.0_1725384046385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_spanish_clinical_trials_umls_7sgs_ner_en_5.5.0_3.0_1725384046385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_spanish_clinical_trials_umls_7sgs_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_spanish_clinical_trials_umls_7sgs_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_spanish_clinical_trials_umls_7sgs_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|442.4 MB|
+
+## References
+
+https://huggingface.co/medspaner/roberta-es-clinical-trials-umls-7sgs-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline_en.md
new file mode 100644
index 00000000000000..2d805070c83cd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline pipeline RoBertaForTokenClassification from medspaner
+author: John Snow Labs
+name: roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline` is a English model originally trained by medspaner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline_en_5.5.0_3.0_1725384073489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline_en_5.5.0_3.0_1725384073489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_spanish_clinical_trials_umls_7sgs_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|442.4 MB|
+
+## References
+
+https://huggingface.co/medspaner/roberta-es-clinical-trials-umls-7sgs-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_sqlsav_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_sqlsav_en.md
new file mode 100644
index 00000000000000..6d462f9849a6e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_sqlsav_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_sqlsav RoBertaForSequenceClassification from Faraz24
+author: John Snow Labs
+name: roberta_sqlsav
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_sqlsav` is a English model originally trained by Faraz24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_sqlsav_en_5.5.0_3.0_1725336718866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_sqlsav_en_5.5.0_3.0_1725336718866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_sqlsav","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_sqlsav", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_sqlsav|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|424.5 MB|
+
+## References
+
+https://huggingface.co/Faraz24/roberta_sqlsav
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_sqlsav_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_sqlsav_pipeline_en.md
new file mode 100644
index 00000000000000..499838db03b3ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_sqlsav_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_sqlsav_pipeline pipeline RoBertaForSequenceClassification from Faraz24
+author: John Snow Labs
+name: roberta_sqlsav_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_sqlsav_pipeline` is a English model originally trained by Faraz24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_sqlsav_pipeline_en_5.5.0_3.0_1725336752704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_sqlsav_pipeline_en_5.5.0_3.0_1725336752704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_sqlsav_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_sqlsav_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_sqlsav_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|424.6 MB|
+
+## References
+
+https://huggingface.co/Faraz24/roberta_sqlsav
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_tuple_matcher_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_tuple_matcher_base_en.md
new file mode 100644
index 00000000000000..36d7c75dbb692f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_tuple_matcher_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_tuple_matcher_base RoBertaForSequenceClassification from shamz15531
+author: John Snow Labs
+name: roberta_tuple_matcher_base
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_tuple_matcher_base` is a English model originally trained by shamz15531.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_tuple_matcher_base_en_5.5.0_3.0_1725402513024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_tuple_matcher_base_en_5.5.0_3.0_1725402513024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_tuple_matcher_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_tuple_matcher_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_tuple_matcher_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|440.1 MB|
+
+## References
+
+https://huggingface.co/shamz15531/roberta_tuple_matcher_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_tuple_matcher_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_tuple_matcher_base_pipeline_en.md
new file mode 100644
index 00000000000000..497f46bc0a6fb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_tuple_matcher_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_tuple_matcher_base_pipeline pipeline RoBertaForSequenceClassification from shamz15531
+author: John Snow Labs
+name: roberta_tuple_matcher_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_tuple_matcher_base_pipeline` is a English model originally trained by shamz15531.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_tuple_matcher_base_pipeline_en_5.5.0_3.0_1725402544080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_tuple_matcher_base_pipeline_en_5.5.0_3.0_1725402544080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_tuple_matcher_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_tuple_matcher_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_tuple_matcher_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|440.1 MB|
+
+## References
+
+https://huggingface.co/shamz15531/roberta_tuple_matcher_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-robertachem_en.md b/docs/_posts/ahmedlone127/2024-09-03-robertachem_en.md
new file mode 100644
index 00000000000000..71c5eecfa1a594
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-robertachem_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English robertachem RoBertaForSequenceClassification from Chettaniiay
+author: John Snow Labs
+name: robertachem
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robertachem` is a English model originally trained by Chettaniiay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robertachem_en_5.5.0_3.0_1725337336745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robertachem_en_5.5.0_3.0_1725337336745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("robertachem","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("robertachem", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robertachem|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|425.8 MB|
+
+## References
+
+https://huggingface.co/Chettaniiay/RoBertaChem
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-rohberta_en.md b/docs/_posts/ahmedlone127/2024-09-03-rohberta_en.md
new file mode 100644
index 00000000000000..61d708df4fcb7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-rohberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rohberta RoBertaEmbeddings from Chettaniiay
+author: John Snow Labs
+name: rohberta
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rohberta` is a English model originally trained by Chettaniiay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rohberta_en_5.5.0_3.0_1725374718327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rohberta_en_5.5.0_3.0_1725374718327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("rohberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("rohberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rohberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/Chettaniiay/RoHBERTA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-rohberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-rohberta_pipeline_en.md
new file mode 100644
index 00000000000000..6fdbec772a8817
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-rohberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rohberta_pipeline pipeline RoBertaEmbeddings from Chettaniiay
+author: John Snow Labs
+name: rohberta_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rohberta_pipeline` is a English model originally trained by Chettaniiay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rohberta_pipeline_en_5.5.0_3.0_1725374743835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rohberta_pipeline_en_5.5.0_3.0_1725374743835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rohberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rohberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rohberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/Chettaniiay/RoHBERTA
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-rured2_ner_microsoft_mdeberta_v3_base_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-03-rured2_ner_microsoft_mdeberta_v3_base_pipeline_ru.md
new file mode 100644
index 00000000000000..a630b2a634473e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-rured2_ner_microsoft_mdeberta_v3_base_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian rured2_ner_microsoft_mdeberta_v3_base_pipeline pipeline DeBertaForTokenClassification from denis-gordeev
+author: John Snow Labs
+name: rured2_ner_microsoft_mdeberta_v3_base_pipeline
+date: 2024-09-03
+tags: [ru, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rured2_ner_microsoft_mdeberta_v3_base_pipeline` is a Russian model originally trained by denis-gordeev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rured2_ner_microsoft_mdeberta_v3_base_pipeline_ru_5.5.0_3.0_1725400617764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rured2_ner_microsoft_mdeberta_v3_base_pipeline_ru_5.5.0_3.0_1725400617764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rured2_ner_microsoft_mdeberta_v3_base_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rured2_ner_microsoft_mdeberta_v3_base_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rured2_ner_microsoft_mdeberta_v3_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|825.1 MB|
+
+## References
+
+https://huggingface.co/denis-gordeev/rured2-ner-microsoft-mdeberta-v3-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-rured2_ner_microsoft_mdeberta_v3_base_ru.md b/docs/_posts/ahmedlone127/2024-09-03-rured2_ner_microsoft_mdeberta_v3_base_ru.md
new file mode 100644
index 00000000000000..62d69afa60960d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-rured2_ner_microsoft_mdeberta_v3_base_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian rured2_ner_microsoft_mdeberta_v3_base DeBertaForTokenClassification from denis-gordeev
+author: John Snow Labs
+name: rured2_ner_microsoft_mdeberta_v3_base
+date: 2024-09-03
+tags: [ru, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rured2_ner_microsoft_mdeberta_v3_base` is a Russian model originally trained by denis-gordeev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rured2_ner_microsoft_mdeberta_v3_base_ru_5.5.0_3.0_1725400498467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rured2_ner_microsoft_mdeberta_v3_base_ru_5.5.0_3.0_1725400498467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("rured2_ner_microsoft_mdeberta_v3_base","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("rured2_ner_microsoft_mdeberta_v3_base", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rured2_ner_microsoft_mdeberta_v3_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ru|
+|Size:|825.1 MB|
+
+## References
+
+https://huggingface.co/denis-gordeev/rured2-ner-microsoft-mdeberta-v3-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sale_opportunity_pipeline_th.md b/docs/_posts/ahmedlone127/2024-09-03-sale_opportunity_pipeline_th.md
new file mode 100644
index 00000000000000..98c46d8ee953c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sale_opportunity_pipeline_th.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Thai sale_opportunity_pipeline pipeline CamemBertForSequenceClassification from rudy-technology
+author: John Snow Labs
+name: sale_opportunity_pipeline
+date: 2024-09-03
+tags: [th, open_source, pipeline, onnx]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sale_opportunity_pipeline` is a Thai model originally trained by rudy-technology.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sale_opportunity_pipeline_th_5.5.0_3.0_1725378038232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sale_opportunity_pipeline_th_5.5.0_3.0_1725378038232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sale_opportunity_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sale_opportunity_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sale_opportunity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/rudy-technology/sale_opportunity
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sale_opportunity_th.md b/docs/_posts/ahmedlone127/2024-09-03-sale_opportunity_th.md
new file mode 100644
index 00000000000000..1758ffe26c648f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sale_opportunity_th.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Thai sale_opportunity CamemBertForSequenceClassification from rudy-technology
+author: John Snow Labs
+name: sale_opportunity
+date: 2024-09-03
+tags: [th, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sale_opportunity` is a Thai model originally trained by rudy-technology.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sale_opportunity_th_5.5.0_3.0_1725378016536.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sale_opportunity_th_5.5.0_3.0_1725378016536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("sale_opportunity","th") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sale_opportunity", "th")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sale_opportunity|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|th|
+|Size:|394.3 MB|
+
+## References
+
+https://huggingface.co/rudy-technology/sale_opportunity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-schemeclassifier3_eng_en.md b/docs/_posts/ahmedlone127/2024-09-03-schemeclassifier3_eng_en.md
new file mode 100644
index 00000000000000..6ca95204de14ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-schemeclassifier3_eng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English schemeclassifier3_eng RoBertaForSequenceClassification from raruidol
+author: John Snow Labs
+name: schemeclassifier3_eng
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`schemeclassifier3_eng` is a English model originally trained by raruidol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/schemeclassifier3_eng_en_5.5.0_3.0_1725402614143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/schemeclassifier3_eng_en_5.5.0_3.0_1725402614143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("schemeclassifier3_eng","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("schemeclassifier3_eng", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|schemeclassifier3_eng|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/raruidol/SchemeClassifier3-ENG
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-schemeclassifier3_eng_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-schemeclassifier3_eng_pipeline_en.md
new file mode 100644
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+---
+layout: model
+title: English schemeclassifier3_eng_pipeline pipeline RoBertaForSequenceClassification from raruidol
+author: John Snow Labs
+name: schemeclassifier3_eng_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`schemeclassifier3_eng_pipeline` is a English model originally trained by raruidol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/schemeclassifier3_eng_pipeline_en_5.5.0_3.0_1725402703838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/schemeclassifier3_eng_pipeline_en_5.5.0_3.0_1725402703838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("schemeclassifier3_eng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("schemeclassifier3_eng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|schemeclassifier3_eng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/raruidol/SchemeClassifier3-ENG
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-scideberta_full_en.md b/docs/_posts/ahmedlone127/2024-09-03-scideberta_full_en.md
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+---
+layout: model
+title: English scideberta_full DeBertaForTokenClassification from KISTI-AI
+author: John Snow Labs
+name: scideberta_full
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scideberta_full` is a English model originally trained by KISTI-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scideberta_full_en_5.5.0_3.0_1725387913275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scideberta_full_en_5.5.0_3.0_1725387913275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("scideberta_full","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("scideberta_full", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scideberta_full|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|440.3 MB|
+
+## References
+
+https://huggingface.co/KISTI-AI/Scideberta-full
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-scideberta_full_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-scideberta_full_pipeline_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scideberta_full_pipeline pipeline DeBertaForTokenClassification from KISTI-AI
+author: John Snow Labs
+name: scideberta_full_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scideberta_full_pipeline` is a English model originally trained by KISTI-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scideberta_full_pipeline_en_5.5.0_3.0_1725388045383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scideberta_full_pipeline_en_5.5.0_3.0_1725388045383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scideberta_full_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scideberta_full_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scideberta_full_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|440.4 MB|
+
+## References
+
+https://huggingface.co/KISTI-AI/Scideberta-full
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-securebert_plus_en.md b/docs/_posts/ahmedlone127/2024-09-03-securebert_plus_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-securebert_plus_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English securebert_plus RoBertaEmbeddings from ehsanaghaei
+author: John Snow Labs
+name: securebert_plus
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_plus` is a English model originally trained by ehsanaghaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_plus_en_5.5.0_3.0_1725375215608.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_plus_en_5.5.0_3.0_1725375215608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("securebert_plus","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("securebert_plus","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|securebert_plus|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|461.8 MB|
+
+## References
+
+https://huggingface.co/ehsanaghaei/SecureBERT_Plus
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-securebert_plus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-securebert_plus_pipeline_en.md
new file mode 100644
index 00000000000000..bf39fe0d622a99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-securebert_plus_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English securebert_plus_pipeline pipeline RoBertaEmbeddings from ehsanaghaei
+author: John Snow Labs
+name: securebert_plus_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_plus_pipeline` is a English model originally trained by ehsanaghaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_plus_pipeline_en_5.5.0_3.0_1725375245817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_plus_pipeline_en_5.5.0_3.0_1725375245817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("securebert_plus_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("securebert_plus_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|securebert_plus_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|461.9 MB|
+
+## References
+
+https://huggingface.co/ehsanaghaei/SecureBERT_Plus
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en.md
new file mode 100644
index 00000000000000..a3dfed8222cd7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic XlmRoBertaSentenceEmbeddings from JEdward7777
+author: John Snow Labs
+name: sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic` is a English model originally trained by JEdward7777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en_5.5.0_3.0_1725398679960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic_en_5.5.0_3.0_1725398679960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_2_finetuned_xlm_r_masakhaner_swahili_macrolanguage_whole_word_phonetic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/JEdward7777/2-finetuned-xlm-r-masakhaner-swa-whole-word-phonetic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_afro_xlmr_mini_finetuned_kintweetsd_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_afro_xlmr_mini_finetuned_kintweetsd_en.md
new file mode 100644
index 00000000000000..6b6fd909a8f23b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_afro_xlmr_mini_finetuned_kintweetsd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_afro_xlmr_mini_finetuned_kintweetsd XlmRoBertaSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_afro_xlmr_mini_finetuned_kintweetsd
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afro_xlmr_mini_finetuned_kintweetsd` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_mini_finetuned_kintweetsd_en_5.5.0_3.0_1725397369113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_mini_finetuned_kintweetsd_en_5.5.0_3.0_1725397369113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afro_xlmr_mini_finetuned_kintweetsd","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afro_xlmr_mini_finetuned_kintweetsd","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afro_xlmr_mini_finetuned_kintweetsd|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|443.1 MB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-mini-finetuned-kintweetsD
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_arabic_camelbert_mix_ar.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_arabic_camelbert_mix_ar.md
new file mode 100644
index 00000000000000..08353bc9efe080
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_arabic_camelbert_mix_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_bert_base_arabic_camelbert_mix BertSentenceEmbeddings from CAMeL-Lab
+author: John Snow Labs
+name: sent_bert_base_arabic_camelbert_mix
+date: 2024-09-03
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabic_camelbert_mix` is a Arabic model originally trained by CAMeL-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_camelbert_mix_ar_5.5.0_3.0_1725355365450.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_camelbert_mix_ar_5.5.0_3.0_1725355365450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_arabic_camelbert_mix","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_arabic_camelbert_mix","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_arabic_camelbert_mix|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|406.6 MB|
+
+## References
+
+https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_arabic_camelbert_mix_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_arabic_camelbert_mix_pipeline_ar.md
new file mode 100644
index 00000000000000..1868edd1f9c246
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_arabic_camelbert_mix_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_bert_base_arabic_camelbert_mix_pipeline pipeline BertSentenceEmbeddings from CAMeL-Lab
+author: John Snow Labs
+name: sent_bert_base_arabic_camelbert_mix_pipeline
+date: 2024-09-03
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabic_camelbert_mix_pipeline` is a Arabic model originally trained by CAMeL-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_camelbert_mix_pipeline_ar_5.5.0_3.0_1725355385635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_camelbert_mix_pipeline_ar_5.5.0_3.0_1725355385635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_arabic_camelbert_mix_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_arabic_camelbert_mix_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_arabic_camelbert_mix_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_cased_google_bert_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_cased_google_bert_en.md
new file mode 100644
index 00000000000000..b25c717cb16a67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_cased_google_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_google_bert BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_base_cased_google_bert
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_google_bert` is a English model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_google_bert_en_5.5.0_3.0_1725355536111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_google_bert_en_5.5.0_3.0_1725355536111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_google_bert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_google_bert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_google_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_cased_google_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_cased_google_bert_pipeline_en.md
new file mode 100644
index 00000000000000..5f94706d37d896
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_cased_google_bert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_google_bert_pipeline pipeline BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_base_cased_google_bert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_google_bert_pipeline` is a English model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_google_bert_pipeline_en_5.5.0_3.0_1725355556943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_google_bert_pipeline_en_5.5.0_3.0_1725355556943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_google_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_google_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_google_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_finnish_uncased_v1_fi.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_finnish_uncased_v1_fi.md
new file mode 100644
index 00000000000000..ee64b2eac27765
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_finnish_uncased_v1_fi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Finnish sent_bert_base_finnish_uncased_v1 BertSentenceEmbeddings from TurkuNLP
+author: John Snow Labs
+name: sent_bert_base_finnish_uncased_v1
+date: 2024-09-03
+tags: [fi, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: fi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_finnish_uncased_v1` is a Finnish model originally trained by TurkuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_finnish_uncased_v1_fi_5.5.0_3.0_1725355455252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_finnish_uncased_v1_fi_5.5.0_3.0_1725355455252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_finnish_uncased_v1","fi") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_finnish_uncased_v1","fi") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_finnish_uncased_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|fi|
+|Size:|464.7 MB|
+
+## References
+
+https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_multilingual_cased_google_bert_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_multilingual_cased_google_bert_pipeline_xx.md
new file mode 100644
index 00000000000000..e12e6afaf6b467
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_multilingual_cased_google_bert_pipeline_xx.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Multilingual sent_bert_base_multilingual_cased_google_bert_pipeline pipeline BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_base_multilingual_cased_google_bert_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_multilingual_cased_google_bert_pipeline` is a Multilingual model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_cased_google_bert_pipeline_xx_5.5.0_3.0_1725355874613.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_cased_google_bert_pipeline_xx_5.5.0_3.0_1725355874613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_multilingual_cased_google_bert_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_multilingual_cased_google_bert_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_multilingual_cased_google_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-multilingual-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_multilingual_cased_google_bert_xx.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_multilingual_cased_google_bert_xx.md
new file mode 100644
index 00000000000000..01ca2d233ec5fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_multilingual_cased_google_bert_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sent_bert_base_multilingual_cased_google_bert BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_base_multilingual_cased_google_bert
+date: 2024-09-03
+tags: [xx, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_multilingual_cased_google_bert` is a Multilingual model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_cased_google_bert_xx_5.5.0_3.0_1725355841032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_cased_google_bert_xx_5.5.0_3.0_1725355841032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_multilingual_cased_google_bert","xx") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_multilingual_cased_google_bert","xx") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_multilingual_cased_google_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-multilingual-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_parsbert_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_parsbert_uncased_en.md
new file mode 100644
index 00000000000000..f79b90a090bf1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_parsbert_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_parsbert_uncased BertSentenceEmbeddings from HooshvareLab
+author: John Snow Labs
+name: sent_bert_base_parsbert_uncased
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_parsbert_uncased` is a English model originally trained by HooshvareLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_parsbert_uncased_en_5.5.0_3.0_1725355160364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_parsbert_uncased_en_5.5.0_3.0_1725355160364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_parsbert_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_parsbert_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_parsbert_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|606.4 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_parsbert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_parsbert_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..94aa8be91e4115
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_parsbert_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_parsbert_uncased_pipeline pipeline BertSentenceEmbeddings from HooshvareLab
+author: John Snow Labs
+name: sent_bert_base_parsbert_uncased_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_parsbert_uncased_pipeline` is a English model originally trained by HooshvareLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_parsbert_uncased_pipeline_en_5.5.0_3.0_1725355193604.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_parsbert_uncased_pipeline_en_5.5.0_3.0_1725355193604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_parsbert_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_parsbert_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_parsbert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|607.0 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_romanian_cased_v1_ro.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_romanian_cased_v1_ro.md
new file mode 100644
index 00000000000000..a68f3c374f2fd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_base_romanian_cased_v1_ro.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Moldavian, Moldovan, Romanian sent_bert_base_romanian_cased_v1 BertSentenceEmbeddings from dumitrescustefan
+author: John Snow Labs
+name: sent_bert_base_romanian_cased_v1
+date: 2024-09-03
+tags: [ro, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ro
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_romanian_cased_v1` is a Moldavian, Moldovan, Romanian model originally trained by dumitrescustefan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_romanian_cased_v1_ro_5.5.0_3.0_1725355234395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_romanian_cased_v1_ro_5.5.0_3.0_1725355234395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_romanian_cased_v1","ro") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_romanian_cased_v1","ro") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_romanian_cased_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ro|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/dumitrescustefan/bert-base-romanian-cased-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline_pt.md
new file mode 100644
index 00000000000000..f162330e559940
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline_pt.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Portuguese sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline pipeline BertSentenceEmbeddings from stjiris
+author: John Snow Labs
+name: sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline
+date: 2024-09-03
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline` is a Portuguese model originally trained by stjiris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline_pt_5.5.0_3.0_1725356068648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline_pt_5.5.0_3.0_1725356068648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-mlm-nli-sts-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pt.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pt.md
new file mode 100644
index 00000000000000..9e59564bbd70a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pt.md
@@ -0,0 +1,79 @@
+---
+layout: model
+title: Portuguese Legal BERT Sentence Embedding Large Cased model
+author: John Snow Labs
+name: sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1
+date: 2024-09-03
+tags: [bert, pt, embeddings, sentence, open_source, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Legal BERT Sentence Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-portuguese-cased-legal-mlm-nli-sts-v1` is a Portuguese model originally trained by `stjiris`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pt_5.5.0_3.0_1725356000518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1_pt_5.5.0_3.0_1725356000518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1", "pt") \
+  .setInputCols("sentence") \
+  .setOutputCol("bert_sentence")
+
+  nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, sent_embeddings ])
+    result = pipeline.fit(data).transform(data)
+```
+```scala
+val sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1", "pt")
+  .setInputCols("sentence")
+  .setOutputCol("bert_sentence")
+
+  val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, sent_embeddings ))
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_bert_large_portuguese_cased_legal_mlm_nli_sts_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+References
+
+- https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-mlm-nli-sts-v1
+- https://rufimelo99.github.io/SemanticSearchSystemForSTJ/
+- https://www.SBERT.net
+- https://github.com/rufimelo99
+- https://www.inesc-id.pt/projects/PR07005/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_kor_base_ko.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_kor_base_ko.md
new file mode 100644
index 00000000000000..2934d5adf50f58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_kor_base_ko.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Korean sent_bert_kor_base BertSentenceEmbeddings from kykim
+author: John Snow Labs
+name: sent_bert_kor_base
+date: 2024-09-03
+tags: [ko, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_kor_base` is a Korean model originally trained by kykim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_kor_base_ko_5.5.0_3.0_1725355183937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_kor_base_ko_5.5.0_3.0_1725355183937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_kor_base","ko") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_kor_base","ko") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_kor_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ko|
+|Size:|441.2 MB|
+
+## References
+
+https://huggingface.co/kykim/bert-kor-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_large_cased_whole_word_masking_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_large_cased_whole_word_masking_en.md
new file mode 100644
index 00000000000000..8f015013ce3b18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_large_cased_whole_word_masking_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_large_cased_whole_word_masking BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_large_cased_whole_word_masking
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_cased_whole_word_masking` is a English model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_whole_word_masking_en_5.5.0_3.0_1725355933573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_whole_word_masking_en_5.5.0_3.0_1725355933573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_cased_whole_word_masking","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_cased_whole_word_masking","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_cased_whole_word_masking|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/google-bert/bert-large-cased-whole-word-masking
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_large_cased_whole_word_masking_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_large_cased_whole_word_masking_pipeline_en.md
new file mode 100644
index 00000000000000..eb882e7525c1b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_large_cased_whole_word_masking_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_large_cased_whole_word_masking_pipeline pipeline BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_large_cased_whole_word_masking_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_cased_whole_word_masking_pipeline` is a English model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_whole_word_masking_pipeline_en_5.5.0_3.0_1725355997487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_whole_word_masking_pipeline_en_5.5.0_3.0_1725355997487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_large_cased_whole_word_masking_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_large_cased_whole_word_masking_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_cased_whole_word_masking_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/google-bert/bert-large-cased-whole-word-masking
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_tiny_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_tiny_uncased_en.md
new file mode 100644
index 00000000000000..032e74f29e4c60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_tiny_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_tiny_uncased BertSentenceEmbeddings from gaunernst
+author: John Snow Labs
+name: sent_bert_tiny_uncased
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_tiny_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_tiny_uncased_en_5.5.0_3.0_1725355345566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_tiny_uncased_en_5.5.0_3.0_1725355345566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_tiny_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_tiny_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_tiny_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-tiny-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bio_clinicalbert_emilyalsentzer_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bio_clinicalbert_emilyalsentzer_en.md
new file mode 100644
index 00000000000000..d34cd3d974d7a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bio_clinicalbert_emilyalsentzer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bio_clinicalbert_emilyalsentzer BertSentenceEmbeddings from emilyalsentzer
+author: John Snow Labs
+name: sent_bio_clinicalbert_emilyalsentzer
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bio_clinicalbert_emilyalsentzer` is a English model originally trained by emilyalsentzer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bio_clinicalbert_emilyalsentzer_en_5.5.0_3.0_1725355297970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bio_clinicalbert_emilyalsentzer_en_5.5.0_3.0_1725355297970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bio_clinicalbert_emilyalsentzer","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bio_clinicalbert_emilyalsentzer","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bio_clinicalbert_emilyalsentzer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_biobertpt_all_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-03-sent_biobertpt_all_pipeline_pt.md
new file mode 100644
index 00000000000000..1936ed94191715
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_biobertpt_all_pipeline_pt.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Portuguese sent_biobertpt_all_pipeline pipeline BertSentenceEmbeddings from pucpr
+author: John Snow Labs
+name: sent_biobertpt_all_pipeline
+date: 2024-09-03
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobertpt_all_pipeline` is a Portuguese model originally trained by pucpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobertpt_all_pipeline_pt_5.5.0_3.0_1725355059553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobertpt_all_pipeline_pt_5.5.0_3.0_1725355059553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_biobertpt_all_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_biobertpt_all_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobertpt_all_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|665.4 MB|
+
+## References
+
+https://huggingface.co/pucpr/biobertpt-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_biobertpt_all_pt.md b/docs/_posts/ahmedlone127/2024-09-03-sent_biobertpt_all_pt.md
new file mode 100644
index 00000000000000..08ad2cc9c81878
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_biobertpt_all_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese sent_biobertpt_all BertSentenceEmbeddings from pucpr
+author: John Snow Labs
+name: sent_biobertpt_all
+date: 2024-09-03
+tags: [pt, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobertpt_all` is a Portuguese model originally trained by pucpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobertpt_all_pt_5.5.0_3.0_1725355024906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobertpt_all_pt_5.5.0_3.0_1725355024906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_biobertpt_all","pt") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_biobertpt_all","pt") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobertpt_all|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|664.8 MB|
+
+## References
+
+https://huggingface.co/pucpr/biobertpt-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_biobit_it.md b/docs/_posts/ahmedlone127/2024-09-03-sent_biobit_it.md
new file mode 100644
index 00000000000000..929f0fb90c923b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_biobit_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian sent_biobit BertSentenceEmbeddings from IVN-RIN
+author: John Snow Labs
+name: sent_biobit
+date: 2024-09-03
+tags: [it, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobit` is a Italian model originally trained by IVN-RIN.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobit_it_5.5.0_3.0_1725355787081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobit_it_5.5.0_3.0_1725355787081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_biobit","it") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_biobit","it") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobit|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|it|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/IVN-RIN/bioBIT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_biobit_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-03-sent_biobit_pipeline_it.md
new file mode 100644
index 00000000000000..2a1a3d7418390c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_biobit_pipeline_it.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Italian sent_biobit_pipeline pipeline BertSentenceEmbeddings from IVN-RIN
+author: John Snow Labs
+name: sent_biobit_pipeline
+date: 2024-09-03
+tags: [it, open_source, pipeline, onnx]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobit_pipeline` is a Italian model originally trained by IVN-RIN.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobit_pipeline_it_5.5.0_3.0_1725355808496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobit_pipeline_it_5.5.0_3.0_1725355808496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_biobit_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_biobit_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/IVN-RIN/bioBIT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_en.md
new file mode 100644
index 00000000000000..ad37d1ae0b2112
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_biomednlp_biomedbert_base_uncased_abstract_fulltext BertSentenceEmbeddings from microsoft
+author: John Snow Labs
+name: sent_biomednlp_biomedbert_base_uncased_abstract_fulltext
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biomednlp_biomedbert_base_uncased_abstract_fulltext` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_en_5.5.0_3.0_1725354994648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_en_5.5.0_3.0_1725354994648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_biomednlp_biomedbert_base_uncased_abstract_fulltext","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_biomednlp_biomedbert_base_uncased_abstract_fulltext","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biomednlp_biomedbert_base_uncased_abstract_fulltext|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en.md
new file mode 100644
index 00000000000000..ca4b260e48e9aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline pipeline BertSentenceEmbeddings from microsoft
+author: John Snow Labs
+name: sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en_5.5.0_3.0_1725355015919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en_5.5.0_3.0_1725355015919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.7 MB|
+
+## References
+
+https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_22200_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_22200_en.md
new file mode 100644
index 00000000000000..a361356640955d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_22200_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_checkpoint_22200 XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_checkpoint_22200
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_22200` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_22200_en_5.5.0_3.0_1725397558860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_22200_en_5.5.0_3.0_1725397558860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_checkpoint_22200","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_checkpoint_22200","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_checkpoint_22200|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-22200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_22200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_22200_pipeline_en.md
new file mode 100644
index 00000000000000..2128eb74103a3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_checkpoint_22200_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_checkpoint_22200_pipeline pipeline XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_checkpoint_22200_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_22200_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_22200_pipeline_en_5.5.0_3.0_1725397621416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_22200_pipeline_en_5.5.0_3.0_1725397621416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_checkpoint_22200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_checkpoint_22200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_checkpoint_22200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-22200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_danish_bert_botxo_da.md b/docs/_posts/ahmedlone127/2024-09-03-sent_danish_bert_botxo_da.md
new file mode 100644
index 00000000000000..84149b6e73e859
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_danish_bert_botxo_da.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Danish sent_danish_bert_botxo BertSentenceEmbeddings from Maltehb
+author: John Snow Labs
+name: sent_danish_bert_botxo
+date: 2024-09-03
+tags: [da, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_danish_bert_botxo` is a Danish model originally trained by Maltehb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_danish_bert_botxo_da_5.5.0_3.0_1725355378907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_danish_bert_botxo_da_5.5.0_3.0_1725355378907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_danish_bert_botxo","da") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_danish_bert_botxo","da") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_danish_bert_botxo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|da|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/Maltehb/danish-bert-botxo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_danish_bert_botxo_pipeline_da.md b/docs/_posts/ahmedlone127/2024-09-03-sent_danish_bert_botxo_pipeline_da.md
new file mode 100644
index 00000000000000..37e402a70a0ea5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_danish_bert_botxo_pipeline_da.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Danish sent_danish_bert_botxo_pipeline pipeline BertSentenceEmbeddings from Maltehb
+author: John Snow Labs
+name: sent_danish_bert_botxo_pipeline
+date: 2024-09-03
+tags: [da, open_source, pipeline, onnx]
+task: Embeddings
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_danish_bert_botxo_pipeline` is a Danish model originally trained by Maltehb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_danish_bert_botxo_pipeline_da_5.5.0_3.0_1725355399692.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_danish_bert_botxo_pipeline_da_5.5.0_3.0_1725355399692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_danish_bert_botxo_pipeline", lang = "da")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_danish_bert_botxo_pipeline", lang = "da")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_danish_bert_botxo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|da|
+|Size:|412.8 MB|
+
+## References
+
+https://huggingface.co/Maltehb/danish-bert-botxo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_dragon_roberta_base_mixed_domain_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_dragon_roberta_base_mixed_domain_en.md
new file mode 100644
index 00000000000000..5e8e24959c3c66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_dragon_roberta_base_mixed_domain_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dragon_roberta_base_mixed_domain XlmRoBertaSentenceEmbeddings from joeranbosma
+author: John Snow Labs
+name: sent_dragon_roberta_base_mixed_domain
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dragon_roberta_base_mixed_domain` is a English model originally trained by joeranbosma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dragon_roberta_base_mixed_domain_en_5.5.0_3.0_1725357882381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dragon_roberta_base_mixed_domain_en_5.5.0_3.0_1725357882381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_dragon_roberta_base_mixed_domain","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_dragon_roberta_base_mixed_domain","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dragon_roberta_base_mixed_domain|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/joeranbosma/dragon-roberta-base-mixed-domain
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_dragon_roberta_base_mixed_domain_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_dragon_roberta_base_mixed_domain_pipeline_en.md
new file mode 100644
index 00000000000000..340a2fe977db50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_dragon_roberta_base_mixed_domain_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dragon_roberta_base_mixed_domain_pipeline pipeline XlmRoBertaSentenceEmbeddings from joeranbosma
+author: John Snow Labs
+name: sent_dragon_roberta_base_mixed_domain_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dragon_roberta_base_mixed_domain_pipeline` is a English model originally trained by joeranbosma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dragon_roberta_base_mixed_domain_pipeline_en_5.5.0_3.0_1725357934971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dragon_roberta_base_mixed_domain_pipeline_en_5.5.0_3.0_1725357934971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dragon_roberta_base_mixed_domain_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dragon_roberta_base_mixed_domain_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dragon_roberta_base_mixed_domain_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/joeranbosma/dragon-roberta-base-mixed-domain
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_entitycs_39_pep_malay_xlmr_base_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-sent_entitycs_39_pep_malay_xlmr_base_pipeline_xx.md
new file mode 100644
index 00000000000000..d2f981f9e29705
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_entitycs_39_pep_malay_xlmr_base_pipeline_xx.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Multilingual sent_entitycs_39_pep_malay_xlmr_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from huawei-noah
+author: John Snow Labs
+name: sent_entitycs_39_pep_malay_xlmr_base_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_entitycs_39_pep_malay_xlmr_base_pipeline` is a Multilingual model originally trained by huawei-noah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_entitycs_39_pep_malay_xlmr_base_pipeline_xx_5.5.0_3.0_1725334602976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_entitycs_39_pep_malay_xlmr_base_pipeline_xx_5.5.0_3.0_1725334602976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_entitycs_39_pep_malay_xlmr_base_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_entitycs_39_pep_malay_xlmr_base_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_entitycs_39_pep_malay_xlmr_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|945.1 MB|
+
+## References
+
+https://huggingface.co/huawei-noah/EntityCS-39-PEP_MS-xlmr-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_ewondo_xlm_roberta_base_nan.md b/docs/_posts/ahmedlone127/2024-09-03-sent_ewondo_xlm_roberta_base_nan.md
new file mode 100644
index 00000000000000..d3f51bfc8a7292
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_ewondo_xlm_roberta_base_nan.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: None sent_ewondo_xlm_roberta_base XlmRoBertaSentenceEmbeddings from ELRs
+author: John Snow Labs
+name: sent_ewondo_xlm_roberta_base
+date: 2024-09-03
+tags: [nan, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: nan
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ewondo_xlm_roberta_base` is a None model originally trained by ELRs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ewondo_xlm_roberta_base_nan_5.5.0_3.0_1725398610964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ewondo_xlm_roberta_base_nan_5.5.0_3.0_1725398610964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_ewondo_xlm_roberta_base","nan") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_ewondo_xlm_roberta_base","nan") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ewondo_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|nan|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ELRs/Ewondo_xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_ewondo_xlm_roberta_base_pipeline_nan.md b/docs/_posts/ahmedlone127/2024-09-03-sent_ewondo_xlm_roberta_base_pipeline_nan.md
new file mode 100644
index 00000000000000..e53bde1678e9ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_ewondo_xlm_roberta_base_pipeline_nan.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: None sent_ewondo_xlm_roberta_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from ELRs
+author: John Snow Labs
+name: sent_ewondo_xlm_roberta_base_pipeline
+date: 2024-09-03
+tags: [nan, open_source, pipeline, onnx]
+task: Embeddings
+language: nan
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ewondo_xlm_roberta_base_pipeline` is a None model originally trained by ELRs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ewondo_xlm_roberta_base_pipeline_nan_5.5.0_3.0_1725398668964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ewondo_xlm_roberta_base_pipeline_nan_5.5.0_3.0_1725398668964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_ewondo_xlm_roberta_base_pipeline", lang = "nan")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_ewondo_xlm_roberta_base_pipeline", lang = "nan")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ewondo_xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nan|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ELRs/Ewondo_xlm-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_fairlex_fscs_minilm_de.md b/docs/_posts/ahmedlone127/2024-09-03-sent_fairlex_fscs_minilm_de.md
new file mode 100644
index 00000000000000..ff1f5c14d78056
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_fairlex_fscs_minilm_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German sent_fairlex_fscs_minilm XlmRoBertaSentenceEmbeddings from coastalcph
+author: John Snow Labs
+name: sent_fairlex_fscs_minilm
+date: 2024-09-03
+tags: [de, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fairlex_fscs_minilm` is a German model originally trained by coastalcph.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_fairlex_fscs_minilm_de_5.5.0_3.0_1725334701268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fairlex_fscs_minilm_de_5.5.0_3.0_1725334701268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_fairlex_fscs_minilm","de") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_fairlex_fscs_minilm","de") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fairlex_fscs_minilm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|402.9 MB|
+
+## References
+
+https://huggingface.co/coastalcph/fairlex-fscs-minilm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_furina_with_transliteration_max_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_furina_with_transliteration_max_en.md
new file mode 100644
index 00000000000000..abc3460a8bebb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_furina_with_transliteration_max_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_furina_with_transliteration_max XlmRoBertaSentenceEmbeddings from yihongLiu
+author: John Snow Labs
+name: sent_furina_with_transliteration_max
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_furina_with_transliteration_max` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_furina_with_transliteration_max_en_5.5.0_3.0_1725398877876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_furina_with_transliteration_max_en_5.5.0_3.0_1725398877876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_furina_with_transliteration_max","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_furina_with_transliteration_max","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_furina_with_transliteration_max|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/furina-with-transliteration-max
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_furina_with_transliteration_max_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_furina_with_transliteration_max_pipeline_en.md
new file mode 100644
index 00000000000000..970348b64ed077
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_furina_with_transliteration_max_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_furina_with_transliteration_max_pipeline pipeline XlmRoBertaSentenceEmbeddings from yihongLiu
+author: John Snow Labs
+name: sent_furina_with_transliteration_max_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_furina_with_transliteration_max_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_furina_with_transliteration_max_pipeline_en_5.5.0_3.0_1725398969165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_furina_with_transliteration_max_pipeline_en_5.5.0_3.0_1725398969165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_furina_with_transliteration_max_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_furina_with_transliteration_max_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_furina_with_transliteration_max_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/furina-with-transliteration-max
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_gbert_large_de.md b/docs/_posts/ahmedlone127/2024-09-03-sent_gbert_large_de.md
new file mode 100644
index 00000000000000..21d0a34f658335
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_gbert_large_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German sent_gbert_large BertSentenceEmbeddings from deepset
+author: John Snow Labs
+name: sent_gbert_large
+date: 2024-09-03
+tags: [de, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gbert_large` is a German model originally trained by deepset.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gbert_large_de_5.5.0_3.0_1725355263112.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gbert_large_de_5.5.0_3.0_1725355263112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_gbert_large","de") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_gbert_large","de") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gbert_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/deepset/gbert-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_gbert_large_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-sent_gbert_large_pipeline_de.md
new file mode 100644
index 00000000000000..73a34b967692a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_gbert_large_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_gbert_large_pipeline pipeline BertSentenceEmbeddings from deepset
+author: John Snow Labs
+name: sent_gbert_large_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gbert_large_pipeline` is a German model originally trained by deepset.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gbert_large_pipeline_de_5.5.0_3.0_1725355327801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gbert_large_pipeline_de_5.5.0_3.0_1725355327801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_gbert_large_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_gbert_large_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gbert_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/deepset/gbert-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_base_pipeline_en.md
new file mode 100644
index 00000000000000..b41fae51c733c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_glot500_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from cis-lmu
+author: John Snow Labs
+name: sent_glot500_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_glot500_base_pipeline` is a English model originally trained by cis-lmu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_glot500_base_pipeline_en_5.5.0_3.0_1725334036364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_glot500_base_pipeline_en_5.5.0_3.0_1725334036364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_glot500_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_glot500_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_glot500_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/cis-lmu/glot500-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_with_transliteration_average_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_with_transliteration_average_en.md
new file mode 100644
index 00000000000000..adb23653fb3054
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_with_transliteration_average_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_glot500_with_transliteration_average XlmRoBertaSentenceEmbeddings from yihongLiu
+author: John Snow Labs
+name: sent_glot500_with_transliteration_average
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_glot500_with_transliteration_average` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_glot500_with_transliteration_average_en_5.5.0_3.0_1725358543306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_glot500_with_transliteration_average_en_5.5.0_3.0_1725358543306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_glot500_with_transliteration_average","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_glot500_with_transliteration_average","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_glot500_with_transliteration_average|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/glot500-with-transliteration-average
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_with_transliteration_average_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_with_transliteration_average_pipeline_en.md
new file mode 100644
index 00000000000000..8b26d70e18d01e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_glot500_with_transliteration_average_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_glot500_with_transliteration_average_pipeline pipeline XlmRoBertaSentenceEmbeddings from yihongLiu
+author: John Snow Labs
+name: sent_glot500_with_transliteration_average_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_glot500_with_transliteration_average_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_glot500_with_transliteration_average_pipeline_en_5.5.0_3.0_1725358635570.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_glot500_with_transliteration_average_pipeline_en_5.5.0_3.0_1725358635570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_glot500_with_transliteration_average_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_glot500_with_transliteration_average_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_glot500_with_transliteration_average_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/glot500-with-transliteration-average
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_hindi_marathi_dev_roberta_hi.md b/docs/_posts/ahmedlone127/2024-09-03-sent_hindi_marathi_dev_roberta_hi.md
new file mode 100644
index 00000000000000..81fe124e7e18e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_hindi_marathi_dev_roberta_hi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hindi sent_hindi_marathi_dev_roberta XlmRoBertaSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hindi_marathi_dev_roberta
+date: 2024-09-03
+tags: [hi, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hindi_marathi_dev_roberta` is a Hindi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hindi_marathi_dev_roberta_hi_5.5.0_3.0_1725357893154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hindi_marathi_dev_roberta_hi_5.5.0_3.0_1725357893154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_hindi_marathi_dev_roberta","hi") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_hindi_marathi_dev_roberta","hi") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hindi_marathi_dev_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|hi|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hindi-marathi-dev-roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_hindi_marathi_dev_roberta_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-03-sent_hindi_marathi_dev_roberta_pipeline_hi.md
new file mode 100644
index 00000000000000..e8b2c087bc2c84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_hindi_marathi_dev_roberta_pipeline_hi.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Hindi sent_hindi_marathi_dev_roberta_pipeline pipeline XlmRoBertaSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hindi_marathi_dev_roberta_pipeline
+date: 2024-09-03
+tags: [hi, open_source, pipeline, onnx]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hindi_marathi_dev_roberta_pipeline` is a Hindi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hindi_marathi_dev_roberta_pipeline_hi_5.5.0_3.0_1725357949034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hindi_marathi_dev_roberta_pipeline_hi_5.5.0_3.0_1725357949034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_hindi_marathi_dev_roberta_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_hindi_marathi_dev_roberta_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hindi_marathi_dev_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hindi-marathi-dev-roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_kcbert_large_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_kcbert_large_en.md
new file mode 100644
index 00000000000000..8fad0cb723b482
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_kcbert_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_kcbert_large BertSentenceEmbeddings from beomi
+author: John Snow Labs
+name: sent_kcbert_large
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kcbert_large` is a English model originally trained by beomi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kcbert_large_en_5.5.0_3.0_1725355792412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kcbert_large_en_5.5.0_3.0_1725355792412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_kcbert_large","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_kcbert_large","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kcbert_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/beomi/kcbert-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_kcbert_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_kcbert_large_pipeline_en.md
new file mode 100644
index 00000000000000..6994cdde36ba88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_kcbert_large_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_kcbert_large_pipeline pipeline BertSentenceEmbeddings from beomi
+author: John Snow Labs
+name: sent_kcbert_large_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kcbert_large_pipeline` is a English model originally trained by beomi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kcbert_large_pipeline_en_5.5.0_3.0_1725355858128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kcbert_large_pipeline_en_5.5.0_3.0_1725355858128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_kcbert_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_kcbert_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kcbert_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/beomi/kcbert-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_khmer_xlm_roberta_base_km.md b/docs/_posts/ahmedlone127/2024-09-03-sent_khmer_xlm_roberta_base_km.md
new file mode 100644
index 00000000000000..6caab47d86950f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_khmer_xlm_roberta_base_km.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Central Khmer, Khmer sent_khmer_xlm_roberta_base XlmRoBertaSentenceEmbeddings from channudam
+author: John Snow Labs
+name: sent_khmer_xlm_roberta_base
+date: 2024-09-03
+tags: [km, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: km
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_khmer_xlm_roberta_base` is a Central Khmer, Khmer model originally trained by channudam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_khmer_xlm_roberta_base_km_5.5.0_3.0_1725398349346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_khmer_xlm_roberta_base_km_5.5.0_3.0_1725398349346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_khmer_xlm_roberta_base","km") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_khmer_xlm_roberta_base","km") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_khmer_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|km|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/channudam/khmer-xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_khmer_xlm_roberta_base_pipeline_km.md b/docs/_posts/ahmedlone127/2024-09-03-sent_khmer_xlm_roberta_base_pipeline_km.md
new file mode 100644
index 00000000000000..9a65b28a9049e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_khmer_xlm_roberta_base_pipeline_km.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Central Khmer, Khmer sent_khmer_xlm_roberta_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from channudam
+author: John Snow Labs
+name: sent_khmer_xlm_roberta_base_pipeline
+date: 2024-09-03
+tags: [km, open_source, pipeline, onnx]
+task: Embeddings
+language: km
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_khmer_xlm_roberta_base_pipeline` is a Central Khmer, Khmer model originally trained by channudam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_khmer_xlm_roberta_base_pipeline_km_5.5.0_3.0_1725398408066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_khmer_xlm_roberta_base_pipeline_km_5.5.0_3.0_1725398408066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_khmer_xlm_roberta_base_pipeline", lang = "km")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_khmer_xlm_roberta_base_pipeline", lang = "km")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_khmer_xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|km|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/channudam/khmer-xlm-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bert_small_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bert_small_uncased_en.md
new file mode 100644
index 00000000000000..bd96446debc348
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bert_small_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_legal_bert_small_uncased BertSentenceEmbeddings from nlpaueb
+author: John Snow Labs
+name: sent_legal_bert_small_uncased
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_bert_small_uncased` is a English model originally trained by nlpaueb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_bert_small_uncased_en_5.5.0_3.0_1725355910594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_bert_small_uncased_en_5.5.0_3.0_1725355910594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_legal_bert_small_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_legal_bert_small_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_bert_small_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|130.6 MB|
+
+## References
+
+https://huggingface.co/nlpaueb/legal-bert-small-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bert_small_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bert_small_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..5f2ffcd03a7a54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bert_small_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_legal_bert_small_uncased_pipeline pipeline BertSentenceEmbeddings from nlpaueb
+author: John Snow Labs
+name: sent_legal_bert_small_uncased_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_bert_small_uncased_pipeline` is a English model originally trained by nlpaueb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_bert_small_uncased_pipeline_en_5.5.0_3.0_1725355917118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_bert_small_uncased_pipeline_en_5.5.0_3.0_1725355917118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_legal_bert_small_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_legal_bert_small_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_bert_small_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|131.1 MB|
+
+## References
+
+https://huggingface.co/nlpaueb/legal-bert-small-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bertimbau_base_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bertimbau_base_pipeline_pt.md
new file mode 100644
index 00000000000000..7a9421251ec9a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bertimbau_base_pipeline_pt.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Portuguese sent_legal_bertimbau_base_pipeline pipeline BertSentenceEmbeddings from rufimelo
+author: John Snow Labs
+name: sent_legal_bertimbau_base_pipeline
+date: 2024-09-03
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_bertimbau_base_pipeline` is a Portuguese model originally trained by rufimelo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_bertimbau_base_pipeline_pt_5.5.0_3.0_1725356061067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_bertimbau_base_pipeline_pt_5.5.0_3.0_1725356061067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_legal_bertimbau_base_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_legal_bertimbau_base_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_bertimbau_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|406.4 MB|
+
+## References
+
+https://huggingface.co/rufimelo/Legal-BERTimbau-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bertimbau_base_pt.md b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bertimbau_base_pt.md
new file mode 100644
index 00000000000000..5d59c7cf3d4d08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_bertimbau_base_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese sent_legal_bertimbau_base BertSentenceEmbeddings from rufimelo
+author: John Snow Labs
+name: sent_legal_bertimbau_base
+date: 2024-09-03
+tags: [pt, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_bertimbau_base` is a Portuguese model originally trained by rufimelo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_bertimbau_base_pt_5.5.0_3.0_1725356040780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_bertimbau_base_pt_5.5.0_3.0_1725356040780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_legal_bertimbau_base","pt") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_legal_bertimbau_base","pt") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_bertimbau_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|405.8 MB|
+
+## References
+
+https://huggingface.co/rufimelo/Legal-BERTimbau-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_legal_hebert_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_hebert_en.md
new file mode 100644
index 00000000000000..153e3c09211c51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_hebert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_legal_hebert BertSentenceEmbeddings from avichr
+author: John Snow Labs
+name: sent_legal_hebert
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_hebert` is a English model originally trained by avichr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_hebert_en_5.5.0_3.0_1725355577698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_hebert_en_5.5.0_3.0_1725355577698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_legal_hebert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_legal_hebert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_hebert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|462.5 MB|
+
+## References
+
+https://huggingface.co/avichr/Legal-heBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_legal_hebert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_hebert_pipeline_en.md
new file mode 100644
index 00000000000000..884bdc8ee42b3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_legal_hebert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_legal_hebert_pipeline pipeline BertSentenceEmbeddings from avichr
+author: John Snow Labs
+name: sent_legal_hebert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_hebert_pipeline` is a English model originally trained by avichr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_hebert_pipeline_en_5.5.0_3.0_1725355601362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_hebert_pipeline_en_5.5.0_3.0_1725355601362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_legal_hebert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_legal_hebert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_hebert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.0 MB|
+
+## References
+
+https://huggingface.co/avichr/Legal-heBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_marathi_roberta_mr.md b/docs/_posts/ahmedlone127/2024-09-03-sent_marathi_roberta_mr.md
new file mode 100644
index 00000000000000..eae60528e2a8dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_marathi_roberta_mr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Marathi sent_marathi_roberta XlmRoBertaSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_marathi_roberta
+date: 2024-09-03
+tags: [mr, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: mr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_marathi_roberta` is a Marathi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_marathi_roberta_mr_5.5.0_3.0_1725358368863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_marathi_roberta_mr_5.5.0_3.0_1725358368863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_marathi_roberta","mr") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_marathi_roberta","mr") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_marathi_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|mr|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/l3cube-pune/marathi-roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_marathi_roberta_pipeline_mr.md b/docs/_posts/ahmedlone127/2024-09-03-sent_marathi_roberta_pipeline_mr.md
new file mode 100644
index 00000000000000..cbc38f44de0208
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_marathi_roberta_pipeline_mr.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Marathi sent_marathi_roberta_pipeline pipeline XlmRoBertaSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_marathi_roberta_pipeline
+date: 2024-09-03
+tags: [mr, open_source, pipeline, onnx]
+task: Embeddings
+language: mr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_marathi_roberta_pipeline` is a Marathi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_marathi_roberta_pipeline_mr_5.5.0_3.0_1725358422924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_marathi_roberta_pipeline_mr_5.5.0_3.0_1725358422924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_marathi_roberta_pipeline", lang = "mr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_marathi_roberta_pipeline", lang = "mr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_marathi_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|mr|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/l3cube-pune/marathi-roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_mathbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_mathbert_en.md
new file mode 100644
index 00000000000000..268b1e410bfe54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_mathbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mathbert BertSentenceEmbeddings from tbs17
+author: John Snow Labs
+name: sent_mathbert
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mathbert` is a English model originally trained by tbs17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mathbert_en_5.5.0_3.0_1725355246566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mathbert_en_5.5.0_3.0_1725355246566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mathbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mathbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mathbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/tbs17/MathBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_mathbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_mathbert_pipeline_en.md
new file mode 100644
index 00000000000000..1ed4a321673424
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_mathbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mathbert_pipeline pipeline BertSentenceEmbeddings from tbs17
+author: John Snow Labs
+name: sent_mathbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mathbert_pipeline` is a English model originally trained by tbs17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mathbert_pipeline_en_5.5.0_3.0_1725355267353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mathbert_pipeline_en_5.5.0_3.0_1725355267353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mathbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mathbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mathbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.7 MB|
+
+## References
+
+https://huggingface.co/tbs17/MathBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_memo_final_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_final_en.md
new file mode 100644
index 00000000000000..0f2645aa96586c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_memo_final XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_memo_final
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_memo_final` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_memo_final_en_5.5.0_3.0_1725397885383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_memo_final_en_5.5.0_3.0_1725397885383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_memo_final","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_memo_final","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_memo_final|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_3500_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_3500_en.md
new file mode 100644
index 00000000000000..7e5e57289a8fc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_3500_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_memo_model_3500 XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_memo_model_3500
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_memo_model_3500` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_memo_model_3500_en_5.5.0_3.0_1725398213687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_memo_model_3500_en_5.5.0_3.0_1725398213687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_memo_model_3500","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_memo_model_3500","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_memo_model_3500|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_model_3500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_3500_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_3500_pipeline_en.md
new file mode 100644
index 00000000000000..bfb0f1125a4854
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_memo_model_3500_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_memo_model_3500_pipeline pipeline XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_memo_model_3500_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_memo_model_3500_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_memo_model_3500_pipeline_en_5.5.0_3.0_1725398268070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_memo_model_3500_pipeline_en_5.5.0_3.0_1725398268070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_memo_model_3500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_memo_model_3500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_memo_model_3500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_model_3500
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_mminilmv2_l12_h384_distilled_from_xlmr_large_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_mminilmv2_l12_h384_distilled_from_xlmr_large_en.md
new file mode 100644
index 00000000000000..c2679c381cba06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_mminilmv2_l12_h384_distilled_from_xlmr_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mminilmv2_l12_h384_distilled_from_xlmr_large XlmRoBertaSentenceEmbeddings from nreimers
+author: John Snow Labs
+name: sent_mminilmv2_l12_h384_distilled_from_xlmr_large
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mminilmv2_l12_h384_distilled_from_xlmr_large` is a English model originally trained by nreimers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mminilmv2_l12_h384_distilled_from_xlmr_large_en_5.5.0_3.0_1725358431475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mminilmv2_l12_h384_distilled_from_xlmr_large_en_5.5.0_3.0_1725358431475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_mminilmv2_l12_h384_distilled_from_xlmr_large","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_mminilmv2_l12_h384_distilled_from_xlmr_large","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mminilmv2_l12_h384_distilled_from_xlmr_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|282.9 MB|
+
+## References
+
+https://huggingface.co/nreimers/mMiniLMv2-L12-H384-distilled-from-XLMR-Large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en.md
new file mode 100644
index 00000000000000..a9d70b04d9f89d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline pipeline XlmRoBertaSentenceEmbeddings from nreimers
+author: John Snow Labs
+name: sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline` is a English model originally trained by nreimers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en_5.5.0_3.0_1725358524436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline_en_5.5.0_3.0_1725358524436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mminilmv2_l12_h384_distilled_from_xlmr_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|283.5 MB|
+
+## References
+
+https://huggingface.co/nreimers/mMiniLMv2-L12-H384-distilled-from-XLMR-Large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline_en.md
new file mode 100644
index 00000000000000..474f81249eb40a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline pipeline XlmRoBertaSentenceEmbeddings from NbAiLab
+author: John Snow Labs
+name: sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline` is a English model originally trained by NbAiLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline_en_5.5.0_3.0_1725333741184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline_en_5.5.0_3.0_1725333741184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_norwegian_bokml_roberta_base_ncc_plus_scandi_1e4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-roberta-base-ncc-plus-scandi-1e4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_ofa_multi_200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_ofa_multi_200_pipeline_en.md
new file mode 100644
index 00000000000000..c148914c465553
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_ofa_multi_200_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_ofa_multi_200_pipeline pipeline XlmRoBertaSentenceEmbeddings from yihongLiu
+author: John Snow Labs
+name: sent_ofa_multi_200_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ofa_multi_200_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ofa_multi_200_pipeline_en_5.5.0_3.0_1725334417549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ofa_multi_200_pipeline_en_5.5.0_3.0_1725334417549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_ofa_multi_200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_ofa_multi_200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ofa_multi_200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/ofa-multi-200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_pretrained_xlm_portuguese_e5_select_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_pretrained_xlm_portuguese_e5_select_en.md
new file mode 100644
index 00000000000000..3a5fd1bf85266a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_pretrained_xlm_portuguese_e5_select_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_pretrained_xlm_portuguese_e5_select XlmRoBertaSentenceEmbeddings from harish
+author: John Snow Labs
+name: sent_pretrained_xlm_portuguese_e5_select
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pretrained_xlm_portuguese_e5_select` is a English model originally trained by harish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pretrained_xlm_portuguese_e5_select_en_5.5.0_3.0_1725398370510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pretrained_xlm_portuguese_e5_select_en_5.5.0_3.0_1725398370510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_pretrained_xlm_portuguese_e5_select","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_pretrained_xlm_portuguese_e5_select","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pretrained_xlm_portuguese_e5_select|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/harish/preTrained-xlm-pt-e5-select
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_pretrained_xlm_portuguese_e5_select_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_pretrained_xlm_portuguese_e5_select_pipeline_en.md
new file mode 100644
index 00000000000000..6ba94ba863448d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_pretrained_xlm_portuguese_e5_select_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_pretrained_xlm_portuguese_e5_select_pipeline pipeline XlmRoBertaSentenceEmbeddings from harish
+author: John Snow Labs
+name: sent_pretrained_xlm_portuguese_e5_select_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pretrained_xlm_portuguese_e5_select_pipeline` is a English model originally trained by harish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pretrained_xlm_portuguese_e5_select_pipeline_en_5.5.0_3.0_1725398425302.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pretrained_xlm_portuguese_e5_select_pipeline_en_5.5.0_3.0_1725398425302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_pretrained_xlm_portuguese_e5_select_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_pretrained_xlm_portuguese_e5_select_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pretrained_xlm_portuguese_e5_select_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/harish/preTrained-xlm-pt-e5-select
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_radbert_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_radbert_en.md
new file mode 100644
index 00000000000000..3265fff361b798
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_radbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_radbert BertSentenceEmbeddings from StanfordAIMI
+author: John Snow Labs
+name: sent_radbert
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_radbert` is a English model originally trained by StanfordAIMI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_radbert_en_5.5.0_3.0_1725355541039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_radbert_en_5.5.0_3.0_1725355541039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_radbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_radbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_radbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|402.5 MB|
+
+## References
+
+https://huggingface.co/StanfordAIMI/RadBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_tod_xlmr_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_tod_xlmr_en.md
new file mode 100644
index 00000000000000..dabb0c12b45a04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_tod_xlmr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_tod_xlmr XlmRoBertaSentenceEmbeddings from umanlp
+author: John Snow Labs
+name: sent_tod_xlmr
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tod_xlmr` is a English model originally trained by umanlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tod_xlmr_en_5.5.0_3.0_1725359034326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tod_xlmr_en_5.5.0_3.0_1725359034326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_tod_xlmr","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_tod_xlmr","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tod_xlmr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/umanlp/TOD-XLMR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_tod_xlmr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_tod_xlmr_pipeline_en.md
new file mode 100644
index 00000000000000..595ccc2d62222c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_tod_xlmr_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_tod_xlmr_pipeline pipeline XlmRoBertaSentenceEmbeddings from umanlp
+author: John Snow Labs
+name: sent_tod_xlmr_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tod_xlmr_pipeline` is a English model originally trained by umanlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tod_xlmr_pipeline_en_5.5.0_3.0_1725359086950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tod_xlmr_pipeline_en_5.5.0_3.0_1725359086950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_tod_xlmr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_tod_xlmr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tod_xlmr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/umanlp/TOD-XLMR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_twitter_xlm_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_twitter_xlm_roberta_base_en.md
new file mode 100644
index 00000000000000..263648829240d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_twitter_xlm_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_twitter_xlm_roberta_base XlmRoBertaSentenceEmbeddings from cardiffnlp
+author: John Snow Labs
+name: sent_twitter_xlm_roberta_base
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_twitter_xlm_roberta_base` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_twitter_xlm_roberta_base_en_5.5.0_3.0_1725358135566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_twitter_xlm_roberta_base_en_5.5.0_3.0_1725358135566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_twitter_xlm_roberta_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_twitter_xlm_roberta_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_twitter_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_align_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_align_pipeline_en.md
new file mode 100644
index 00000000000000..2b25fc69634ce3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_align_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_align_pipeline pipeline XlmRoBertaSentenceEmbeddings from CZWin32768
+author: John Snow Labs
+name: sent_xlm_align_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_align_pipeline` is a English model originally trained by CZWin32768.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_align_pipeline_en_5.5.0_3.0_1725398523713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_align_pipeline_en_5.5.0_3.0_1725398523713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_align_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_align_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_align_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|660.1 MB|
+
+## References
+
+https://huggingface.co/CZWin32768/xlm-align
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_facebookai_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_facebookai_pipeline_xx.md
new file mode 100644
index 00000000000000..9c7a005a0df6b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_facebookai_pipeline_xx.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Multilingual sent_xlm_roberta_base_facebookai_pipeline pipeline XlmRoBertaSentenceEmbeddings from FacebookAI
+author: John Snow Labs
+name: sent_xlm_roberta_base_facebookai_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_facebookai_pipeline` is a Multilingual model originally trained by FacebookAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_facebookai_pipeline_xx_5.5.0_3.0_1725359807499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_facebookai_pipeline_xx_5.5.0_3.0_1725359807499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_facebookai_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_facebookai_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_facebookai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|653.5 MB|
+
+## References
+
+https://huggingface.co/FacebookAI/xlm-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_arabic_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_arabic_en.md
new file mode 100644
index 00000000000000..709c5baba8bfcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_arabic XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_arabic
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_arabic` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_arabic_en_5.5.0_3.0_1725359239812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_arabic_en_5.5.0_3.0_1725359239812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_arabic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_arabic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_arabic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-arabic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_arabic_pipeline_en.md
new file mode 100644
index 00000000000000..de3e9e4969e7ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_arabic_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_arabic_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_arabic_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_arabic_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_arabic_pipeline_en_5.5.0_3.0_1725359293851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_arabic_pipeline_en_5.5.0_3.0_1725359293851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_arabic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_arabic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-arabic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_clinais_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_clinais_en.md
new file mode 100644
index 00000000000000..c86734e582cbac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_clinais_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_clinais XlmRoBertaSentenceEmbeddings from joheras
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_clinais
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_clinais` is a English model originally trained by joheras.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_clinais_en_5.5.0_3.0_1725359623389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_clinais_en_5.5.0_3.0_1725359623389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_clinais","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_clinais","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_clinais|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|988.3 MB|
+
+## References
+
+https://huggingface.co/joheras/xlm-roberta-base-finetuned-clinais
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_clinais_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_clinais_pipeline_en.md
new file mode 100644
index 00000000000000..96f47f878eef0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_clinais_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_clinais_pipeline pipeline XlmRoBertaSentenceEmbeddings from joheras
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_clinais_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_clinais_pipeline` is a English model originally trained by joheras.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_clinais_pipeline_en_5.5.0_3.0_1725359690399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_clinais_pipeline_en_5.5.0_3.0_1725359690399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_clinais_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_clinais_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_clinais_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|988.8 MB|
+
+## References
+
+https://huggingface.co/joheras/xlm-roberta-base-finetuned-clinais
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_en.md
new file mode 100644
index 00000000000000..8bfffa9d2a1fa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned XlmRoBertaSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_en_5.5.0_3.0_1725397618287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_en_5.5.0_3.0_1725397618287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kin-finetuned-kin-tweets-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..1fa7fda8e52d41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline pipeline XlmRoBertaSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline_en_5.5.0_3.0_1725397683718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline_en_5.5.0_3.0_1725397683718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kin-finetuned-kin-tweets-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_dutch_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_dutch_en.md
new file mode 100644
index 00000000000000..395e1d18e53725
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_dutch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_on_runaways_dutch XlmRoBertaSentenceEmbeddings from Nadav
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_on_runaways_dutch
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_on_runaways_dutch` is a English model originally trained by Nadav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_on_runaways_dutch_en_5.5.0_3.0_1725334067573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_on_runaways_dutch_en_5.5.0_3.0_1725334067573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_on_runaways_dutch","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_on_runaways_dutch","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_on_runaways_dutch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Nadav/xlm-roberta-base-finetuned-on-runaways-nl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_french_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_french_en.md
new file mode 100644
index 00000000000000..8fa95b6f46bfd9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_on_runaways_french_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_on_runaways_french XlmRoBertaSentenceEmbeddings from Nadav
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_on_runaways_french
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_on_runaways_french` is a English model originally trained by Nadav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_on_runaways_french_en_5.5.0_3.0_1725334361672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_on_runaways_french_en_5.5.0_3.0_1725334361672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_on_runaways_french","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_on_runaways_french","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_on_runaways_french|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Nadav/xlm-roberta-base-finetuned-on-runaways-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_swahili_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_swahili_en.md
new file mode 100644
index 00000000000000..b3a33fd42e635a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_swahili_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_swahili XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_swahili
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_swahili` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_swahili_en_5.5.0_3.0_1725358706086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_swahili_en_5.5.0_3.0_1725358706086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_swahili","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_swahili","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_swahili|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-swahili
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_swahili_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_swahili_pipeline_en.md
new file mode 100644
index 00000000000000..acbfdb65b98537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_swahili_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_swahili_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_swahili_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_swahili_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_swahili_pipeline_en_5.5.0_3.0_1725358759095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_swahili_pipeline_en_5.5.0_3.0_1725358759095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_swahili_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_swahili_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_swahili_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-swahili
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_wolof_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_wolof_en.md
new file mode 100644
index 00000000000000..93c7c9b47ad1f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_wolof_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_wolof XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_wolof
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_wolof` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_wolof_en_5.5.0_3.0_1725398125607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_wolof_en_5.5.0_3.0_1725398125607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_wolof","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_wolof","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_wolof|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-wolof
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_zulu_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_zulu_en.md
new file mode 100644
index 00000000000000..e44be4b3b300ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_zulu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_zulu XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_zulu
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_zulu` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_zulu_en_5.5.0_3.0_1725398048861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_zulu_en_5.5.0_3.0_1725398048861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_zulu","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_zulu","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_zulu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-zulu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_zulu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_zulu_pipeline_en.md
new file mode 100644
index 00000000000000..d65514ff70544b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_finetuned_zulu_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_zulu_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_zulu_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_zulu_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_zulu_pipeline_en_5.5.0_3.0_1725398102926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_zulu_pipeline_en_5.5.0_3.0_1725398102926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_zulu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_zulu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_zulu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-zulu
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_xlmberttest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_xlmberttest_pipeline_en.md
new file mode 100644
index 00000000000000..3de194555555f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_xlmberttest_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_xlmberttest_pipeline pipeline XlmRoBertaSentenceEmbeddings from JungHun
+author: John Snow Labs
+name: sent_xlm_roberta_base_xlmberttest_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_xlmberttest_pipeline` is a English model originally trained by JungHun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_xlmberttest_pipeline_en_5.5.0_3.0_1725397909017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_xlmberttest_pipeline_en_5.5.0_3.0_1725397909017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_xlmberttest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_xlmberttest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_xlmberttest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|894.3 MB|
+
+## References
+
+https://huggingface.co/JungHun/xlm-roberta-base-xlmberttest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_v_base_trimmed_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_v_base_trimmed_english_en.md
new file mode 100644
index 00000000000000..4694af0fa5304b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_v_base_trimmed_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_english XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_english
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_english` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_english_en_5.5.0_3.0_1725359171936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_english_en_5.5.0_3.0_1725359171936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_v_base_trimmed_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_v_base_trimmed_english_pipeline_en.md
new file mode 100644
index 00000000000000..d16ba6b569a2e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_v_base_trimmed_english_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_english_pipeline pipeline XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_english_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_english_pipeline_en_5.5.0_3.0_1725359490957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_english_pipeline_en_5.5.0_3.0_1725359490957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_v_base_trimmed_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_v_base_trimmed_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlmr_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlmr_finetuned_en.md
new file mode 100644
index 00000000000000..3077690234c96f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlmr_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlmr_finetuned XlmRoBertaSentenceEmbeddings from kietnt0603
+author: John Snow Labs
+name: sent_xlmr_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlmr_finetuned` is a English model originally trained by kietnt0603.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlmr_finetuned_en_5.5.0_3.0_1725397496897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlmr_finetuned_en_5.5.0_3.0_1725397496897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlmr_finetuned","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlmr_finetuned","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlmr_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/kietnt0603/xlmr-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlmr_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlmr_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..1b4b6c8ff52ab6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlmr_finetuned_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlmr_finetuned_pipeline pipeline XlmRoBertaSentenceEmbeddings from kietnt0603
+author: John Snow Labs
+name: sent_xlmr_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlmr_finetuned_pipeline` is a English model originally trained by kietnt0603.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlmr_finetuned_pipeline_en_5.5.0_3.0_1725397553416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlmr_finetuned_pipeline_en_5.5.0_3.0_1725397553416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlmr_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlmr_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlmr_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/kietnt0603/xlmr-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlmroberta_twi_eng_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlmroberta_twi_eng_en.md
new file mode 100644
index 00000000000000..caa95d11678b37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlmroberta_twi_eng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlmroberta_twi_eng XlmRoBertaSentenceEmbeddings from sgjwong
+author: John Snow Labs
+name: sent_xlmroberta_twi_eng
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlmroberta_twi_eng` is a English model originally trained by sgjwong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlmroberta_twi_eng_en_5.5.0_3.0_1725358626067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlmroberta_twi_eng_en_5.5.0_3.0_1725358626067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlmroberta_twi_eng","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlmroberta_twi_eng","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlmroberta_twi_eng|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/sgjwong/xlmroberta-tw_eng
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlmroberta_twi_eng_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlmroberta_twi_eng_pipeline_en.md
new file mode 100644
index 00000000000000..780e57af405f2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlmroberta_twi_eng_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlmroberta_twi_eng_pipeline pipeline XlmRoBertaSentenceEmbeddings from sgjwong
+author: John Snow Labs
+name: sent_xlmroberta_twi_eng_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlmroberta_twi_eng_pipeline` is a English model originally trained by sgjwong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlmroberta_twi_eng_pipeline_en_5.5.0_3.0_1725358687688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlmroberta_twi_eng_pipeline_en_5.5.0_3.0_1725358687688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlmroberta_twi_eng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlmroberta_twi_eng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlmroberta_twi_eng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/sgjwong/xlmroberta-tw_eng
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_all_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_all_mpnet_base_v2_en.md
new file mode 100644
index 00000000000000..7be8f3fbae35be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_all_mpnet_base_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sentence_transformers_all_mpnet_base_v2 MPNetEmbeddings from ai-human-lab
+author: John Snow Labs
+name: sentence_transformers_all_mpnet_base_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_all_mpnet_base_v2` is a English model originally trained by ai-human-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_all_mpnet_base_v2_en_5.5.0_3.0_1725350422680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_all_mpnet_base_v2_en_5.5.0_3.0_1725350422680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("sentence_transformers_all_mpnet_base_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("sentence_transformers_all_mpnet_base_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentence_transformers_all_mpnet_base_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/ai-human-lab/sentence-transformers_all-mpnet-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_all_mpnet_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_all_mpnet_base_v2_pipeline_en.md
new file mode 100644
index 00000000000000..5ad360d4d4ce32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_all_mpnet_base_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sentence_transformers_all_mpnet_base_v2_pipeline pipeline MPNetEmbeddings from ai-human-lab
+author: John Snow Labs
+name: sentence_transformers_all_mpnet_base_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_all_mpnet_base_v2_pipeline` is a English model originally trained by ai-human-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_all_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725350443151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_all_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725350443151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentence_transformers_all_mpnet_base_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentence_transformers_all_mpnet_base_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentence_transformers_all_mpnet_base_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/ai-human-lab/sentence-transformers_all-mpnet-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_e5_small_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_e5_small_v2_en.md
new file mode 100644
index 00000000000000..5e51c6a02779af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_e5_small_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sentence_transformers_e5_small_v2 E5Embeddings from yunyu
+author: John Snow Labs
+name: sentence_transformers_e5_small_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_e5_small_v2` is a English model originally trained by yunyu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_e5_small_v2_en_5.5.0_3.0_1725332326534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_e5_small_v2_en_5.5.0_3.0_1725332326534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("sentence_transformers_e5_small_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("sentence_transformers_e5_small_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentence_transformers_e5_small_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|79.9 MB|
+
+## References
+
+https://huggingface.co/yunyu/sentence-transformers-e5-small-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_e5_small_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_e5_small_v2_pipeline_en.md
new file mode 100644
index 00000000000000..4e73a3aa56c2da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentence_transformers_e5_small_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sentence_transformers_e5_small_v2_pipeline pipeline E5Embeddings from yunyu
+author: John Snow Labs
+name: sentence_transformers_e5_small_v2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_e5_small_v2_pipeline` is a English model originally trained by yunyu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_e5_small_v2_pipeline_en_5.5.0_3.0_1725332350826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_e5_small_v2_pipeline_en_5.5.0_3.0_1725332350826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentence_transformers_e5_small_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentence_transformers_e5_small_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentence_transformers_e5_small_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|79.9 MB|
+
+## References
+
+https://huggingface.co/yunyu/sentence-transformers-e5-small-v2
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_italian_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_italian_pipeline_it.md
new file mode 100644
index 00000000000000..7c7f97bb1a2731
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_italian_pipeline_it.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Italian sentiment_analysis_italian_pipeline pipeline CamemBertForSequenceClassification from Taraassss
+author: John Snow Labs
+name: sentiment_analysis_italian_pipeline
+date: 2024-09-03
+tags: [it, open_source, pipeline, onnx]
+task: Text Classification
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_italian_pipeline` is a Italian model originally trained by Taraassss.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_italian_pipeline_it_5.5.0_3.0_1725325688608.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_italian_pipeline_it_5.5.0_3.0_1725325688608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_analysis_italian_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_italian_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|394.8 MB|
+
+## References
+
+https://huggingface.co/Taraassss/sentiment_analysis_IT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_pp_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_pp_en.md
new file mode 100644
index 00000000000000..6d634ea4af734c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_pp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_pp CamemBertForSequenceClassification from Ppxndpxdd
+author: John Snow Labs
+name: sentiment_analysis_pp
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_pp` is a English model originally trained by Ppxndpxdd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_pp_en_5.5.0_3.0_1725325535962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_pp_en_5.5.0_3.0_1725325535962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("sentiment_analysis_pp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sentiment_analysis_pp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_pp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.3 MB|
+
+## References
+
+https://huggingface.co/Ppxndpxdd/sentiment-analysis-pp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_pp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_pp_pipeline_en.md
new file mode 100644
index 00000000000000..a501c7640f2bb3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_pp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_analysis_pp_pipeline pipeline CamemBertForSequenceClassification from Ppxndpxdd
+author: John Snow Labs
+name: sentiment_analysis_pp_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_pp_pipeline` is a English model originally trained by Ppxndpxdd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_pp_pipeline_en_5.5.0_3.0_1725325554638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_pp_pipeline_en_5.5.0_3.0_1725325554638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_analysis_pp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_pp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_pp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/Ppxndpxdd/sentiment-analysis-pp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_sbcbi_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_sbcbi_en.md
new file mode 100644
index 00000000000000..5425acc995c990
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_sbcbi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_sbcbi DistilBertForSequenceClassification from sbcBI
+author: John Snow Labs
+name: sentiment_analysis_sbcbi
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_sbcbi` is a English model originally trained by sbcBI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_sbcbi_en_5.5.0_3.0_1725394043628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_sbcbi_en_5.5.0_3.0_1725394043628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_analysis_sbcbi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_sbcbi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_sbcbi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sbcBI/sentiment_analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_sbcbi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_sbcbi_pipeline_en.md
new file mode 100644
index 00000000000000..6736d022208ba2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_sbcbi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_analysis_sbcbi_pipeline pipeline DistilBertForSequenceClassification from sbcBI
+author: John Snow Labs
+name: sentiment_analysis_sbcbi_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_sbcbi_pipeline` is a English model originally trained by sbcBI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_sbcbi_pipeline_en_5.5.0_3.0_1725394057485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_sbcbi_pipeline_en_5.5.0_3.0_1725394057485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_analysis_sbcbi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_sbcbi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_sbcbi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sbcBI/sentiment_analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_wangyh6_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_wangyh6_en.md
new file mode 100644
index 00000000000000..74c664ca617269
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_wangyh6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_wangyh6 DistilBertForSequenceClassification from wangyh6
+author: John Snow Labs
+name: sentiment_analysis_wangyh6
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_wangyh6` is a English model originally trained by wangyh6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_wangyh6_en_5.5.0_3.0_1725329642461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_wangyh6_en_5.5.0_3.0_1725329642461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_analysis_wangyh6","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_wangyh6", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_wangyh6|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/wangyh6/sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_pipeline_th.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_pipeline_th.md
new file mode 100644
index 00000000000000..a2ba739131064e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_pipeline_th.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Thai sentiment_pipeline pipeline CamemBertForSequenceClassification from rudy-technology
+author: John Snow Labs
+name: sentiment_pipeline
+date: 2024-09-03
+tags: [th, open_source, pipeline, onnx]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_pipeline` is a Thai model originally trained by rudy-technology.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_pipeline_th_5.5.0_3.0_1725378318686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_pipeline_th_5.5.0_3.0_1725378318686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/rudy-technology/sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_sentiment_small_random3_seed2_bertweet_large_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_sentiment_small_random3_seed2_bertweet_large_en.md
new file mode 100644
index 00000000000000..2fc0c79c7cd261
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_sentiment_small_random3_seed2_bertweet_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_sentiment_small_random3_seed2_bertweet_large RoBertaForSequenceClassification from tweettemposhift
+author: John Snow Labs
+name: sentiment_sentiment_small_random3_seed2_bertweet_large
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_sentiment_small_random3_seed2_bertweet_large` is a English model originally trained by tweettemposhift.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_sentiment_small_random3_seed2_bertweet_large_en_5.5.0_3.0_1725369235076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_sentiment_small_random3_seed2_bertweet_large_en_5.5.0_3.0_1725369235076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("sentiment_sentiment_small_random3_seed2_bertweet_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("sentiment_sentiment_small_random3_seed2_bertweet_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_sentiment_small_random3_seed2_bertweet_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/tweettemposhift/sentiment-sentiment_small_random3_seed2-bertweet-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline_en.md
new file mode 100644
index 00000000000000..ff729f2cd6b4f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline pipeline RoBertaForSequenceClassification from tweettemposhift
+author: John Snow Labs
+name: sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline` is a English model originally trained by tweettemposhift.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline_en_5.5.0_3.0_1725369338333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline_en_5.5.0_3.0_1725369338333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_sentiment_small_random3_seed2_bertweet_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/tweettemposhift/sentiment-sentiment_small_random3_seed2-bertweet-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_th.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_th.md
new file mode 100644
index 00000000000000..b091335f683112
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_th.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Thai sentiment CamemBertForSequenceClassification from rudy-technology
+author: John Snow Labs
+name: sentiment
+date: 2024-09-03
+tags: [th, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment` is a Thai model originally trained by rudy-technology.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_th_5.5.0_3.0_1725378298030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_th_5.5.0_3.0_1725378298030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("sentiment","th") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sentiment", "th")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|th|
+|Size:|394.3 MB|
+
+## References
+
+https://huggingface.co/rudy-technology/sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-setfit_model_indepandance_epochs2_en.md b/docs/_posts/ahmedlone127/2024-09-03-setfit_model_indepandance_epochs2_en.md
new file mode 100644
index 00000000000000..4bb3298df1c3eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-setfit_model_indepandance_epochs2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English setfit_model_indepandance_epochs2 MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_indepandance_epochs2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_indepandance_epochs2` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_indepandance_epochs2_en_5.5.0_3.0_1725350604501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_indepandance_epochs2_en_5.5.0_3.0_1725350604501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("setfit_model_indepandance_epochs2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("setfit_model_indepandance_epochs2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_indepandance_epochs2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit_model_indepandance_epochs2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-setfit_model_indepandance_epochs2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-setfit_model_indepandance_epochs2_pipeline_en.md
new file mode 100644
index 00000000000000..08fe18f2d6c6cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-setfit_model_indepandance_epochs2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_model_indepandance_epochs2_pipeline pipeline MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_indepandance_epochs2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_indepandance_epochs2_pipeline` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_indepandance_epochs2_pipeline_en_5.5.0_3.0_1725350624809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_indepandance_epochs2_pipeline_en_5.5.0_3.0_1725350624809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("setfit_model_indepandance_epochs2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_model_indepandance_epochs2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_indepandance_epochs2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit_model_indepandance_epochs2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-setfittest_en.md b/docs/_posts/ahmedlone127/2024-09-03-setfittest_en.md
new file mode 100644
index 00000000000000..61eea886f170b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-setfittest_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English setfittest MPNetEmbeddings from scaperex
+author: John Snow Labs
+name: setfittest
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfittest` is a English model originally trained by scaperex.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfittest_en_5.5.0_3.0_1725350930723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfittest_en_5.5.0_3.0_1725350930723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("setfittest","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("setfittest","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfittest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/scaperex/SetFitTest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-setfittest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-setfittest_pipeline_en.md
new file mode 100644
index 00000000000000..1ab677bf4b56e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-setfittest_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfittest_pipeline pipeline MPNetEmbeddings from scaperex
+author: John Snow Labs
+name: setfittest_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfittest_pipeline` is a English model originally trained by scaperex.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfittest_pipeline_en_5.5.0_3.0_1725350951578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfittest_pipeline_en_5.5.0_3.0_1725350951578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("setfittest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfittest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfittest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/scaperex/SetFitTest
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-shanghainese_opus_chinese_serbocroatian_4000_en.md b/docs/_posts/ahmedlone127/2024-09-03-shanghainese_opus_chinese_serbocroatian_4000_en.md
new file mode 100644
index 00000000000000..f56163029c4dbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-shanghainese_opus_chinese_serbocroatian_4000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English shanghainese_opus_chinese_serbocroatian_4000 MarianTransformer from spycsh
+author: John Snow Labs
+name: shanghainese_opus_chinese_serbocroatian_4000
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shanghainese_opus_chinese_serbocroatian_4000` is a English model originally trained by spycsh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shanghainese_opus_chinese_serbocroatian_4000_en_5.5.0_3.0_1725346609988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shanghainese_opus_chinese_serbocroatian_4000_en_5.5.0_3.0_1725346609988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("shanghainese_opus_chinese_serbocroatian_4000","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("shanghainese_opus_chinese_serbocroatian_4000","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|shanghainese_opus_chinese_serbocroatian_4000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|540.1 MB|
+
+## References
+
+https://huggingface.co/spycsh/shanghainese-opus-zh-sh-4000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-singlelabelrecommendationmodel_en.md b/docs/_posts/ahmedlone127/2024-09-03-singlelabelrecommendationmodel_en.md
new file mode 100644
index 00000000000000..43661b281a334b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-singlelabelrecommendationmodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English singlelabelrecommendationmodel RoBertaForSequenceClassification from terrongraham
+author: John Snow Labs
+name: singlelabelrecommendationmodel
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`singlelabelrecommendationmodel` is a English model originally trained by terrongraham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/singlelabelrecommendationmodel_en_5.5.0_3.0_1725336712299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/singlelabelrecommendationmodel_en_5.5.0_3.0_1725336712299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("singlelabelrecommendationmodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("singlelabelrecommendationmodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|singlelabelrecommendationmodel|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|425.0 MB|
+
+## References
+
+https://huggingface.co/terrongraham/SingleLabelRecommendationModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sitexsometre_camembert_large_stsb100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sitexsometre_camembert_large_stsb100_pipeline_en.md
new file mode 100644
index 00000000000000..9421c063387e85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sitexsometre_camembert_large_stsb100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sitexsometre_camembert_large_stsb100_pipeline pipeline CamemBertForSequenceClassification from Kigo1974
+author: John Snow Labs
+name: sitexsometre_camembert_large_stsb100_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_large_stsb100_pipeline` is a English model originally trained by Kigo1974.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_large_stsb100_pipeline_en_5.5.0_3.0_1725378981807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_large_stsb100_pipeline_en_5.5.0_3.0_1725378981807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sitexsometre_camembert_large_stsb100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sitexsometre_camembert_large_stsb100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sitexsometre_camembert_large_stsb100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|805.5 MB|
+
+## References
+
+https://huggingface.co/Kigo1974/sitexsometre-camembert-large-stsb100
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-slovakbert_pipeline_sk.md b/docs/_posts/ahmedlone127/2024-09-03-slovakbert_pipeline_sk.md
new file mode 100644
index 00000000000000..5c2e462c3a092f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-slovakbert_pipeline_sk.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Slovak slovakbert_pipeline pipeline RoBertaEmbeddings from gerulata
+author: John Snow Labs
+name: slovakbert_pipeline
+date: 2024-09-03
+tags: [sk, open_source, pipeline, onnx]
+task: Embeddings
+language: sk
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovakbert_pipeline` is a Slovak model originally trained by gerulata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovakbert_pipeline_sk_5.5.0_3.0_1725375748181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovakbert_pipeline_sk_5.5.0_3.0_1725375748181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slovakbert_pipeline", lang = "sk")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slovakbert_pipeline", lang = "sk")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slovakbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sk|
+|Size:|296.1 MB|
+
+## References
+
+https://huggingface.co/gerulata/slovakbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-slovakbert_sk.md b/docs/_posts/ahmedlone127/2024-09-03-slovakbert_sk.md
new file mode 100644
index 00000000000000..97e3c8bec2df3d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-slovakbert_sk.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Slovak slovakbert RoBertaEmbeddings from gerulata
+author: John Snow Labs
+name: slovakbert
+date: 2024-09-03
+tags: [sk, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: sk
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovakbert` is a Slovak model originally trained by gerulata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovakbert_sk_5.5.0_3.0_1725375658891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovakbert_sk_5.5.0_3.0_1725375658891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("slovakbert","sk") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("slovakbert","sk") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slovakbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|sk|
+|Size:|296.1 MB|
+
+## References
+
+https://huggingface.co/gerulata/slovakbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-socbert_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-socbert_base_en.md
new file mode 100644
index 00000000000000..82e2f446c5a7c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-socbert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English socbert_base RoBertaEmbeddings from sarkerlab
+author: John Snow Labs
+name: socbert_base
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`socbert_base` is a English model originally trained by sarkerlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/socbert_base_en_5.5.0_3.0_1725374563255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/socbert_base_en_5.5.0_3.0_1725374563255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("socbert_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("socbert_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|socbert_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|533.8 MB|
+
+## References
+
+https://huggingface.co/sarkerlab/SocBERT-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-socbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-socbert_base_pipeline_en.md
new file mode 100644
index 00000000000000..0e6529d5ea2522
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-socbert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English socbert_base_pipeline pipeline RoBertaEmbeddings from sarkerlab
+author: John Snow Labs
+name: socbert_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`socbert_base_pipeline` is a English model originally trained by sarkerlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/socbert_base_pipeline_en_5.5.0_3.0_1725374591753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/socbert_base_pipeline_en_5.5.0_3.0_1725374591753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("socbert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("socbert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|socbert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|533.8 MB|
+
+## References
+
+https://huggingface.co/sarkerlab/SocBERT-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-soqbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-soqbert_pipeline_en.md
new file mode 100644
index 00000000000000..4aa56011ecbb76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-soqbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English soqbert_pipeline pipeline DistilBertForSequenceClassification from ilert
+author: John Snow Labs
+name: soqbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`soqbert_pipeline` is a English model originally trained by ilert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/soqbert_pipeline_en_5.5.0_3.0_1725329894453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/soqbert_pipeline_en_5.5.0_3.0_1725329894453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("soqbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("soqbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|soqbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ilert/SoQbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-southern_sotho_all_mpnet_finetuned_arabic_2000_en.md b/docs/_posts/ahmedlone127/2024-09-03-southern_sotho_all_mpnet_finetuned_arabic_2000_en.md
new file mode 100644
index 00000000000000..7b34c1d04ee6e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-southern_sotho_all_mpnet_finetuned_arabic_2000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_arabic_2000 MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_arabic_2000
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_arabic_2000` is a English model originally trained by danfeg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_2000_en_5.5.0_3.0_1725350587814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_2000_en_5.5.0_3.0_1725350587814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_arabic_2000","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_arabic_2000","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_arabic_2000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-AR-2000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline_en.md
new file mode 100644
index 00000000000000..c3bd8c423e56ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline pipeline MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline` is a English model originally trained by danfeg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline_en_5.5.0_3.0_1725350609495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline_en_5.5.0_3.0_1725350609495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_arabic_2000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-AR-2000
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-spoken_deberta_small_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-spoken_deberta_small_v2_en.md
new file mode 100644
index 00000000000000..a88d38d46ba6bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-spoken_deberta_small_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spoken_deberta_small_v2 DeBertaEmbeddings from viethq188
+author: John Snow Labs
+name: spoken_deberta_small_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, deberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spoken_deberta_small_v2` is a English model originally trained by viethq188.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spoken_deberta_small_v2_en_5.5.0_3.0_1725377395344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spoken_deberta_small_v2_en_5.5.0_3.0_1725377395344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("spoken_deberta_small_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("spoken_deberta_small_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spoken_deberta_small_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|en|
+|Size:|387.8 MB|
+
+## References
+
+https://huggingface.co/viethq188/spoken-deberta-small-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sql_injection_attack_detection_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sql_injection_attack_detection_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..fff5d9c7115283
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sql_injection_attack_detection_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sql_injection_attack_detection_distilbert_pipeline pipeline DistilBertForSequenceClassification from cybersectony
+author: John Snow Labs
+name: sql_injection_attack_detection_distilbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sql_injection_attack_detection_distilbert_pipeline` is a English model originally trained by cybersectony.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sql_injection_attack_detection_distilbert_pipeline_en_5.5.0_3.0_1725329794818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sql_injection_attack_detection_distilbert_pipeline_en_5.5.0_3.0_1725329794818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sql_injection_attack_detection_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sql_injection_attack_detection_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sql_injection_attack_detection_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cybersectony/sql-injection-attack-detection-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-squeezebert_uncased_finetuned_squad_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-squeezebert_uncased_finetuned_squad_v2_en.md
new file mode 100644
index 00000000000000..1c172e41132470
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-squeezebert_uncased_finetuned_squad_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English squeezebert_uncased_finetuned_squad_v2 BertForQuestionAnswering from ALOQAS
+author: John Snow Labs
+name: squeezebert_uncased_finetuned_squad_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squeezebert_uncased_finetuned_squad_v2` is a English model originally trained by ALOQAS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squeezebert_uncased_finetuned_squad_v2_en_5.5.0_3.0_1725352251422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squeezebert_uncased_finetuned_squad_v2_en_5.5.0_3.0_1725352251422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("squeezebert_uncased_finetuned_squad_v2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("squeezebert_uncased_finetuned_squad_v2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squeezebert_uncased_finetuned_squad_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|187.2 MB|
+
+## References
+
+https://huggingface.co/ALOQAS/squeezebert-uncased-finetuned-squad-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-standardized_e5_base_unsupervised_16_198009_en.md b/docs/_posts/ahmedlone127/2024-09-03-standardized_e5_base_unsupervised_16_198009_en.md
new file mode 100644
index 00000000000000..7d2ed525c2f48d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-standardized_e5_base_unsupervised_16_198009_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English standardized_e5_base_unsupervised_16_198009 E5Embeddings from rithwik-db
+author: John Snow Labs
+name: standardized_e5_base_unsupervised_16_198009
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`standardized_e5_base_unsupervised_16_198009` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/standardized_e5_base_unsupervised_16_198009_en_5.5.0_3.0_1725393099032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/standardized_e5_base_unsupervised_16_198009_en_5.5.0_3.0_1725393099032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("standardized_e5_base_unsupervised_16_198009","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("standardized_e5_base_unsupervised_16_198009","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|standardized_e5_base_unsupervised_16_198009|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|386.1 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/standardized-e5-base-unsupervised-16-198009
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-standardized_e5_base_unsupervised_16_198009_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-standardized_e5_base_unsupervised_16_198009_pipeline_en.md
new file mode 100644
index 00000000000000..912904e0ecbf0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-standardized_e5_base_unsupervised_16_198009_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English standardized_e5_base_unsupervised_16_198009_pipeline pipeline E5Embeddings from rithwik-db
+author: John Snow Labs
+name: standardized_e5_base_unsupervised_16_198009_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`standardized_e5_base_unsupervised_16_198009_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/standardized_e5_base_unsupervised_16_198009_pipeline_en_5.5.0_3.0_1725393127650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/standardized_e5_base_unsupervised_16_198009_pipeline_en_5.5.0_3.0_1725393127650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("standardized_e5_base_unsupervised_16_198009_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("standardized_e5_base_unsupervised_16_198009_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|standardized_e5_base_unsupervised_16_198009_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|386.1 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/standardized-e5-base-unsupervised-16-198009
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-student_marian_english_romanian_6_1_sshleifer_en.md b/docs/_posts/ahmedlone127/2024-09-03-student_marian_english_romanian_6_1_sshleifer_en.md
new file mode 100644
index 00000000000000..20090eee3ea2a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-student_marian_english_romanian_6_1_sshleifer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English student_marian_english_romanian_6_1_sshleifer MarianTransformer from sshleifer
+author: John Snow Labs
+name: student_marian_english_romanian_6_1_sshleifer
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`student_marian_english_romanian_6_1_sshleifer` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/student_marian_english_romanian_6_1_sshleifer_en_5.5.0_3.0_1725346158389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/student_marian_english_romanian_6_1_sshleifer_en_5.5.0_3.0_1725346158389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("student_marian_english_romanian_6_1_sshleifer","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("student_marian_english_romanian_6_1_sshleifer","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|student_marian_english_romanian_6_1_sshleifer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|271.4 MB|
+
+## References
+
+https://huggingface.co/sshleifer/student_marian_en_ro_6_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-student_marian_english_romanian_6_1_sshleifer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-student_marian_english_romanian_6_1_sshleifer_pipeline_en.md
new file mode 100644
index 00000000000000..400b5709832510
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-student_marian_english_romanian_6_1_sshleifer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English student_marian_english_romanian_6_1_sshleifer_pipeline pipeline MarianTransformer from sshleifer
+author: John Snow Labs
+name: student_marian_english_romanian_6_1_sshleifer_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`student_marian_english_romanian_6_1_sshleifer_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/student_marian_english_romanian_6_1_sshleifer_pipeline_en_5.5.0_3.0_1725346238234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/student_marian_english_romanian_6_1_sshleifer_pipeline_en_5.5.0_3.0_1725346238234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("student_marian_english_romanian_6_1_sshleifer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("student_marian_english_romanian_6_1_sshleifer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|student_marian_english_romanian_6_1_sshleifer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|272.0 MB|
+
+## References
+
+https://huggingface.co/sshleifer/student_marian_en_ro_6_1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-subsec_xlm_roberta_norwegian_catalan_galician_en.md b/docs/_posts/ahmedlone127/2024-09-03-subsec_xlm_roberta_norwegian_catalan_galician_en.md
new file mode 100644
index 00000000000000..15285b5ea9a273
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-subsec_xlm_roberta_norwegian_catalan_galician_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English subsec_xlm_roberta_norwegian_catalan_galician XlmRoBertaEmbeddings from homersimpson
+author: John Snow Labs
+name: subsec_xlm_roberta_norwegian_catalan_galician
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`subsec_xlm_roberta_norwegian_catalan_galician` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/subsec_xlm_roberta_norwegian_catalan_galician_en_5.5.0_3.0_1725354428111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/subsec_xlm_roberta_norwegian_catalan_galician_en_5.5.0_3.0_1725354428111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("subsec_xlm_roberta_norwegian_catalan_galician","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("subsec_xlm_roberta_norwegian_catalan_galician","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|subsec_xlm_roberta_norwegian_catalan_galician|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|642.5 MB|
+
+## References
+
+https://huggingface.co/homersimpson/subsec-xlm-roberta-no-ca-gl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en.md
new file mode 100644
index 00000000000000..c601b52dd52070
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English subsec_xlm_roberta_norwegian_catalan_galician_pipeline pipeline XlmRoBertaEmbeddings from homersimpson
+author: John Snow Labs
+name: subsec_xlm_roberta_norwegian_catalan_galician_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`subsec_xlm_roberta_norwegian_catalan_galician_pipeline` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en_5.5.0_3.0_1725354618113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en_5.5.0_3.0_1725354618113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("subsec_xlm_roberta_norwegian_catalan_galician_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("subsec_xlm_roberta_norwegian_catalan_galician_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|subsec_xlm_roberta_norwegian_catalan_galician_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|642.6 MB|
+
+## References
+
+https://huggingface.co/homersimpson/subsec-xlm-roberta-no-ca-gl
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sunbird_multiple_languages_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-sunbird_multiple_languages_english_en.md
new file mode 100644
index 00000000000000..e88844ffe7dfbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sunbird_multiple_languages_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sunbird_multiple_languages_english MarianTransformer from Sunbird
+author: John Snow Labs
+name: sunbird_multiple_languages_english
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sunbird_multiple_languages_english` is a English model originally trained by Sunbird.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sunbird_multiple_languages_english_en_5.5.0_3.0_1725404338649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sunbird_multiple_languages_english_en_5.5.0_3.0_1725404338649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("sunbird_multiple_languages_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("sunbird_multiple_languages_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sunbird_multiple_languages_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|532.1 MB|
+
+## References
+
+https://huggingface.co/Sunbird/sunbird-mul-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sunbird_multiple_languages_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sunbird_multiple_languages_english_pipeline_en.md
new file mode 100644
index 00000000000000..fc5498eb62e44c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sunbird_multiple_languages_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sunbird_multiple_languages_english_pipeline pipeline MarianTransformer from Sunbird
+author: John Snow Labs
+name: sunbird_multiple_languages_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sunbird_multiple_languages_english_pipeline` is a English model originally trained by Sunbird.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sunbird_multiple_languages_english_pipeline_en_5.5.0_3.0_1725404368514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sunbird_multiple_languages_english_pipeline_en_5.5.0_3.0_1725404368514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sunbird_multiple_languages_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sunbird_multiple_languages_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sunbird_multiple_languages_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|532.6 MB|
+
+## References
+
+https://huggingface.co/Sunbird/sunbird-mul-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-surgicberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-surgicberta_pipeline_en.md
new file mode 100644
index 00000000000000..717aebde67e95c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-surgicberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English surgicberta_pipeline pipeline RoBertaEmbeddings from marcobombieri
+author: John Snow Labs
+name: surgicberta_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`surgicberta_pipeline` is a English model originally trained by marcobombieri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/surgicberta_pipeline_en_5.5.0_3.0_1725374798461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/surgicberta_pipeline_en_5.5.0_3.0_1725374798461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("surgicberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("surgicberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|surgicberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/marcobombieri/surgicberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-swahili_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-swahili_english_pipeline_en.md
new file mode 100644
index 00000000000000..5668a41efc7661
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-swahili_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English swahili_english_pipeline pipeline MarianTransformer from Rogendo
+author: John Snow Labs
+name: swahili_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swahili_english_pipeline` is a English model originally trained by Rogendo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swahili_english_pipeline_en_5.5.0_3.0_1725347064089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swahili_english_pipeline_en_5.5.0_3.0_1725347064089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swahili_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swahili_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swahili_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.3 MB|
+
+## References
+
+https://huggingface.co/Rogendo/sw-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-takalane_northern_sotho_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-takalane_northern_sotho_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..434717cbd2bb58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-takalane_northern_sotho_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English takalane_northern_sotho_roberta_pipeline pipeline RoBertaEmbeddings from jannesg
+author: John Snow Labs
+name: takalane_northern_sotho_roberta_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`takalane_northern_sotho_roberta_pipeline` is a English model originally trained by jannesg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/takalane_northern_sotho_roberta_pipeline_en_5.5.0_3.0_1725381718941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/takalane_northern_sotho_roberta_pipeline_en_5.5.0_3.0_1725381718941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("takalane_northern_sotho_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("takalane_northern_sotho_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|takalane_northern_sotho_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|310.4 MB|
+
+## References
+
+https://huggingface.co/jannesg/takalane_nso_roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-takalane_tso_roberta_pipeline_ts.md b/docs/_posts/ahmedlone127/2024-09-03-takalane_tso_roberta_pipeline_ts.md
new file mode 100644
index 00000000000000..2a5a22b480f0b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-takalane_tso_roberta_pipeline_ts.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Tsonga takalane_tso_roberta_pipeline pipeline RoBertaEmbeddings from jannesg
+author: John Snow Labs
+name: takalane_tso_roberta_pipeline
+date: 2024-09-03
+tags: [ts, open_source, pipeline, onnx]
+task: Embeddings
+language: ts
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`takalane_tso_roberta_pipeline` is a Tsonga model originally trained by jannesg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/takalane_tso_roberta_pipeline_ts_5.5.0_3.0_1725381717542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/takalane_tso_roberta_pipeline_ts_5.5.0_3.0_1725381717542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("takalane_tso_roberta_pipeline", lang = "ts")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("takalane_tso_roberta_pipeline", lang = "ts")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|takalane_tso_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ts|
+|Size:|310.8 MB|
+
+## References
+
+https://huggingface.co/jannesg/takalane_tso_roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-takalane_tso_roberta_ts.md b/docs/_posts/ahmedlone127/2024-09-03-takalane_tso_roberta_ts.md
new file mode 100644
index 00000000000000..e52dbb10317584
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-takalane_tso_roberta_ts.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Tsonga takalane_tso_roberta RoBertaEmbeddings from jannesg
+author: John Snow Labs
+name: takalane_tso_roberta
+date: 2024-09-03
+tags: [ts, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: ts
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`takalane_tso_roberta` is a Tsonga model originally trained by jannesg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/takalane_tso_roberta_ts_5.5.0_3.0_1725381697852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/takalane_tso_roberta_ts_5.5.0_3.0_1725381697852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("takalane_tso_roberta","ts") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("takalane_tso_roberta","ts") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|takalane_tso_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|ts|
+|Size:|310.8 MB|
+
+## References
+
+https://huggingface.co/jannesg/takalane_tso_roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-telepathy_model_en.md b/docs/_posts/ahmedlone127/2024-09-03-telepathy_model_en.md
new file mode 100644
index 00000000000000..e7bb46981b7adf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-telepathy_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English telepathy_model AlbertForSequenceClassification from meghanamreddy
+author: John Snow Labs
+name: telepathy_model
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`telepathy_model` is a English model originally trained by meghanamreddy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/telepathy_model_en_5.5.0_3.0_1725386107562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/telepathy_model_en_5.5.0_3.0_1725386107562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("telepathy_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("telepathy_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|telepathy_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/meghanamreddy/telepathy_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-telepathy_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-telepathy_model_pipeline_en.md
new file mode 100644
index 00000000000000..3e7b4943ae34c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-telepathy_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English telepathy_model_pipeline pipeline AlbertForSequenceClassification from meghanamreddy
+author: John Snow Labs
+name: telepathy_model_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`telepathy_model_pipeline` is a English model originally trained by meghanamreddy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/telepathy_model_pipeline_en_5.5.0_3.0_1725386110039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/telepathy_model_pipeline_en_5.5.0_3.0_1725386110039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("telepathy_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("telepathy_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|telepathy_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/meghanamreddy/telepathy_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-terjman_large_v2_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-03-terjman_large_v2_pipeline_ar.md
new file mode 100644
index 00000000000000..f1ccdac0046743
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-terjman_large_v2_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic terjman_large_v2_pipeline pipeline MarianTransformer from atlasia
+author: John Snow Labs
+name: terjman_large_v2_pipeline
+date: 2024-09-03
+tags: [ar, open_source, pipeline, onnx]
+task: Translation
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`terjman_large_v2_pipeline` is a Arabic model originally trained by atlasia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/terjman_large_v2_pipeline_ar_5.5.0_3.0_1725346391687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/terjman_large_v2_pipeline_ar_5.5.0_3.0_1725346391687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("terjman_large_v2_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("terjman_large_v2_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|terjman_large_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|691.9 MB|
+
+## References
+
+https://huggingface.co/atlasia/Terjman-Large-v2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-test111_en.md b/docs/_posts/ahmedlone127/2024-09-03-test111_en.md
new file mode 100644
index 00000000000000..0ef89fcfdef86a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-test111_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test111 XlmRoBertaForQuestionAnswering from prajwalJumde
+author: John Snow Labs
+name: test111
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test111` is a English model originally trained by prajwalJumde.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test111_en_5.5.0_3.0_1725380931698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test111_en_5.5.0_3.0_1725380931698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("test111","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("test111", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test111|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|812.4 MB|
+
+## References
+
+https://huggingface.co/prajwalJumde/test111
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-test111_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-test111_pipeline_en.md
new file mode 100644
index 00000000000000..49062cb3db07fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-test111_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test111_pipeline pipeline XlmRoBertaForQuestionAnswering from prajwalJumde
+author: John Snow Labs
+name: test111_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test111_pipeline` is a English model originally trained by prajwalJumde.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test111_pipeline_en_5.5.0_3.0_1725381040650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test111_pipeline_en_5.5.0_3.0_1725381040650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test111_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test111_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test111_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|812.4 MB|
+
+## References
+
+https://huggingface.co/prajwalJumde/test111
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-test_ditilroberta_eli5_en.md b/docs/_posts/ahmedlone127/2024-09-03-test_ditilroberta_eli5_en.md
new file mode 100644
index 00000000000000..8f71d9caf06b4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-test_ditilroberta_eli5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_ditilroberta_eli5 RoBertaEmbeddings from 318h7
+author: John Snow Labs
+name: test_ditilroberta_eli5
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ditilroberta_eli5` is a English model originally trained by 318h7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ditilroberta_eli5_en_5.5.0_3.0_1725382567944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ditilroberta_eli5_en_5.5.0_3.0_1725382567944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("test_ditilroberta_eli5","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("test_ditilroberta_eli5","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ditilroberta_eli5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.4 MB|
+
+## References
+
+https://huggingface.co/318h7/test_ditilroberta_eli5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-test_ditilroberta_eli5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-test_ditilroberta_eli5_pipeline_en.md
new file mode 100644
index 00000000000000..781d1a80b4328a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-test_ditilroberta_eli5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_ditilroberta_eli5_pipeline pipeline RoBertaEmbeddings from 318h7
+author: John Snow Labs
+name: test_ditilroberta_eli5_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ditilroberta_eli5_pipeline` is a English model originally trained by 318h7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ditilroberta_eli5_pipeline_en_5.5.0_3.0_1725382584921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ditilroberta_eli5_pipeline_en_5.5.0_3.0_1725382584921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_ditilroberta_eli5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_ditilroberta_eli5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ditilroberta_eli5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/318h7/test_ditilroberta_eli5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-text_comp_en.md b/docs/_posts/ahmedlone127/2024-09-03-text_comp_en.md
new file mode 100644
index 00000000000000..578e45eb181430
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-text_comp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English text_comp RoBertaForSequenceClassification from isanchez
+author: John Snow Labs
+name: text_comp
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_comp` is a English model originally trained by isanchez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_comp_en_5.5.0_3.0_1725402708601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_comp_en_5.5.0_3.0_1725402708601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("text_comp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("text_comp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_comp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/isanchez/text-comp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-text_comp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-text_comp_pipeline_en.md
new file mode 100644
index 00000000000000..7e89d28513c0d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-text_comp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English text_comp_pipeline pipeline RoBertaForSequenceClassification from isanchez
+author: John Snow Labs
+name: text_comp_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_comp_pipeline` is a English model originally trained by isanchez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_comp_pipeline_en_5.5.0_3.0_1725402728696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_comp_pipeline_en_5.5.0_3.0_1725402728696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text_comp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_comp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_comp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/isanchez/text-comp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-thaig2p_v2_0_pipeline_th.md b/docs/_posts/ahmedlone127/2024-09-03-thaig2p_v2_0_pipeline_th.md
new file mode 100644
index 00000000000000..177edf375e5e62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-thaig2p_v2_0_pipeline_th.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Thai thaig2p_v2_0_pipeline pipeline MarianTransformer from pythainlp
+author: John Snow Labs
+name: thaig2p_v2_0_pipeline
+date: 2024-09-03
+tags: [th, open_source, pipeline, onnx]
+task: Translation
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thaig2p_v2_0_pipeline` is a Thai model originally trained by pythainlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thaig2p_v2_0_pipeline_th_5.5.0_3.0_1725405175634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thaig2p_v2_0_pipeline_th_5.5.0_3.0_1725405175634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("thaig2p_v2_0_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("thaig2p_v2_0_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|thaig2p_v2_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|196.9 MB|
+
+## References
+
+https://huggingface.co/pythainlp/thaig2p-v2.0
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-thaig2p_v2_0_th.md b/docs/_posts/ahmedlone127/2024-09-03-thaig2p_v2_0_th.md
new file mode 100644
index 00000000000000..e603fd4d4bc144
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-thaig2p_v2_0_th.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Thai thaig2p_v2_0 MarianTransformer from pythainlp
+author: John Snow Labs
+name: thaig2p_v2_0
+date: 2024-09-03
+tags: [th, open_source, onnx, translation, marian]
+task: Translation
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thaig2p_v2_0` is a Thai model originally trained by pythainlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thaig2p_v2_0_th_5.5.0_3.0_1725405165261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thaig2p_v2_0_th_5.5.0_3.0_1725405165261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("thaig2p_v2_0","th") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("thaig2p_v2_0","th") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|thaig2p_v2_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|th|
+|Size:|196.3 MB|
+
+## References
+
+https://huggingface.co/pythainlp/thaig2p-v2.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tiny_random_debertaforquestionanswering_ydshieh_en.md b/docs/_posts/ahmedlone127/2024-09-03-tiny_random_debertaforquestionanswering_ydshieh_en.md
new file mode 100644
index 00000000000000..b76591482ca2dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tiny_random_debertaforquestionanswering_ydshieh_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tiny_random_debertaforquestionanswering_ydshieh BertForQuestionAnswering from ydshieh
+author: John Snow Labs
+name: tiny_random_debertaforquestionanswering_ydshieh
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_debertaforquestionanswering_ydshieh` is a English model originally trained by ydshieh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_debertaforquestionanswering_ydshieh_en_5.5.0_3.0_1725351599471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_debertaforquestionanswering_ydshieh_en_5.5.0_3.0_1725351599471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("tiny_random_debertaforquestionanswering_ydshieh","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("tiny_random_debertaforquestionanswering_ydshieh", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_random_debertaforquestionanswering_ydshieh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|339.9 KB|
+
+## References
+
+https://huggingface.co/ydshieh/tiny-random-DebertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tiny_random_debertaforquestionanswering_ydshieh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-tiny_random_debertaforquestionanswering_ydshieh_pipeline_en.md
new file mode 100644
index 00000000000000..db421f03e15ab2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tiny_random_debertaforquestionanswering_ydshieh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tiny_random_debertaforquestionanswering_ydshieh_pipeline pipeline BertForQuestionAnswering from ydshieh
+author: John Snow Labs
+name: tiny_random_debertaforquestionanswering_ydshieh_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_debertaforquestionanswering_ydshieh_pipeline` is a English model originally trained by ydshieh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_debertaforquestionanswering_ydshieh_pipeline_en_5.5.0_3.0_1725351599846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_debertaforquestionanswering_ydshieh_pipeline_en_5.5.0_3.0_1725351599846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tiny_random_debertaforquestionanswering_ydshieh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tiny_random_debertaforquestionanswering_ydshieh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_random_debertaforquestionanswering_ydshieh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|346.4 KB|
+
+## References
+
+https://huggingface.co/ydshieh/tiny-random-DebertaForQuestionAnswering
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_en.md b/docs/_posts/ahmedlone127/2024-09-03-tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_en.md
new file mode 100644
index 00000000000000..d3ab7b4d47e6b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized XlmRoBertaForTokenClassification from anonymoussubmissions
+author: John Snow Labs
+name: tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized` is a English model originally trained by anonymoussubmissions.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_en_5.5.0_3.0_1725323183209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized_en_5.5.0_3.0_1725323183209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tner_xlm_roberta_base_ontonotes5_switchboard_non_normalized_and_normalized|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|859.3 MB|
+
+## References
+
+https://huggingface.co/anonymoussubmissions/tner-xlm-roberta-base-ontonotes5-switchboard-non-normalized-and-normalized
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tod_xlmr_en.md b/docs/_posts/ahmedlone127/2024-09-03-tod_xlmr_en.md
new file mode 100644
index 00000000000000..95e9d5bbc30700
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tod_xlmr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tod_xlmr XlmRoBertaEmbeddings from umanlp
+author: John Snow Labs
+name: tod_xlmr
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tod_xlmr` is a English model originally trained by umanlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tod_xlmr_en_5.5.0_3.0_1725390956649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tod_xlmr_en_5.5.0_3.0_1725390956649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("tod_xlmr","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("tod_xlmr","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tod_xlmr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/umanlp/TOD-XLMR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tod_xlmr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-tod_xlmr_pipeline_en.md
new file mode 100644
index 00000000000000..6be060810ce4ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tod_xlmr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tod_xlmr_pipeline pipeline XlmRoBertaEmbeddings from umanlp
+author: John Snow Labs
+name: tod_xlmr_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tod_xlmr_pipeline` is a English model originally trained by umanlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tod_xlmr_pipeline_en_5.5.0_3.0_1725391011099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tod_xlmr_pipeline_en_5.5.0_3.0_1725391011099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tod_xlmr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tod_xlmr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tod_xlmr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/umanlp/TOD-XLMR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tokenizerlabeller_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-tokenizerlabeller_pipeline_en.md
new file mode 100644
index 00000000000000..76d2e545dffb2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tokenizerlabeller_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tokenizerlabeller_pipeline pipeline MarianTransformer from guymorlan
+author: John Snow Labs
+name: tokenizerlabeller_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tokenizerlabeller_pipeline` is a English model originally trained by guymorlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tokenizerlabeller_pipeline_en_5.5.0_3.0_1725405082481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tokenizerlabeller_pipeline_en_5.5.0_3.0_1725405082481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tokenizerlabeller_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tokenizerlabeller_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tokenizerlabeller_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|533.1 MB|
+
+## References
+
+https://huggingface.co/guymorlan/TokenizerLabeller
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-topic_obits_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-topic_obits_pipeline_en.md
new file mode 100644
index 00000000000000..737e50c2bf4aad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-topic_obits_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English topic_obits_pipeline pipeline RoBertaForSequenceClassification from dell-research-harvard
+author: John Snow Labs
+name: topic_obits_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_obits_pipeline` is a English model originally trained by dell-research-harvard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topic_obits_pipeline_en_5.5.0_3.0_1725402994271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_obits_pipeline_en_5.5.0_3.0_1725402994271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("topic_obits_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("topic_obits_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_obits_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.1 MB|
+
+## References
+
+https://huggingface.co/dell-research-harvard/topic-obits
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-topic_politics_en.md b/docs/_posts/ahmedlone127/2024-09-03-topic_politics_en.md
new file mode 100644
index 00000000000000..db96d05025eb84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-topic_politics_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English topic_politics RoBertaForSequenceClassification from dell-research-harvard
+author: John Snow Labs
+name: topic_politics
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_politics` is a English model originally trained by dell-research-harvard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topic_politics_en_5.5.0_3.0_1725369126593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_politics_en_5.5.0_3.0_1725369126593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("topic_politics","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("topic_politics", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_politics|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/dell-research-harvard/topic-politics
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tosroberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-tosroberta_base_en.md
new file mode 100644
index 00000000000000..eb6edf6477b0ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tosroberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tosroberta_base RoBertaForSequenceClassification from CodeHima
+author: John Snow Labs
+name: tosroberta_base
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tosroberta_base` is a English model originally trained by CodeHima.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tosroberta_base_en_5.5.0_3.0_1725369849953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tosroberta_base_en_5.5.0_3.0_1725369849953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("tosroberta_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("tosroberta_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tosroberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|429.8 MB|
+
+## References
+
+https://huggingface.co/CodeHima/TOSRoberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tosrobertav2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-tosrobertav2_pipeline_en.md
new file mode 100644
index 00000000000000..f37d778189dc95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tosrobertav2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tosrobertav2_pipeline pipeline RoBertaForSequenceClassification from CodeHima
+author: John Snow Labs
+name: tosrobertav2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tosrobertav2_pipeline` is a English model originally trained by CodeHima.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tosrobertav2_pipeline_en_5.5.0_3.0_1725336747953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tosrobertav2_pipeline_en_5.5.0_3.0_1725336747953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tosrobertav2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tosrobertav2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tosrobertav2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CodeHima/TOSRobertaV2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-trained_model_distilbert_0305_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-trained_model_distilbert_0305_pipeline_en.md
new file mode 100644
index 00000000000000..532fd8bba877a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-trained_model_distilbert_0305_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trained_model_distilbert_0305_pipeline pipeline DistilBertForSequenceClassification from sciencedata
+author: John Snow Labs
+name: trained_model_distilbert_0305_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_model_distilbert_0305_pipeline` is a English model originally trained by sciencedata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_model_distilbert_0305_pipeline_en_5.5.0_3.0_1725330160928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_model_distilbert_0305_pipeline_en_5.5.0_3.0_1725330160928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trained_model_distilbert_0305_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trained_model_distilbert_0305_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_model_distilbert_0305_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sciencedata/trained_model_distilbert_0305
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-transformer_en.md b/docs/_posts/ahmedlone127/2024-09-03-transformer_en.md
new file mode 100644
index 00000000000000..c8c717b5ca6285
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-transformer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English transformer MPNetEmbeddings from kpourdeilami
+author: John Snow Labs
+name: transformer
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transformer` is a English model originally trained by kpourdeilami.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transformer_en_5.5.0_3.0_1725350474031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transformer_en_5.5.0_3.0_1725350474031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("transformer","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("transformer","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transformer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/kpourdeilami/transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-transformer_english_russian_under_tree_en.md b/docs/_posts/ahmedlone127/2024-09-03-transformer_english_russian_under_tree_en.md
new file mode 100644
index 00000000000000..e0b67807d8b5bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-transformer_english_russian_under_tree_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English transformer_english_russian_under_tree MarianTransformer from under-tree
+author: John Snow Labs
+name: transformer_english_russian_under_tree
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transformer_english_russian_under_tree` is a English model originally trained by under-tree.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transformer_english_russian_under_tree_en_5.5.0_3.0_1725405301045.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transformer_english_russian_under_tree_en_5.5.0_3.0_1725405301045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("transformer_english_russian_under_tree","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("transformer_english_russian_under_tree","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transformer_english_russian_under_tree|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|525.4 MB|
+
+## References
+
+https://huggingface.co/under-tree/transformer-en-ru
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-transformer_english_russian_under_tree_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-transformer_english_russian_under_tree_pipeline_en.md
new file mode 100644
index 00000000000000..a6c190f54aa52f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-transformer_english_russian_under_tree_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English transformer_english_russian_under_tree_pipeline pipeline MarianTransformer from under-tree
+author: John Snow Labs
+name: transformer_english_russian_under_tree_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transformer_english_russian_under_tree_pipeline` is a English model originally trained by under-tree.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transformer_english_russian_under_tree_pipeline_en_5.5.0_3.0_1725405329396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transformer_english_russian_under_tree_pipeline_en_5.5.0_3.0_1725405329396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("transformer_english_russian_under_tree_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("transformer_english_russian_under_tree_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transformer_english_russian_under_tree_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|526.0 MB|
+
+## References
+
+https://huggingface.co/under-tree/transformer-en-ru
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-translation_finetuned_english_tonga_tonga_islands_jp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-translation_finetuned_english_tonga_tonga_islands_jp_pipeline_en.md
new file mode 100644
index 00000000000000..a9d39dcb43de8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-translation_finetuned_english_tonga_tonga_islands_jp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English translation_finetuned_english_tonga_tonga_islands_jp_pipeline pipeline MarianTransformer from ldh243
+author: John Snow Labs
+name: translation_finetuned_english_tonga_tonga_islands_jp_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_finetuned_english_tonga_tonga_islands_jp_pipeline` is a English model originally trained by ldh243.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_finetuned_english_tonga_tonga_islands_jp_pipeline_en_5.5.0_3.0_1725404628002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_finetuned_english_tonga_tonga_islands_jp_pipeline_en_5.5.0_3.0_1725404628002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("translation_finetuned_english_tonga_tonga_islands_jp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translation_finetuned_english_tonga_tonga_islands_jp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_finetuned_english_tonga_tonga_islands_jp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|431.2 MB|
+
+## References
+
+https://huggingface.co/ldh243/translation-finetuned-en-to-jp
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-translation_for_recipes_french_english_fr.md b/docs/_posts/ahmedlone127/2024-09-03-translation_for_recipes_french_english_fr.md
new file mode 100644
index 00000000000000..6a20b5b162df92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-translation_for_recipes_french_english_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French translation_for_recipes_french_english MarianTransformer from PaulineSanchez
+author: John Snow Labs
+name: translation_for_recipes_french_english
+date: 2024-09-03
+tags: [fr, open_source, onnx, translation, marian]
+task: Translation
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_for_recipes_french_english` is a French model originally trained by PaulineSanchez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_for_recipes_french_english_fr_5.5.0_3.0_1725404960365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_for_recipes_french_english_fr_5.5.0_3.0_1725404960365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translation_for_recipes_french_english","fr") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translation_for_recipes_french_english","fr") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_for_recipes_french_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|fr|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/PaulineSanchez/translation_for_recipes_fr_en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-translation_for_recipes_french_english_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-03-translation_for_recipes_french_english_pipeline_fr.md
new file mode 100644
index 00000000000000..558198d0ef8575
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-translation_for_recipes_french_english_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French translation_for_recipes_french_english_pipeline pipeline MarianTransformer from PaulineSanchez
+author: John Snow Labs
+name: translation_for_recipes_french_english_pipeline
+date: 2024-09-03
+tags: [fr, open_source, pipeline, onnx]
+task: Translation
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_for_recipes_french_english_pipeline` is a French model originally trained by PaulineSanchez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_for_recipes_french_english_pipeline_fr_5.5.0_3.0_1725404994160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_for_recipes_french_english_pipeline_fr_5.5.0_3.0_1725404994160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("translation_for_recipes_french_english_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translation_for_recipes_french_english_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_for_recipes_french_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/PaulineSanchez/translation_for_recipes_fr_en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-translit_ppa_northern_sami_asian_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-translit_ppa_northern_sami_asian_pipeline_xx.md
new file mode 100644
index 00000000000000..722c7a50bec666
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-translit_ppa_northern_sami_asian_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual translit_ppa_northern_sami_asian_pipeline pipeline XlmRoBertaEmbeddings from orxhelili
+author: John Snow Labs
+name: translit_ppa_northern_sami_asian_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translit_ppa_northern_sami_asian_pipeline` is a Multilingual model originally trained by orxhelili.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translit_ppa_northern_sami_asian_pipeline_xx_5.5.0_3.0_1725399541169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translit_ppa_northern_sami_asian_pipeline_xx_5.5.0_3.0_1725399541169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("translit_ppa_northern_sami_asian_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translit_ppa_northern_sami_asian_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translit_ppa_northern_sami_asian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/orxhelili/translit_ppa_se_asian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-translit_ppa_northern_sami_asian_xx.md b/docs/_posts/ahmedlone127/2024-09-03-translit_ppa_northern_sami_asian_xx.md
new file mode 100644
index 00000000000000..b5e51f9ebc180a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-translit_ppa_northern_sami_asian_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual translit_ppa_northern_sami_asian XlmRoBertaEmbeddings from orxhelili
+author: John Snow Labs
+name: translit_ppa_northern_sami_asian
+date: 2024-09-03
+tags: [xx, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translit_ppa_northern_sami_asian` is a Multilingual model originally trained by orxhelili.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translit_ppa_northern_sami_asian_xx_5.5.0_3.0_1725399463688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translit_ppa_northern_sami_asian_xx_5.5.0_3.0_1725399463688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("translit_ppa_northern_sami_asian","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("translit_ppa_northern_sami_asian","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translit_ppa_northern_sami_asian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|xx|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/orxhelili/translit_ppa_se_asian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-transmodel_arabic_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-transmodel_arabic_english_pipeline_en.md
new file mode 100644
index 00000000000000..ea9aa66739f360
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-transmodel_arabic_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English transmodel_arabic_english_pipeline pipeline MarianTransformer from sofianch
+author: John Snow Labs
+name: transmodel_arabic_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transmodel_arabic_english_pipeline` is a English model originally trained by sofianch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transmodel_arabic_english_pipeline_en_5.5.0_3.0_1725346941388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transmodel_arabic_english_pipeline_en_5.5.0_3.0_1725346941388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("transmodel_arabic_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("transmodel_arabic_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transmodel_arabic_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.4 MB|
+
+## References
+
+https://huggingface.co/sofianch/TransModel_ar_en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_2183ce_3be9a5_en.md b/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_2183ce_3be9a5_en.md
new file mode 100644
index 00000000000000..75fa93c9100ae0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-triplets_e5_base_500_2183ce_3be9a5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English triplets_e5_base_500_2183ce_3be9a5 E5Embeddings from rithwik-db
+author: John Snow Labs
+name: triplets_e5_base_500_2183ce_3be9a5
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`triplets_e5_base_500_2183ce_3be9a5` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/triplets_e5_base_500_2183ce_3be9a5_en_5.5.0_3.0_1725332280413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/triplets_e5_base_500_2183ce_3be9a5_en_5.5.0_3.0_1725332280413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("triplets_e5_base_500_2183ce_3be9a5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("triplets_e5_base_500_2183ce_3be9a5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|triplets_e5_base_500_2183ce_3be9a5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|386.6 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/triplets-e5-base-500-2183ce-3be9a5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tst_tfm_stm_pp_pipeline_th.md b/docs/_posts/ahmedlone127/2024-09-03-tst_tfm_stm_pp_pipeline_th.md
new file mode 100644
index 00000000000000..0cf2672dcb5e4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tst_tfm_stm_pp_pipeline_th.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Thai tst_tfm_stm_pp_pipeline pipeline CamemBertForSequenceClassification from Ppxndpxdd
+author: John Snow Labs
+name: tst_tfm_stm_pp_pipeline
+date: 2024-09-03
+tags: [th, open_source, pipeline, onnx]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tst_tfm_stm_pp_pipeline` is a Thai model originally trained by Ppxndpxdd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tst_tfm_stm_pp_pipeline_th_5.5.0_3.0_1725325286508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tst_tfm_stm_pp_pipeline_th_5.5.0_3.0_1725325286508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tst_tfm_stm_pp_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tst_tfm_stm_pp_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tst_tfm_stm_pp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/Ppxndpxdd/tst_tfm_stm_pp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tttt_en.md b/docs/_posts/ahmedlone127/2024-09-03-tttt_en.md
new file mode 100644
index 00000000000000..1c41755d7ac94f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tttt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tttt MarianTransformer from andrejaystevenson
+author: John Snow Labs
+name: tttt
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tttt` is a English model originally trained by andrejaystevenson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tttt_en_5.5.0_3.0_1725404282319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tttt_en_5.5.0_3.0_1725404282319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("tttt","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("tttt","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tttt|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|330.1 MB|
+
+## References
+
+https://huggingface.co/andrejaystevenson/tttt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tttt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-tttt_pipeline_en.md
new file mode 100644
index 00000000000000..996fd4974ee317
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tttt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tttt_pipeline pipeline MarianTransformer from andrejaystevenson
+author: John Snow Labs
+name: tttt_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tttt_pipeline` is a English model originally trained by andrejaystevenson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tttt_pipeline_en_5.5.0_3.0_1725404379997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tttt_pipeline_en_5.5.0_3.0_1725404379997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tttt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tttt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tttt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|330.6 MB|
+
+## References
+
+https://huggingface.co/andrejaystevenson/tttt
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-turkish_tonga_tonga_islands_english_finetuned_model_en.md b/docs/_posts/ahmedlone127/2024-09-03-turkish_tonga_tonga_islands_english_finetuned_model_en.md
new file mode 100644
index 00000000000000..0f52db2ab88a0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-turkish_tonga_tonga_islands_english_finetuned_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English turkish_tonga_tonga_islands_english_finetuned_model MarianTransformer from ckartal
+author: John Snow Labs
+name: turkish_tonga_tonga_islands_english_finetuned_model
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_tonga_tonga_islands_english_finetuned_model` is a English model originally trained by ckartal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_tonga_tonga_islands_english_finetuned_model_en_5.5.0_3.0_1725346854047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_tonga_tonga_islands_english_finetuned_model_en_5.5.0_3.0_1725346854047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("turkish_tonga_tonga_islands_english_finetuned_model","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("turkish_tonga_tonga_islands_english_finetuned_model","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_tonga_tonga_islands_english_finetuned_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|525.3 MB|
+
+## References
+
+https://huggingface.co/ckartal/turkish-to-english-finetuned-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-turkishbertweet_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-03-turkishbertweet_pipeline_tr.md
new file mode 100644
index 00000000000000..ab7954e4a747d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-turkishbertweet_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish turkishbertweet_pipeline pipeline RoBertaEmbeddings from VRLLab
+author: John Snow Labs
+name: turkishbertweet_pipeline
+date: 2024-09-03
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkishbertweet_pipeline` is a Turkish model originally trained by VRLLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkishbertweet_pipeline_tr_5.5.0_3.0_1725375192955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkishbertweet_pipeline_tr_5.5.0_3.0_1725375192955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkishbertweet_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkishbertweet_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkishbertweet_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|606.1 MB|
+
+## References
+
+https://huggingface.co/VRLLab/TurkishBERTweet
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-turkishbertweet_tr.md b/docs/_posts/ahmedlone127/2024-09-03-turkishbertweet_tr.md
new file mode 100644
index 00000000000000..369fa682c9c0d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-turkishbertweet_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish turkishbertweet RoBertaEmbeddings from VRLLab
+author: John Snow Labs
+name: turkishbertweet
+date: 2024-09-03
+tags: [tr, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkishbertweet` is a Turkish model originally trained by VRLLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkishbertweet_tr_5.5.0_3.0_1725375159458.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkishbertweet_tr_5.5.0_3.0_1725375159458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("turkishbertweet","tr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("turkishbertweet","tr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkishbertweet|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|tr|
+|Size:|606.1 MB|
+
+## References
+
+https://huggingface.co/VRLLab/TurkishBERTweet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tweetner_en.md b/docs/_posts/ahmedlone127/2024-09-03-tweetner_en.md
new file mode 100644
index 00000000000000..0ed7139b220aa2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tweetner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tweetner RoBertaForTokenClassification from ivanresh
+author: John Snow Labs
+name: tweetner
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweetner` is a English model originally trained by ivanresh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweetner_en_5.5.0_3.0_1725384123414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweetner_en_5.5.0_3.0_1725384123414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("tweetner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("tweetner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweetner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ivanresh/TweetNer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-tweetner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-tweetner_pipeline_en.md
new file mode 100644
index 00000000000000..679ead88c2cd08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-tweetner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tweetner_pipeline pipeline RoBertaForTokenClassification from ivanresh
+author: John Snow Labs
+name: tweetner_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweetner_pipeline` is a English model originally trained by ivanresh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweetner_pipeline_en_5.5.0_3.0_1725384210694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweetner_pipeline_en_5.5.0_3.0_1725384210694.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tweetner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tweetner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweetner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ivanresh/TweetNer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_2022_154m_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_2022_154m_en.md
new file mode 100644
index 00000000000000..533ee353673979
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_2022_154m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_2022_154m RoBertaEmbeddings from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_2022_154m
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_2022_154m` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_2022_154m_en_5.5.0_3.0_1725375073316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_2022_154m_en_5.5.0_3.0_1725375073316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_2022_154m","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_2022_154m","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_2022_154m|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-2022-154m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_2022_154m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_2022_154m_pipeline_en.md
new file mode 100644
index 00000000000000..76b8ddf1229deb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_2022_154m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_2022_154m_pipeline pipeline RoBertaEmbeddings from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_2022_154m_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_2022_154m_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_2022_154m_pipeline_en_5.5.0_3.0_1725375097900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_2022_154m_pipeline_en_5.5.0_3.0_1725375097900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_base_2022_154m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_2022_154m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_2022_154m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-2022-154m
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline_en.md
new file mode 100644
index 00000000000000..caf12d15dbafaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline_en_5.5.0_3.0_1725403201988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline_en_5.5.0_3.0_1725403201988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_dec2020_tweet_topic_multi_2020_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.4 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-dec2020-tweet-topic-multi-2020
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_dec2021_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_dec2021_pipeline_en.md
new file mode 100644
index 00000000000000..970631c2ba948e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_dec2021_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_dec2021_pipeline pipeline RoBertaEmbeddings from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_dec2021_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_dec2021_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_dec2021_pipeline_en_5.5.0_3.0_1725382628748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_dec2021_pipeline_en_5.5.0_3.0_1725382628748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_base_dec2021_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_dec2021_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_dec2021_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-dec2021
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_emotion_latest_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_emotion_latest_en.md
new file mode 100644
index 00000000000000..7e6200435e05c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_emotion_latest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_emotion_latest RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_emotion_latest
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_emotion_latest` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emotion_latest_en_5.5.0_3.0_1725369929369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emotion_latest_en_5.5.0_3.0_1725369929369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_emotion_latest","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_emotion_latest", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_emotion_latest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-emotion-latest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_emotion_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_emotion_latest_pipeline_en.md
new file mode 100644
index 00000000000000..a8335e91c73656
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_emotion_latest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_emotion_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_emotion_latest_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_emotion_latest_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emotion_latest_pipeline_en_5.5.0_3.0_1725369955397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emotion_latest_pipeline_en_5.5.0_3.0_1725369955397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_base_emotion_latest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_emotion_latest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_emotion_latest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-emotion-latest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_sentiment_kapiche_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_sentiment_kapiche_pipeline_en.md
new file mode 100644
index 00000000000000..b61c2929d80d34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_sentiment_kapiche_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_sentiment_kapiche_pipeline pipeline RoBertaForSequenceClassification from Kapiche
+author: John Snow Labs
+name: twitter_roberta_base_sentiment_kapiche_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_sentiment_kapiche_pipeline` is a English model originally trained by Kapiche.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_sentiment_kapiche_pipeline_en_5.5.0_3.0_1725368657510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_sentiment_kapiche_pipeline_en_5.5.0_3.0_1725368657510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_base_sentiment_kapiche_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_sentiment_kapiche_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_sentiment_kapiche_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+https://huggingface.co/Kapiche/twitter-roberta-base-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_sep2020_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_sep2020_en.md
new file mode 100644
index 00000000000000..8b4f3a24a1a099
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_sep2020_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_sep2020 RoBertaEmbeddings from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_sep2020
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_sep2020` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_sep2020_en_5.5.0_3.0_1725382204015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_sep2020_en_5.5.0_3.0_1725382204015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_sep2020","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_sep2020","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_sep2020|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-sep2020
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_topic_sentiment_latest_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_topic_sentiment_latest_en.md
new file mode 100644
index 00000000000000..d98ce598e3c995
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_roberta_base_topic_sentiment_latest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_topic_sentiment_latest RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_topic_sentiment_latest
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_topic_sentiment_latest` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_topic_sentiment_latest_en_5.5.0_3.0_1725402147611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_topic_sentiment_latest_en_5.5.0_3.0_1725402147611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_topic_sentiment_latest","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_topic_sentiment_latest", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_topic_sentiment_latest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.1 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-topic-sentiment-latest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_sentiment_analysis_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_sentiment_analysis_v2_en.md
new file mode 100644
index 00000000000000..c8d460156d199b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_sentiment_analysis_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_sentiment_analysis_v2 DistilBertForSequenceClassification from mliamsinclair
+author: John Snow Labs
+name: twitter_sentiment_analysis_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_sentiment_analysis_v2` is a English model originally trained by mliamsinclair.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_sentiment_analysis_v2_en_5.5.0_3.0_1725394040244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_sentiment_analysis_v2_en_5.5.0_3.0_1725394040244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("twitter_sentiment_analysis_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("twitter_sentiment_analysis_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_sentiment_analysis_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mliamsinclair/twitter-sentiment-analysis-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_xlm_roberta_base_sentiment_multilingual_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_xlm_roberta_base_sentiment_multilingual_pipeline_xx.md
new file mode 100644
index 00000000000000..b6ab75673a2bb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_xlm_roberta_base_sentiment_multilingual_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual twitter_xlm_roberta_base_sentiment_multilingual_pipeline pipeline XlmRoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_multilingual_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_multilingual_pipeline` is a Multilingual model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_multilingual_pipeline_xx_5.5.0_3.0_1725396865723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_multilingual_pipeline_xx_5.5.0_3.0_1725396865723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_xlm_roberta_base_sentiment_multilingual_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_xlm_roberta_base_sentiment_multilingual_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_multilingual_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-twitter_xlm_roberta_base_sentiment_multilingual_xx.md b/docs/_posts/ahmedlone127/2024-09-03-twitter_xlm_roberta_base_sentiment_multilingual_xx.md
new file mode 100644
index 00000000000000..59618a4450ab98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-twitter_xlm_roberta_base_sentiment_multilingual_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual twitter_xlm_roberta_base_sentiment_multilingual XlmRoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_multilingual
+date: 2024-09-03
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_multilingual` is a Multilingual model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_multilingual_xx_5.5.0_3.0_1725396811567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_multilingual_xx_5.5.0_3.0_1725396811567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_multilingual","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_multilingual", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_multilingual|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-umberto_fine_tuned_hate_offensivity_en.md b/docs/_posts/ahmedlone127/2024-09-03-umberto_fine_tuned_hate_offensivity_en.md
new file mode 100644
index 00000000000000..4437f7c45e53bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-umberto_fine_tuned_hate_offensivity_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English umberto_fine_tuned_hate_offensivity CamemBertForSequenceClassification from lupobricco
+author: John Snow Labs
+name: umberto_fine_tuned_hate_offensivity
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`umberto_fine_tuned_hate_offensivity` is a English model originally trained by lupobricco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/umberto_fine_tuned_hate_offensivity_en_5.5.0_3.0_1725378637721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/umberto_fine_tuned_hate_offensivity_en_5.5.0_3.0_1725378637721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("umberto_fine_tuned_hate_offensivity","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("umberto_fine_tuned_hate_offensivity", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|umberto_fine_tuned_hate_offensivity|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|392.8 MB|
+
+## References
+
+https://huggingface.co/lupobricco/umBERTo_fine-tuned_hate_offensivity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-umberto_fine_tuned_hate_offensivity_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-umberto_fine_tuned_hate_offensivity_pipeline_en.md
new file mode 100644
index 00000000000000..a1229bc484f241
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-umberto_fine_tuned_hate_offensivity_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English umberto_fine_tuned_hate_offensivity_pipeline pipeline CamemBertForSequenceClassification from lupobricco
+author: John Snow Labs
+name: umberto_fine_tuned_hate_offensivity_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`umberto_fine_tuned_hate_offensivity_pipeline` is a English model originally trained by lupobricco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/umberto_fine_tuned_hate_offensivity_pipeline_en_5.5.0_3.0_1725378665372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/umberto_fine_tuned_hate_offensivity_pipeline_en_5.5.0_3.0_1725378665372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("umberto_fine_tuned_hate_offensivity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("umberto_fine_tuned_hate_offensivity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|umberto_fine_tuned_hate_offensivity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.8 MB|
+
+## References
+
+https://huggingface.co/lupobricco/umBERTo_fine-tuned_hate_offensivity
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-uner_roberta_ner_en.md b/docs/_posts/ahmedlone127/2024-09-03-uner_roberta_ner_en.md
new file mode 100644
index 00000000000000..875ec5da653e78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-uner_roberta_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English uner_roberta_ner XlmRoBertaForTokenClassification from mirfan899
+author: John Snow Labs
+name: uner_roberta_ner
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uner_roberta_ner` is a English model originally trained by mirfan899.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uner_roberta_ner_en_5.5.0_3.0_1725347890425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uner_roberta_ner_en_5.5.0_3.0_1725347890425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("uner_roberta_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("uner_roberta_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uner_roberta_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/mirfan899/uner-roberta-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-uner_roberta_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-uner_roberta_ner_pipeline_en.md
new file mode 100644
index 00000000000000..bbd0fa8a0a9cb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-uner_roberta_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English uner_roberta_ner_pipeline pipeline XlmRoBertaForTokenClassification from mirfan899
+author: John Snow Labs
+name: uner_roberta_ner_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uner_roberta_ner_pipeline` is a English model originally trained by mirfan899.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uner_roberta_ner_pipeline_en_5.5.0_3.0_1725348014092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uner_roberta_ner_pipeline_en_5.5.0_3.0_1725348014092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uner_roberta_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uner_roberta_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uner_roberta_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/mirfan899/uner-roberta-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-unspsc_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-unspsc_base_en.md
new file mode 100644
index 00000000000000..489dc3d4348ef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-unspsc_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English unspsc_base DistilBertForSequenceClassification from woland2k
+author: John Snow Labs
+name: unspsc_base
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unspsc_base` is a English model originally trained by woland2k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unspsc_base_en_5.5.0_3.0_1725394451105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unspsc_base_en_5.5.0_3.0_1725394451105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("unspsc_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("unspsc_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|unspsc_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|260.1 MB|
+
+## References
+
+https://huggingface.co/woland2k/unspsc-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-unspsc_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-unspsc_base_pipeline_en.md
new file mode 100644
index 00000000000000..ba6f9f7f327016
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-unspsc_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English unspsc_base_pipeline pipeline DistilBertForSequenceClassification from woland2k
+author: John Snow Labs
+name: unspsc_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unspsc_base_pipeline` is a English model originally trained by woland2k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unspsc_base_pipeline_en_5.5.0_3.0_1725394465515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unspsc_base_pipeline_en_5.5.0_3.0_1725394465515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("unspsc_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("unspsc_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|unspsc_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|260.1 MB|
+
+## References
+
+https://huggingface.co/woland2k/unspsc-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-varta_bert_xx.md b/docs/_posts/ahmedlone127/2024-09-03-varta_bert_xx.md
new file mode 100644
index 00000000000000..2edbb8ab48be52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-varta_bert_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual varta_bert BertEmbeddings from rahular
+author: John Snow Labs
+name: varta_bert
+date: 2024-09-03
+tags: [xx, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`varta_bert` is a Multilingual model originally trained by rahular.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/varta_bert_xx_5.5.0_3.0_1725323819897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/varta_bert_xx_5.5.0_3.0_1725323819897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("varta_bert","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("varta_bert","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|varta_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|xx|
+|Size:|691.1 MB|
+
+## References
+
+https://huggingface.co/rahular/varta-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-vien_resume_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-vien_resume_roberta_base_en.md
new file mode 100644
index 00000000000000..f179ce19e71595
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-vien_resume_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vien_resume_roberta_base XlmRoBertaEmbeddings from thaidv96
+author: John Snow Labs
+name: vien_resume_roberta_base
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vien_resume_roberta_base` is a English model originally trained by thaidv96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vien_resume_roberta_base_en_5.5.0_3.0_1725399914810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vien_resume_roberta_base_en_5.5.0_3.0_1725399914810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("vien_resume_roberta_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("vien_resume_roberta_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vien_resume_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/thaidv96/vien-resume-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-vien_resume_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-vien_resume_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..2900821fe703e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-vien_resume_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vien_resume_roberta_base_pipeline pipeline XlmRoBertaEmbeddings from thaidv96
+author: John Snow Labs
+name: vien_resume_roberta_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vien_resume_roberta_base_pipeline` is a English model originally trained by thaidv96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vien_resume_roberta_base_pipeline_en_5.5.0_3.0_1725399977866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vien_resume_roberta_base_pipeline_en_5.5.0_3.0_1725399977866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vien_resume_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vien_resume_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vien_resume_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/thaidv96/vien-resume-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-vietnamese_english_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-vietnamese_english_roberta_base_en.md
new file mode 100644
index 00000000000000..794e918adb8446
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-vietnamese_english_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vietnamese_english_roberta_base RoBertaEmbeddings from truongpdd
+author: John Snow Labs
+name: vietnamese_english_roberta_base
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_english_roberta_base` is a English model originally trained by truongpdd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_english_roberta_base_en_5.5.0_3.0_1725381803659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_english_roberta_base_en_5.5.0_3.0_1725381803659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("vietnamese_english_roberta_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("vietnamese_english_roberta_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vietnamese_english_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|600.9 MB|
+
+## References
+
+https://huggingface.co/truongpdd/vi-en-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-vietnamese_english_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-vietnamese_english_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..635a7b17dbab88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-vietnamese_english_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vietnamese_english_roberta_base_pipeline pipeline RoBertaEmbeddings from truongpdd
+author: John Snow Labs
+name: vietnamese_english_roberta_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_english_roberta_base_pipeline` is a English model originally trained by truongpdd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_english_roberta_base_pipeline_en_5.5.0_3.0_1725381838466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_english_roberta_base_pipeline_en_5.5.0_3.0_1725381838466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vietnamese_english_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vietnamese_english_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vietnamese_english_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|601.0 MB|
+
+## References
+
+https://huggingface.co/truongpdd/vi-en-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-vis_genome_fine_tuned_opus_maltese_english_hausa_en.md b/docs/_posts/ahmedlone127/2024-09-03-vis_genome_fine_tuned_opus_maltese_english_hausa_en.md
new file mode 100644
index 00000000000000..2a2efb1301475c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-vis_genome_fine_tuned_opus_maltese_english_hausa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vis_genome_fine_tuned_opus_maltese_english_hausa MarianTransformer from lukmanaj
+author: John Snow Labs
+name: vis_genome_fine_tuned_opus_maltese_english_hausa
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vis_genome_fine_tuned_opus_maltese_english_hausa` is a English model originally trained by lukmanaj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vis_genome_fine_tuned_opus_maltese_english_hausa_en_5.5.0_3.0_1725346886383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vis_genome_fine_tuned_opus_maltese_english_hausa_en_5.5.0_3.0_1725346886383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("vis_genome_fine_tuned_opus_maltese_english_hausa","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("vis_genome_fine_tuned_opus_maltese_english_hausa","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vis_genome_fine_tuned_opus_maltese_english_hausa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|497.2 MB|
+
+## References
+
+https://huggingface.co/lukmanaj/vis-genome-fine-tuned-opus-mt-en-ha
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-w_en2zh_hsk_en.md b/docs/_posts/ahmedlone127/2024-09-03-w_en2zh_hsk_en.md
new file mode 100644
index 00000000000000..1816c4aa46536d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-w_en2zh_hsk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English w_en2zh_hsk MarianTransformer from Chun
+author: John Snow Labs
+name: w_en2zh_hsk
+date: 2024-09-03
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`w_en2zh_hsk` is a English model originally trained by Chun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/w_en2zh_hsk_en_5.5.0_3.0_1725403752975.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/w_en2zh_hsk_en_5.5.0_3.0_1725403752975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("w_en2zh_hsk","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("w_en2zh_hsk","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|w_en2zh_hsk|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|541.0 MB|
+
+## References
+
+https://huggingface.co/Chun/w-en2zh-hsk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-w_en2zh_hsk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-w_en2zh_hsk_pipeline_en.md
new file mode 100644
index 00000000000000..8b33342700d583
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-w_en2zh_hsk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English w_en2zh_hsk_pipeline pipeline MarianTransformer from Chun
+author: John Snow Labs
+name: w_en2zh_hsk_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`w_en2zh_hsk_pipeline` is a English model originally trained by Chun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/w_en2zh_hsk_pipeline_en_5.5.0_3.0_1725403786025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/w_en2zh_hsk_pipeline_en_5.5.0_3.0_1725403786025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("w_en2zh_hsk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("w_en2zh_hsk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|w_en2zh_hsk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|541.5 MB|
+
+## References
+
+https://huggingface.co/Chun/w-en2zh-hsk
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_base_bengali_shhossain_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_base_bengali_shhossain_en.md
new file mode 100644
index 00000000000000..b5e6e6b7f35a85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_base_bengali_shhossain_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_base_bengali_shhossain WhisperForCTC from shhossain
+author: John Snow Labs
+name: whisper_base_bengali_shhossain
+date: 2024-09-03
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_bengali_shhossain` is a English model originally trained by shhossain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_bengali_shhossain_en_5.5.0_3.0_1725362993130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_bengali_shhossain_en_5.5.0_3.0_1725362993130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_base_bengali_shhossain","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_base_bengali_shhossain", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_bengali_shhossain|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|644.0 MB|
+
+## References
+
+https://huggingface.co/shhossain/whisper-base-bn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_base_bengali_shhossain_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_base_bengali_shhossain_pipeline_en.md
new file mode 100644
index 00000000000000..c22986ce25a367
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_base_bengali_shhossain_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_base_bengali_shhossain_pipeline pipeline WhisperForCTC from shhossain
+author: John Snow Labs
+name: whisper_base_bengali_shhossain_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_bengali_shhossain_pipeline` is a English model originally trained by shhossain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_bengali_shhossain_pipeline_en_5.5.0_3.0_1725363038837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_bengali_shhossain_pipeline_en_5.5.0_3.0_1725363038837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_base_bengali_shhossain_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_base_bengali_shhossain_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_bengali_shhossain_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|644.0 MB|
+
+## References
+
+https://huggingface.co/shhossain/whisper-base-bn
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_base_quran_ar.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_base_quran_ar.md
new file mode 100644
index 00000000000000..038be706323cbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_base_quran_ar.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Arabic whisper_base_quran WhisperForCTC from raghadOmar
+author: John Snow Labs
+name: whisper_base_quran
+date: 2024-09-03
+tags: [ar, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_quran` is a Arabic model originally trained by raghadOmar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_quran_ar_5.5.0_3.0_1725365104277.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_quran_ar_5.5.0_3.0_1725365104277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_base_quran","ar") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_base_quran", "ar")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_quran|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/raghadOmar/whisper-base-quran
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_base_quran_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_base_quran_pipeline_ar.md
new file mode 100644
index 00000000000000..9b424f2c4f69f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_base_quran_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic whisper_base_quran_pipeline pipeline WhisperForCTC from raghadOmar
+author: John Snow Labs
+name: whisper_base_quran_pipeline
+date: 2024-09-03
+tags: [ar, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_quran_pipeline` is a Arabic model originally trained by raghadOmar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_quran_pipeline_ar_5.5.0_3.0_1725365194938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_quran_pipeline_ar_5.5.0_3.0_1725365194938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_base_quran_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_base_quran_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_quran_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/raghadOmar/whisper-base-quran
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_medium_arabic_suite_iv_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_medium_arabic_suite_iv_en.md
new file mode 100644
index 00000000000000..949b5e3bfad7d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_medium_arabic_suite_iv_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_medium_arabic_suite_iv WhisperForCTC from KarthikAvinash
+author: John Snow Labs
+name: whisper_medium_arabic_suite_iv
+date: 2024-09-03
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_medium_arabic_suite_iv` is a English model originally trained by KarthikAvinash.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_medium_arabic_suite_iv_en_5.5.0_3.0_1725367893931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_medium_arabic_suite_iv_en_5.5.0_3.0_1725367893931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_medium_arabic_suite_iv","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_medium_arabic_suite_iv", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_medium_arabic_suite_iv|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|4.8 GB|
+
+## References
+
+https://huggingface.co/KarthikAvinash/whisper-medium-arabic-suite-IV
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_medium_arabic_suite_iv_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_medium_arabic_suite_iv_pipeline_en.md
new file mode 100644
index 00000000000000..95c6c6ddb49275
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_medium_arabic_suite_iv_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_medium_arabic_suite_iv_pipeline pipeline WhisperForCTC from KarthikAvinash
+author: John Snow Labs
+name: whisper_medium_arabic_suite_iv_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_medium_arabic_suite_iv_pipeline` is a English model originally trained by KarthikAvinash.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_medium_arabic_suite_iv_pipeline_en_5.5.0_3.0_1725368138137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_medium_arabic_suite_iv_pipeline_en_5.5.0_3.0_1725368138137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_medium_arabic_suite_iv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_medium_arabic_suite_iv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_medium_arabic_suite_iv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|4.8 GB|
+
+## References
+
+https://huggingface.co/KarthikAvinash/whisper-medium-arabic-suite-IV
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_small_arabic_ayoubkirouane_ar.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_arabic_ayoubkirouane_ar.md
new file mode 100644
index 00000000000000..9f5b47cefa49c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_arabic_ayoubkirouane_ar.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Arabic whisper_small_arabic_ayoubkirouane WhisperForCTC from ayoubkirouane
+author: John Snow Labs
+name: whisper_small_arabic_ayoubkirouane
+date: 2024-09-03
+tags: [ar, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_arabic_ayoubkirouane` is a Arabic model originally trained by ayoubkirouane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_ayoubkirouane_ar_5.5.0_3.0_1725365413588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_ayoubkirouane_ar_5.5.0_3.0_1725365413588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_arabic_ayoubkirouane","ar") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_arabic_ayoubkirouane", "ar")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_arabic_ayoubkirouane|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/ayoubkirouane/whisper-small-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_small_arabic_ayoubkirouane_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_arabic_ayoubkirouane_pipeline_ar.md
new file mode 100644
index 00000000000000..789ab1a64faf60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_arabic_ayoubkirouane_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic whisper_small_arabic_ayoubkirouane_pipeline pipeline WhisperForCTC from ayoubkirouane
+author: John Snow Labs
+name: whisper_small_arabic_ayoubkirouane_pipeline
+date: 2024-09-03
+tags: [ar, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_arabic_ayoubkirouane_pipeline` is a Arabic model originally trained by ayoubkirouane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_ayoubkirouane_pipeline_ar_5.5.0_3.0_1725365513907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_ayoubkirouane_pipeline_ar_5.5.0_3.0_1725365513907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_arabic_ayoubkirouane_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_arabic_ayoubkirouane_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_arabic_ayoubkirouane_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/ayoubkirouane/whisper-small-ar
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_small_breton_alanoix_br.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_breton_alanoix_br.md
new file mode 100644
index 00000000000000..8c3bd394cefb83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_breton_alanoix_br.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Breton whisper_small_breton_alanoix WhisperForCTC from alanoix
+author: John Snow Labs
+name: whisper_small_breton_alanoix
+date: 2024-09-03
+tags: [br, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: br
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_breton_alanoix` is a Breton model originally trained by alanoix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_breton_alanoix_br_5.5.0_3.0_1725362560652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_breton_alanoix_br_5.5.0_3.0_1725362560652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_breton_alanoix","br") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_breton_alanoix", "br")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_breton_alanoix|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|br|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/alanoix/whisper-small-br
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_small_breton_alanoix_pipeline_br.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_breton_alanoix_pipeline_br.md
new file mode 100644
index 00000000000000..feba3b57e18ab8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_breton_alanoix_pipeline_br.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Breton whisper_small_breton_alanoix_pipeline pipeline WhisperForCTC from alanoix
+author: John Snow Labs
+name: whisper_small_breton_alanoix_pipeline
+date: 2024-09-03
+tags: [br, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: br
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_breton_alanoix_pipeline` is a Breton model originally trained by alanoix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_breton_alanoix_pipeline_br_5.5.0_3.0_1725362652605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_breton_alanoix_pipeline_br_5.5.0_3.0_1725362652605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_breton_alanoix_pipeline", lang = "br")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_breton_alanoix_pipeline", lang = "br")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_breton_alanoix_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|br|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/alanoix/whisper-small-br
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_small_wer35_ekg_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_wer35_ekg_en.md
new file mode 100644
index 00000000000000..485039f1ad9c62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_wer35_ekg_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_small_wer35_ekg WhisperForCTC from rikeshsilwalekg
+author: John Snow Labs
+name: whisper_small_wer35_ekg
+date: 2024-09-03
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_wer35_ekg` is a English model originally trained by rikeshsilwalekg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_wer35_ekg_en_5.5.0_3.0_1725362498586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_wer35_ekg_en_5.5.0_3.0_1725362498586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_wer35_ekg","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_wer35_ekg", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_wer35_ekg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/rikeshsilwalekg/whisper-small-wer35-ekg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_small_wer35_ekg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_wer35_ekg_pipeline_en.md
new file mode 100644
index 00000000000000..26b763e79b7c61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_wer35_ekg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_small_wer35_ekg_pipeline pipeline WhisperForCTC from rikeshsilwalekg
+author: John Snow Labs
+name: whisper_small_wer35_ekg_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_wer35_ekg_pipeline` is a English model originally trained by rikeshsilwalekg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_wer35_ekg_pipeline_en_5.5.0_3.0_1725362593215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_wer35_ekg_pipeline_en_5.5.0_3.0_1725362593215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_wer35_ekg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_wer35_ekg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_wer35_ekg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/rikeshsilwalekg/whisper-small-wer35-ekg
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_small_yoruba_steja_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_yoruba_steja_en.md
new file mode 100644
index 00000000000000..8811c4a38b0bf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_yoruba_steja_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_small_yoruba_steja WhisperForCTC from steja
+author: John Snow Labs
+name: whisper_small_yoruba_steja
+date: 2024-09-03
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_yoruba_steja` is a English model originally trained by steja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_yoruba_steja_en_5.5.0_3.0_1725363998518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_yoruba_steja_en_5.5.0_3.0_1725363998518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_yoruba_steja","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_yoruba_steja", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_yoruba_steja|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/steja/whisper-small-yoruba
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_small_yoruba_steja_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_yoruba_steja_pipeline_en.md
new file mode 100644
index 00000000000000..f9602c349e4b64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_small_yoruba_steja_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_small_yoruba_steja_pipeline pipeline WhisperForCTC from steja
+author: John Snow Labs
+name: whisper_small_yoruba_steja_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_yoruba_steja_pipeline` is a English model originally trained by steja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_yoruba_steja_pipeline_en_5.5.0_3.0_1725364099015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_yoruba_steja_pipeline_en_5.5.0_3.0_1725364099015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_yoruba_steja_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_yoruba_steja_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_yoruba_steja_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/steja/whisper-small-yoruba
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_chinese_twi_baseline_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_chinese_twi_baseline_pipeline_zh.md
new file mode 100644
index 00000000000000..50c801e33646c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_chinese_twi_baseline_pipeline_zh.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Chinese whisper_tiny_chinese_twi_baseline_pipeline pipeline WhisperForCTC from xmzhu
+author: John Snow Labs
+name: whisper_tiny_chinese_twi_baseline_pipeline
+date: 2024-09-03
+tags: [zh, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_chinese_twi_baseline_pipeline` is a Chinese model originally trained by xmzhu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_chinese_twi_baseline_pipeline_zh_5.5.0_3.0_1725360890790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_chinese_twi_baseline_pipeline_zh_5.5.0_3.0_1725360890790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tiny_chinese_twi_baseline_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_chinese_twi_baseline_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_chinese_twi_baseline_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|390.7 MB|
+
+## References
+
+https://huggingface.co/xmzhu/whisper-tiny-zh-TW-baseline
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_chinese_twi_baseline_zh.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_chinese_twi_baseline_zh.md
new file mode 100644
index 00000000000000..fd722f0e60ad5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_chinese_twi_baseline_zh.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Chinese whisper_tiny_chinese_twi_baseline WhisperForCTC from xmzhu
+author: John Snow Labs
+name: whisper_tiny_chinese_twi_baseline
+date: 2024-09-03
+tags: [zh, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_chinese_twi_baseline` is a Chinese model originally trained by xmzhu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_chinese_twi_baseline_zh_5.5.0_3.0_1725360868226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_chinese_twi_baseline_zh_5.5.0_3.0_1725360868226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_chinese_twi_baseline","zh") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_chinese_twi_baseline", "zh")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_chinese_twi_baseline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|zh|
+|Size:|390.7 MB|
+
+## References
+
+https://huggingface.co/xmzhu/whisper-tiny-zh-TW-baseline
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_english_eai6_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_english_eai6_en.md
new file mode 100644
index 00000000000000..c145d5c8342ba8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_english_eai6_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_tiny_english_eai6 WhisperForCTC from eai6
+author: John Snow Labs
+name: whisper_tiny_english_eai6
+date: 2024-09-03
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_english_eai6` is a English model originally trained by eai6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_english_eai6_en_5.5.0_3.0_1725363840799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_english_eai6_en_5.5.0_3.0_1725363840799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_english_eai6","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_english_eai6", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_english_eai6|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|393.9 MB|
+
+## References
+
+https://huggingface.co/eai6/whisper-tiny.en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_english_eai6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_english_eai6_pipeline_en.md
new file mode 100644
index 00000000000000..58c918c6a45596
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_english_eai6_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_tiny_english_eai6_pipeline pipeline WhisperForCTC from eai6
+author: John Snow Labs
+name: whisper_tiny_english_eai6_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_english_eai6_pipeline` is a English model originally trained by eai6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_english_eai6_pipeline_en_5.5.0_3.0_1725363862341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_english_eai6_pipeline_en_5.5.0_3.0_1725363862341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tiny_english_eai6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_english_eai6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_english_eai6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|393.9 MB|
+
+## References
+
+https://huggingface.co/eai6/whisper-tiny.en
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_kor_16k_hf_ep100_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_kor_16k_hf_ep100_en.md
new file mode 100644
index 00000000000000..b9803f78bae328
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_kor_16k_hf_ep100_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_tiny_kor_16k_hf_ep100 WhisperForCTC from kaen2891
+author: John Snow Labs
+name: whisper_tiny_kor_16k_hf_ep100
+date: 2024-09-03
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_kor_16k_hf_ep100` is a English model originally trained by kaen2891.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_kor_16k_hf_ep100_en_5.5.0_3.0_1725363196919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_kor_16k_hf_ep100_en_5.5.0_3.0_1725363196919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_kor_16k_hf_ep100","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_kor_16k_hf_ep100", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_kor_16k_hf_ep100|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|389.5 MB|
+
+## References
+
+https://huggingface.co/kaen2891/whisper-tiny-kor-16k-hf-ep100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_kor_16k_hf_ep100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_kor_16k_hf_ep100_pipeline_en.md
new file mode 100644
index 00000000000000..6451b7dc192346
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_kor_16k_hf_ep100_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_tiny_kor_16k_hf_ep100_pipeline pipeline WhisperForCTC from kaen2891
+author: John Snow Labs
+name: whisper_tiny_kor_16k_hf_ep100_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_kor_16k_hf_ep100_pipeline` is a English model originally trained by kaen2891.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_kor_16k_hf_ep100_pipeline_en_5.5.0_3.0_1725363218327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_kor_16k_hf_ep100_pipeline_en_5.5.0_3.0_1725363218327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tiny_kor_16k_hf_ep100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_kor_16k_hf_ep100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_kor_16k_hf_ep100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|389.5 MB|
+
+## References
+
+https://huggingface.co/kaen2891/whisper-tiny-kor-16k-hf-ep100
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_spanish_rjac_es.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_spanish_rjac_es.md
new file mode 100644
index 00000000000000..cd5c4162e00fd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_spanish_rjac_es.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Castilian, Spanish whisper_tiny_spanish_rjac WhisperForCTC from rjac
+author: John Snow Labs
+name: whisper_tiny_spanish_rjac
+date: 2024-09-03
+tags: [es, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_spanish_rjac` is a Castilian, Spanish model originally trained by rjac.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_spanish_rjac_es_5.5.0_3.0_1725362076420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_spanish_rjac_es_5.5.0_3.0_1725362076420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_spanish_rjac","es") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_spanish_rjac", "es")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_spanish_rjac|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|es|
+|Size:|384.0 MB|
+
+## References
+
+https://huggingface.co/rjac/whisper-tiny-spanish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_spanish_rjac_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_spanish_rjac_pipeline_es.md
new file mode 100644
index 00000000000000..a1f488c69bac1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_spanish_rjac_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish whisper_tiny_spanish_rjac_pipeline pipeline WhisperForCTC from rjac
+author: John Snow Labs
+name: whisper_tiny_spanish_rjac_pipeline
+date: 2024-09-03
+tags: [es, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_spanish_rjac_pipeline` is a Castilian, Spanish model originally trained by rjac.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_spanish_rjac_pipeline_es_5.5.0_3.0_1725362103843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_spanish_rjac_pipeline_es_5.5.0_3.0_1725362103843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tiny_spanish_rjac_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_spanish_rjac_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_spanish_rjac_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|384.0 MB|
+
+## References
+
+https://huggingface.co/rjac/whisper-tiny-spanish
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_urdu_sharjeel103_pipeline_ur.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_urdu_sharjeel103_pipeline_ur.md
new file mode 100644
index 00000000000000..aed665672602a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_urdu_sharjeel103_pipeline_ur.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Urdu whisper_tiny_urdu_sharjeel103_pipeline pipeline WhisperForCTC from sharjeel103
+author: John Snow Labs
+name: whisper_tiny_urdu_sharjeel103_pipeline
+date: 2024-09-03
+tags: [ur, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ur
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_urdu_sharjeel103_pipeline` is a Urdu model originally trained by sharjeel103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_urdu_sharjeel103_pipeline_ur_5.5.0_3.0_1725365482610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_urdu_sharjeel103_pipeline_ur_5.5.0_3.0_1725365482610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tiny_urdu_sharjeel103_pipeline", lang = "ur")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_urdu_sharjeel103_pipeline", lang = "ur")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_urdu_sharjeel103_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ur|
+|Size:|389.1 MB|
+
+## References
+
+https://huggingface.co/sharjeel103/whisper-tiny-urdu
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_urdu_sharjeel103_ur.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_urdu_sharjeel103_ur.md
new file mode 100644
index 00000000000000..2bc1b37fd94270
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_tiny_urdu_sharjeel103_ur.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Urdu whisper_tiny_urdu_sharjeel103 WhisperForCTC from sharjeel103
+author: John Snow Labs
+name: whisper_tiny_urdu_sharjeel103
+date: 2024-09-03
+tags: [ur, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ur
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_urdu_sharjeel103` is a Urdu model originally trained by sharjeel103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_urdu_sharjeel103_ur_5.5.0_3.0_1725365454583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_urdu_sharjeel103_ur_5.5.0_3.0_1725365454583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_urdu_sharjeel103","ur") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_urdu_sharjeel103", "ur")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_urdu_sharjeel103|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ur|
+|Size:|389.1 MB|
+
+## References
+
+https://huggingface.co/sharjeel103/whisper-tiny-urdu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_torgo_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_torgo_finetuned_en.md
new file mode 100644
index 00000000000000..1d3ec6cae050f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_torgo_finetuned_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_torgo_finetuned WhisperForCTC from RSTV-24
+author: John Snow Labs
+name: whisper_torgo_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_torgo_finetuned` is a English model originally trained by RSTV-24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_torgo_finetuned_en_5.5.0_3.0_1725366377624.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_torgo_finetuned_en_5.5.0_3.0_1725366377624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_torgo_finetuned","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_torgo_finetuned", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_torgo_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|645.3 MB|
+
+## References
+
+https://huggingface.co/RSTV-24/Whisper-Torgo-Finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-whisper_torgo_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-whisper_torgo_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..66cdb338299bd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-whisper_torgo_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_torgo_finetuned_pipeline pipeline WhisperForCTC from RSTV-24
+author: John Snow Labs
+name: whisper_torgo_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_torgo_finetuned_pipeline` is a English model originally trained by RSTV-24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_torgo_finetuned_pipeline_en_5.5.0_3.0_1725366420992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_torgo_finetuned_pipeline_en_5.5.0_3.0_1725366420992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_torgo_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_torgo_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_torgo_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|645.3 MB|
+
+## References
+
+https://huggingface.co/RSTV-24/Whisper-Torgo-Finetuned
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_pagekit_test_tags_cwadj_en.md b/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_pagekit_test_tags_cwadj_en.md
new file mode 100644
index 00000000000000..7460ef3f1532dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-withinapps_ndd_pagekit_test_tags_cwadj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_pagekit_test_tags_cwadj DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_pagekit_test_tags_cwadj
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_pagekit_test_tags_cwadj` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_pagekit_test_tags_cwadj_en_5.5.0_3.0_1725330211658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_pagekit_test_tags_cwadj_en_5.5.0_3.0_1725330211658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_pagekit_test_tags_cwadj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_pagekit_test_tags_cwadj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_pagekit_test_tags_cwadj|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-pagekit_test-tags-CWAdj
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xdoc_base_funsd_en.md b/docs/_posts/ahmedlone127/2024-09-03-xdoc_base_funsd_en.md
new file mode 100644
index 00000000000000..b5d1bf31399e2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xdoc_base_funsd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xdoc_base_funsd RoBertaForTokenClassification from microsoft
+author: John Snow Labs
+name: xdoc_base_funsd
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xdoc_base_funsd` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xdoc_base_funsd_en_5.5.0_3.0_1725383666552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xdoc_base_funsd_en_5.5.0_3.0_1725383666552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("xdoc_base_funsd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("xdoc_base_funsd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xdoc_base_funsd|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/microsoft/xdoc-base-funsd
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xdoc_base_funsd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xdoc_base_funsd_pipeline_en.md
new file mode 100644
index 00000000000000..e1064236372c9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xdoc_base_funsd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xdoc_base_funsd_pipeline pipeline RoBertaForTokenClassification from microsoft
+author: John Snow Labs
+name: xdoc_base_funsd_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xdoc_base_funsd_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xdoc_base_funsd_pipeline_en_5.5.0_3.0_1725383691242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xdoc_base_funsd_pipeline_en_5.5.0_3.0_1725383691242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xdoc_base_funsd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xdoc_base_funsd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xdoc_base_funsd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/microsoft/xdoc-base-funsd
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_r_with_transliteration_max_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_r_with_transliteration_max_en.md
new file mode 100644
index 00000000000000..7cf594c24ca260
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_r_with_transliteration_max_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_r_with_transliteration_max XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: xlm_r_with_transliteration_max
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_with_transliteration_max` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_with_transliteration_max_en_5.5.0_3.0_1725352808577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_with_transliteration_max_en_5.5.0_3.0_1725352808577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_r_with_transliteration_max","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_r_with_transliteration_max","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_with_transliteration_max|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|843.3 MB|
+
+## References
+
+https://huggingface.co/yihongLiu/xlm-r-with-transliteration-max
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_esg_ner_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_esg_ner_en.md
new file mode 100644
index 00000000000000..49a02ef3528a36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_esg_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_esg_ner XlmRoBertaForTokenClassification from santoshvutukuri
+author: John Snow Labs
+name: xlm_roberta_base_esg_ner
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_esg_ner` is a English model originally trained by santoshvutukuri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_esg_ner_en_5.5.0_3.0_1725349404544.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_esg_ner_en_5.5.0_3.0_1725349404544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_esg_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_esg_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_esg_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|847.0 MB|
+
+## References
+
+https://huggingface.co/santoshvutukuri/xlm-roberta-base-esg-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_esg_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_esg_ner_pipeline_en.md
new file mode 100644
index 00000000000000..b42fd9eac6a628
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_esg_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_esg_ner_pipeline pipeline XlmRoBertaForTokenClassification from santoshvutukuri
+author: John Snow Labs
+name: xlm_roberta_base_esg_ner_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_esg_ner_pipeline` is a English model originally trained by santoshvutukuri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_esg_ner_pipeline_en_5.5.0_3.0_1725349475119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_esg_ner_pipeline_en_5.5.0_3.0_1725349475119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_esg_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_esg_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_esg_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|847.1 MB|
+
+## References
+
+https://huggingface.co/santoshvutukuri/xlm-roberta-base-esg-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1_en.md
new file mode 100644
index 00000000000000..f299c6b5d38288
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1 XlmRoBertaForQuestionAnswering from jluckyboyj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1` is a English model originally trained by jluckyboyj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1_en_5.5.0_3.0_1725380000215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1_en_5.5.0_3.0_1725380000215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|852.8 MB|
+
+## References
+
+https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-augument-visquad2-15-3-2023-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_chichewa_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_chichewa_en.md
new file mode 100644
index 00000000000000..4a28d113730bb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_chichewa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_chichewa XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_chichewa
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_chichewa` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_chichewa_en_5.5.0_3.0_1725352653797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_chichewa_en_5.5.0_3.0_1725352653797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_chichewa","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_chichewa","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_chichewa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-chichewa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_chichewa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_chichewa_pipeline_en.md
new file mode 100644
index 00000000000000..7e31f54b18ae14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_chichewa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_chichewa_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_chichewa_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_chichewa_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_chichewa_pipeline_en_5.5.0_3.0_1725352704864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_chichewa_pipeline_en_5.5.0_3.0_1725352704864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_chichewa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_chichewa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_chichewa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-chichewa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_clinais_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_clinais_en.md
new file mode 100644
index 00000000000000..ad7ba79b606bb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_clinais_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_clinais XlmRoBertaEmbeddings from joheras
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_clinais
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_clinais` is a English model originally trained by joheras.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_clinais_en_5.5.0_3.0_1725391187848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_clinais_en_5.5.0_3.0_1725391187848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_clinais","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_clinais","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_clinais|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|988.3 MB|
+
+## References
+
+https://huggingface.co/joheras/xlm-roberta-base-finetuned-clinais
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_dholuo_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_dholuo_en.md
new file mode 100644
index 00000000000000..aa3729a7eb430a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_dholuo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_dholuo XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_dholuo
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_dholuo` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_dholuo_en_5.5.0_3.0_1725352757442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_dholuo_en_5.5.0_3.0_1725352757442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_dholuo","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_dholuo","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_dholuo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-luo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_dholuo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_dholuo_pipeline_en.md
new file mode 100644
index 00000000000000..471ee80a128d09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_dholuo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_dholuo_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_dholuo_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_dholuo_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_dholuo_pipeline_en_5.5.0_3.0_1725352814633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_dholuo_pipeline_en_5.5.0_3.0_1725352814633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_dholuo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_dholuo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_dholuo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-luo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_digikala_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_digikala_en.md
new file mode 100644
index 00000000000000..001d0bb4485425
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_digikala_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_digikala XlmRoBertaEmbeddings from ShahlaDnshi96
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_digikala
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_digikala` is a English model originally trained by ShahlaDnshi96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_digikala_en_5.5.0_3.0_1725354230748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_digikala_en_5.5.0_3.0_1725354230748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_digikala","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_digikala","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_digikala|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|652.9 MB|
+
+## References
+
+https://huggingface.co/ShahlaDnshi96/xlm-roberta-base-finetuned-digikala
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_digikala_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_digikala_pipeline_en.md
new file mode 100644
index 00000000000000..1f63b2326ea1c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_digikala_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_digikala_pipeline pipeline XlmRoBertaEmbeddings from ShahlaDnshi96
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_digikala_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_digikala_pipeline` is a English model originally trained by ShahlaDnshi96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_digikala_pipeline_en_5.5.0_3.0_1725354425303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_digikala_pipeline_en_5.5.0_3.0_1725354425303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_digikala_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_digikala_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_digikala_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|652.9 MB|
+
+## References
+
+https://huggingface.co/ShahlaDnshi96/xlm-roberta-base-finetuned-digikala
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hausa_ha.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hausa_ha.md
new file mode 100644
index 00000000000000..f3eef887479253
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hausa_ha.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hausa xlm_roberta_base_finetuned_hausa XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_hausa
+date: 2024-09-03
+tags: [ha, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: ha
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_hausa` is a Hausa model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_hausa_ha_5.5.0_3.0_1725390847799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_hausa_ha_5.5.0_3.0_1725390847799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_hausa","ha") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_hausa","ha") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_hausa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|ha|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-hausa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hausa_pipeline_ha.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hausa_pipeline_ha.md
new file mode 100644
index 00000000000000..96a95fdf430e07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hausa_pipeline_ha.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hausa xlm_roberta_base_finetuned_hausa_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_hausa_pipeline
+date: 2024-09-03
+tags: [ha, open_source, pipeline, onnx]
+task: Embeddings
+language: ha
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_hausa_pipeline` is a Hausa model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_hausa_pipeline_ha_5.5.0_3.0_1725390902785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_hausa_pipeline_ha_5.5.0_3.0_1725390902785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_hausa_pipeline", lang = "ha")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_hausa_pipeline", lang = "ha")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ha|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-hausa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hkdse_english_paper4_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hkdse_english_paper4_en.md
new file mode 100644
index 00000000000000..110a5e2515402c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hkdse_english_paper4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_hkdse_english_paper4 XlmRoBertaEmbeddings from Wootang01
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_hkdse_english_paper4
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_hkdse_english_paper4` is a English model originally trained by Wootang01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_hkdse_english_paper4_en_5.5.0_3.0_1725353285080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_hkdse_english_paper4_en_5.5.0_3.0_1725353285080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_hkdse_english_paper4","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_hkdse_english_paper4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_hkdse_english_paper4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|977.5 MB|
+
+## References
+
+https://huggingface.co/Wootang01/xlm-roberta-base-finetuned-hkdse-english-paper4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline_en.md
new file mode 100644
index 00000000000000..eb1ea21d809494
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline pipeline XlmRoBertaEmbeddings from Wootang01
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline` is a English model originally trained by Wootang01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline_en_5.5.0_3.0_1725353363556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline_en_5.5.0_3.0_1725353363556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_hkdse_english_paper4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|977.5 MB|
+
+## References
+
+https://huggingface.co/Wootang01/xlm-roberta-base-finetuned-hkdse-english-paper4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_en.md
new file mode 100644
index 00000000000000..6c8ad8bbfd50f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_en_5.5.0_3.0_1725390523556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_en_5.5.0_3.0_1725390523556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kin-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..6a240927762e83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline pipeline XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline_en_5.5.0_3.0_1725390579183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline_en_5.5.0_3.0_1725390579183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kin-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline_en.md
new file mode 100644
index 00000000000000..40ed2dc58a112b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline pipeline XlmRoBertaForSequenceClassification from shaer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline` is a English model originally trained by shaer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline_en_5.5.0_3.0_1725396954893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline_en_5.5.0_3.0_1725396954893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_english_test_rundi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.5 MB|
+
+## References
+
+https://huggingface.co/shaer/xlm-roberta-base-finetuned-marc-en-test-run
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_naija_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_naija_en.md
new file mode 100644
index 00000000000000..90354a0032de2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_naija_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_naija XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_naija
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_naija` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_naija_en_5.5.0_3.0_1725399567343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_naija_en_5.5.0_3.0_1725399567343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_naija","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_naija","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_naija|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-naija
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_naija_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_naija_pipeline_en.md
new file mode 100644
index 00000000000000..a2c8b552ed186f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_naija_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_naija_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_naija_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_naija_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_naija_pipeline_en_5.5.0_3.0_1725399624098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_naija_pipeline_en_5.5.0_3.0_1725399624098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_naija_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_naija_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_naija_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-naija
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_osdg_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_osdg_en.md
new file mode 100644
index 00000000000000..fa96858f676f01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_osdg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_osdg XlmRoBertaForSequenceClassification from peter2000
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_osdg
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_osdg` is a English model originally trained by peter2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_osdg_en_5.5.0_3.0_1725396591628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_osdg_en_5.5.0_3.0_1725396591628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_osdg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_osdg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_osdg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|802.3 MB|
+
+## References
+
+https://huggingface.co/peter2000/xlm-roberta-base-finetuned-osdg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_osdg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_osdg_pipeline_en.md
new file mode 100644
index 00000000000000..c151a620bafc14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_osdg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_osdg_pipeline pipeline XlmRoBertaForSequenceClassification from peter2000
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_osdg_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_osdg_pipeline` is a English model originally trained by peter2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_osdg_pipeline_en_5.5.0_3.0_1725396729627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_osdg_pipeline_en_5.5.0_3.0_1725396729627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_osdg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_osdg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_osdg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|802.3 MB|
+
+## References
+
+https://huggingface.co/peter2000/xlm-roberta-base-finetuned-osdg
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline_en.md
new file mode 100644
index 00000000000000..16ffdcff7c2f3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline pipeline XlmRoBertaForTokenClassification from the-neural-networker
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline` is a English model originally trained by the-neural-networker.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline_en_5.5.0_3.0_1725348892061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline_en_5.5.0_3.0_1725348892061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_the_neural_networker_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.1 MB|
+
+## References
+
+https://huggingface.co/the-neural-networker/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_hcy5561_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_hcy5561_en.md
new file mode 100644
index 00000000000000..53a6cf122260e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_hcy5561_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_hcy5561 XlmRoBertaForTokenClassification from hcy5561
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_hcy5561
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_hcy5561` is a English model originally trained by hcy5561.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_hcy5561_en_5.5.0_3.0_1725323412218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_hcy5561_en_5.5.0_3.0_1725323412218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_hcy5561","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_hcy5561", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_hcy5561|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/hcy5561/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_seobak_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_seobak_en.md
new file mode 100644
index 00000000000000..bc92b670814035
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_seobak_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_seobak XlmRoBertaForTokenClassification from seobak
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_seobak
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_seobak` is a English model originally trained by seobak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_seobak_en_5.5.0_3.0_1725349772941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_seobak_en_5.5.0_3.0_1725349772941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_seobak","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_seobak", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_seobak|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/seobak/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_seobak_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_seobak_pipeline_en.md
new file mode 100644
index 00000000000000..1c8aeeffd2f981
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_french_seobak_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_seobak_pipeline pipeline XlmRoBertaForTokenClassification from seobak
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_seobak_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_seobak_pipeline` is a English model originally trained by seobak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_seobak_pipeline_en_5.5.0_3.0_1725349862029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_seobak_pipeline_en_5.5.0_3.0_1725349862029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_seobak_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_seobak_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_seobak_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/seobak/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_akira10_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_akira10_en.md
new file mode 100644
index 00000000000000..e736c7e5878fa1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_akira10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_akira10 XlmRoBertaForTokenClassification from Akira10
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_akira10
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_akira10` is a English model originally trained by Akira10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_akira10_en_5.5.0_3.0_1725372141062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_akira10_en_5.5.0_3.0_1725372141062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_akira10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_akira10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_akira10|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Akira10/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_akira10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_akira10_pipeline_en.md
new file mode 100644
index 00000000000000..f48858cdb622c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_akira10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_akira10_pipeline pipeline XlmRoBertaForTokenClassification from Akira10
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_akira10_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_akira10_pipeline` is a English model originally trained by Akira10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_akira10_pipeline_en_5.5.0_3.0_1725372223638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_akira10_pipeline_en_5.5.0_3.0_1725372223638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_akira10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_akira10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_akira10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Akira10/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_binzhu2023_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_binzhu2023_en.md
new file mode 100644
index 00000000000000..b041c763a9730f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_binzhu2023_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_binzhu2023 XlmRoBertaForTokenClassification from binzhu2023
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_binzhu2023
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_binzhu2023` is a English model originally trained by binzhu2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_binzhu2023_en_5.5.0_3.0_1725348085722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_binzhu2023_en_5.5.0_3.0_1725348085722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_binzhu2023","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_binzhu2023", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_binzhu2023|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/binzhu2023/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline_en.md
new file mode 100644
index 00000000000000..b6d9b03edd92b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline pipeline XlmRoBertaForTokenClassification from binzhu2023
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline` is a English model originally trained by binzhu2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline_en_5.5.0_3.0_1725348153143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline_en_5.5.0_3.0_1725348153143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_binzhu2023_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/binzhu2023/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ffalcao_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ffalcao_en.md
new file mode 100644
index 00000000000000..968d6a16016011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_ffalcao_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ffalcao XlmRoBertaForTokenClassification from ffalcao
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ffalcao
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ffalcao` is a English model originally trained by ffalcao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ffalcao_en_5.5.0_3.0_1725349227001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ffalcao_en_5.5.0_3.0_1725349227001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ffalcao","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ffalcao", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ffalcao|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/ffalcao/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline_en.md
new file mode 100644
index 00000000000000..e76ea72d31f77e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline pipeline XlmRoBertaForTokenClassification from lijingxin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline` is a English model originally trained by lijingxin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline_en_5.5.0_3.0_1725322470912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline_en_5.5.0_3.0_1725322470912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_lijingxin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/lijingxin/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline_en.md
new file mode 100644
index 00000000000000..5bda2f7a81ccdb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline pipeline XlmRoBertaForTokenClassification from Nobody138
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline` is a English model originally trained by Nobody138.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline_en_5.5.0_3.0_1725323387197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline_en_5.5.0_3.0_1725323387197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_nobody138_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/Nobody138/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_philophilae_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_philophilae_en.md
new file mode 100644
index 00000000000000..965c122fd61d29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_french_philophilae_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_philophilae XlmRoBertaForTokenClassification from Philophilae
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_philophilae
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_philophilae` is a English model originally trained by Philophilae.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_philophilae_en_5.5.0_3.0_1725323553062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_philophilae_en_5.5.0_3.0_1725323553062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_philophilae","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_philophilae", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_philophilae|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|857.0 MB|
+
+## References
+
+https://huggingface.co/Philophilae/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_hoonface_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_hoonface_en.md
new file mode 100644
index 00000000000000..bb22c8e3fef572
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_hoonface_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_hoonface XlmRoBertaForTokenClassification from hoonface
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_hoonface
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_hoonface` is a English model originally trained by hoonface.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hoonface_en_5.5.0_3.0_1725323020032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hoonface_en_5.5.0_3.0_1725323020032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_hoonface","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_hoonface", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_hoonface|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/hoonface/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline_en.md
new file mode 100644
index 00000000000000..26800602ceebfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline pipeline XlmRoBertaForTokenClassification from juhyun76
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline` is a English model originally trained by juhyun76.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline_en_5.5.0_3.0_1725321784301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline_en_5.5.0_3.0_1725321784301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_juhyun76_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|841.2 MB|
+
+## References
+
+https://huggingface.co/juhyun76/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_photonmz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_photonmz_pipeline_en.md
new file mode 100644
index 00000000000000..25f717c8b1a1f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_photonmz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_photonmz_pipeline pipeline XlmRoBertaForTokenClassification from photonmz
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_photonmz_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_photonmz_pipeline` is a English model originally trained by photonmz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_photonmz_pipeline_en_5.5.0_3.0_1725323103078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_photonmz_pipeline_en_5.5.0_3.0_1725323103078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_photonmz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_photonmz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_photonmz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/photonmz/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_tieincred_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_tieincred_en.md
new file mode 100644
index 00000000000000..719dff5be3c74e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_german_tieincred_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_tieincred XlmRoBertaForTokenClassification from TieIncred
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_tieincred
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_tieincred` is a English model originally trained by TieIncred.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tieincred_en_5.5.0_3.0_1725348395280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tieincred_en_5.5.0_3.0_1725348395280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_tieincred","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_tieincred", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_tieincred|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/TieIncred/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_chaoli_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_chaoli_en.md
new file mode 100644
index 00000000000000..022f6ef4c1e874
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_chaoli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_chaoli XlmRoBertaForTokenClassification from ChaoLi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_chaoli
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_chaoli` is a English model originally trained by ChaoLi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_chaoli_en_5.5.0_3.0_1725374113203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_chaoli_en_5.5.0_3.0_1725374113203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_chaoli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_chaoli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_chaoli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/ChaoLi/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline_en.md
new file mode 100644
index 00000000000000..5cea0129bce7dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline pipeline XlmRoBertaForTokenClassification from ChaoLi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline` is a English model originally trained by ChaoLi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline_en_5.5.0_3.0_1725374205121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline_en_5.5.0_3.0_1725374205121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_chaoli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/ChaoLi/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_jgriffi_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_jgriffi_en.md
new file mode 100644
index 00000000000000..9e296e5b319a25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_jgriffi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_jgriffi XlmRoBertaForTokenClassification from jgriffi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_jgriffi
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_jgriffi` is a English model originally trained by jgriffi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jgriffi_en_5.5.0_3.0_1725373822994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jgriffi_en_5.5.0_3.0_1725373822994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_jgriffi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_jgriffi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_jgriffi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|833.1 MB|
+
+## References
+
+https://huggingface.co/jgriffi/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline_en.md
new file mode 100644
index 00000000000000..05c0927459183e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline pipeline XlmRoBertaForTokenClassification from jgriffi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline` is a English model originally trained by jgriffi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline_en_5.5.0_3.0_1725373912955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline_en_5.5.0_3.0_1725373912955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_jgriffi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.1 MB|
+
+## References
+
+https://huggingface.co/jgriffi/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline_en.md
new file mode 100644
index 00000000000000..46440faf15524b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline pipeline XlmRoBertaForTokenClassification from param-mehta
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline` is a English model originally trained by param-mehta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline_en_5.5.0_3.0_1725322077744.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline_en_5.5.0_3.0_1725322077744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_param_mehta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|820.7 MB|
+
+## References
+
+https://huggingface.co/param-mehta/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline_en.md
new file mode 100644
index 00000000000000..1019d86445eea7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline pipeline XlmRoBertaForTokenClassification from saqidr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline` is a English model originally trained by saqidr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline_en_5.5.0_3.0_1725323270880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline_en_5.5.0_3.0_1725323270880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_saqidr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/saqidr/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_questions_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_questions_en.md
new file mode 100644
index 00000000000000..e55810fe737476
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_questions_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_questions XlmRoBertaEmbeddings from lucazed
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_questions
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_questions` is a English model originally trained by lucazed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_questions_en_5.5.0_3.0_1725353808792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_questions_en_5.5.0_3.0_1725353808792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_questions","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_questions","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_questions|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|976.8 MB|
+
+## References
+
+https://huggingface.co/lucazed/xlm-roberta-base-finetuned-questions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_questions_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_questions_pipeline_en.md
new file mode 100644
index 00000000000000..f5d3663b8a41c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_questions_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_questions_pipeline pipeline XlmRoBertaEmbeddings from lucazed
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_questions_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_questions_pipeline` is a English model originally trained by lucazed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_questions_pipeline_en_5.5.0_3.0_1725353879048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_questions_pipeline_en_5.5.0_3.0_1725353879048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_questions_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_questions_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_questions_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|976.8 MB|
+
+## References
+
+https://huggingface.co/lucazed/xlm-roberta-base-finetuned-questions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_recipe_gk_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_recipe_gk_en.md
new file mode 100644
index 00000000000000..8315b13392fbef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_recipe_gk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_recipe_gk XlmRoBertaForTokenClassification from edwardjross
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_recipe_gk
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_recipe_gk` is a English model originally trained by edwardjross.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_recipe_gk_en_5.5.0_3.0_1725348538985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_recipe_gk_en_5.5.0_3.0_1725348538985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_recipe_gk","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_recipe_gk", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_recipe_gk|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|833.4 MB|
+
+## References
+
+https://huggingface.co/edwardjross/xlm-roberta-base-finetuned-recipe-gk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_recipe_gk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_recipe_gk_pipeline_en.md
new file mode 100644
index 00000000000000..180ec117d42223
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_recipe_gk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_recipe_gk_pipeline pipeline XlmRoBertaForTokenClassification from edwardjross
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_recipe_gk_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_recipe_gk_pipeline` is a English model originally trained by edwardjross.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_recipe_gk_pipeline_en_5.5.0_3.0_1725348608753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_recipe_gk_pipeline_en_5.5.0_3.0_1725348608753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_recipe_gk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_recipe_gk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_recipe_gk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.4 MB|
+
+## References
+
+https://huggingface.co/edwardjross/xlm-roberta-base-finetuned-recipe-gk
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_smcp_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_smcp_en.md
new file mode 100644
index 00000000000000..1e159b47cf44b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_smcp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_smcp XlmRoBertaEmbeddings from sophiaaaa
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_smcp
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_smcp` is a English model originally trained by sophiaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_smcp_en_5.5.0_3.0_1725399917605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_smcp_en_5.5.0_3.0_1725399917605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_smcp","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_smcp","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_smcp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|944.2 MB|
+
+## References
+
+https://huggingface.co/sophiaaaa/xlm-roberta-base-finetuned-smcp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_smcp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_smcp_pipeline_en.md
new file mode 100644
index 00000000000000..4b35d0851b298e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_smcp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_smcp_pipeline pipeline XlmRoBertaEmbeddings from sophiaaaa
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_smcp_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_smcp_pipeline` is a English model originally trained by sophiaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_smcp_pipeline_en_5.5.0_3.0_1725400007893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_smcp_pipeline_en_5.5.0_3.0_1725400007893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_smcp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_smcp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_smcp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|944.2 MB|
+
+## References
+
+https://huggingface.co/sophiaaaa/xlm-roberta-base-finetuned-smcp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_yoruba_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_yoruba_en.md
new file mode 100644
index 00000000000000..75411c8ce46b80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_yoruba_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_yoruba XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_yoruba
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_yoruba` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_yoruba_en_5.5.0_3.0_1725353005919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_yoruba_en_5.5.0_3.0_1725353005919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_yoruba","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_yoruba","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_yoruba|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-yoruba
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_yoruba_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_yoruba_pipeline_en.md
new file mode 100644
index 00000000000000..c3031e15e526b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_yoruba_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_yoruba_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_yoruba_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_yoruba_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_yoruba_pipeline_en_5.5.0_3.0_1725353061982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_yoruba_pipeline_en_5.5.0_3.0_1725353061982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_yoruba_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_yoruba_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_yoruba_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-yoruba
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_zulu_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_zulu_en.md
new file mode 100644
index 00000000000000..5c263f9d32a8eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_zulu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_zulu XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_zulu
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_zulu` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_zulu_en_5.5.0_3.0_1725343398483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_zulu_en_5.5.0_3.0_1725343398483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_zulu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_zulu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_zulu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-zulu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_zulu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_zulu_pipeline_en.md
new file mode 100644
index 00000000000000..6e40a4691944ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_finetuned_zulu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_zulu_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_zulu_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_zulu_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_zulu_pipeline_en_5.5.0_3.0_1725343449529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_zulu_pipeline_en_5.5.0_3.0_1725343449529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_zulu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_zulu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_zulu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-zulu
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_ft_cstwitter_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_ft_cstwitter_en.md
new file mode 100644
index 00000000000000..abec4540ce5cb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_ft_cstwitter_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_ft_cstwitter XlmRoBertaEmbeddings from hadifar
+author: John Snow Labs
+name: xlm_roberta_base_ft_cstwitter
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ft_cstwitter` is a English model originally trained by hadifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_cstwitter_en_5.5.0_3.0_1725353010817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_cstwitter_en_5.5.0_3.0_1725353010817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_ft_cstwitter","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_ft_cstwitter","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ft_cstwitter|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hadifar/xlm-roberta-base-ft-CSTwitter
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_ft_cstwitter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_ft_cstwitter_pipeline_en.md
new file mode 100644
index 00000000000000..40ccd261b495b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_ft_cstwitter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_ft_cstwitter_pipeline pipeline XlmRoBertaEmbeddings from hadifar
+author: John Snow Labs
+name: xlm_roberta_base_ft_cstwitter_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ft_cstwitter_pipeline` is a English model originally trained by hadifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_cstwitter_pipeline_en_5.5.0_3.0_1725353066312.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_cstwitter_pipeline_en_5.5.0_3.0_1725353066312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_ft_cstwitter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_ft_cstwitter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ft_cstwitter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hadifar/xlm-roberta-base-ft-CSTwitter
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_lcc_english_2e_5_42_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_lcc_english_2e_5_42_en.md
new file mode 100644
index 00000000000000..221c64a271a93d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_lcc_english_2e_5_42_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lcc_english_2e_5_42 XlmRoBertaForSequenceClassification from EhsanAghazadeh
+author: John Snow Labs
+name: xlm_roberta_base_lcc_english_2e_5_42
+date: 2024-09-03
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lcc_english_2e_5_42` is a English model originally trained by EhsanAghazadeh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lcc_english_2e_5_42_en_5.5.0_3.0_1725396174972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lcc_english_2e_5_42_en_5.5.0_3.0_1725396174972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lcc_english_2e_5_42","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lcc_english_2e_5_42", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lcc_english_2e_5_42|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|806.8 MB|
+
+## References
+
+https://huggingface.co/EhsanAghazadeh/xlm-roberta-base-lcc-en-2e-5-42
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_longformer_4096_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_longformer_4096_en.md
new file mode 100644
index 00000000000000..2214cad25652b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_longformer_4096_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_longformer_4096 XlmRoBertaEmbeddings from ogaloglu
+author: John Snow Labs
+name: xlm_roberta_base_longformer_4096
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_longformer_4096` is a English model originally trained by ogaloglu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_longformer_4096_en_5.5.0_3.0_1725405740987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_longformer_4096_en_5.5.0_3.0_1725405740987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_longformer_4096","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_longformer_4096","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_longformer_4096|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ogaloglu/xlm-roberta-base-longformer-4096
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_romanian_ner_ronec_ro.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_romanian_ner_ronec_ro.md
new file mode 100644
index 00000000000000..d904ca7cecb335
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_romanian_ner_ronec_ro.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Moldavian, Moldovan, Romanian xlm_roberta_base_romanian_ner_ronec XlmRoBertaForTokenClassification from EvanD
+author: John Snow Labs
+name: xlm_roberta_base_romanian_ner_ronec
+date: 2024-09-03
+tags: [ro, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: ro
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_romanian_ner_ronec` is a Moldavian, Moldovan, Romanian model originally trained by EvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_romanian_ner_ronec_ro_5.5.0_3.0_1725349027926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_romanian_ner_ronec_ro_5.5.0_3.0_1725349027926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_romanian_ner_ronec","ro") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_romanian_ner_ronec", "ro")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_romanian_ner_ronec|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ro|
+|Size:|800.3 MB|
+
+## References
+
+https://huggingface.co/EvanD/xlm-roberta-base-romanian-ner-ronec
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_en.md
new file mode 100644
index 00000000000000..9a4b71cbdb0daf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix XlmRoBertaForQuestionAnswering from chiendvhust
+author: John Snow Labs
+name: xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix` is a English model originally trained by chiendvhust.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_en_5.5.0_3.0_1725379786859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_en_5.5.0_3.0_1725379786859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|876.6 MB|
+
+## References
+
+https://huggingface.co/chiendvhust/xlm-roberta-base-squad2-finetuned-squad2-covidQA-fix
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline_en.md
new file mode 100644
index 00000000000000..4c3092359360e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline pipeline XlmRoBertaForQuestionAnswering from chiendvhust
+author: John Snow Labs
+name: xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline` is a English model originally trained by chiendvhust.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline_en_5.5.0_3.0_1725379861308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline_en_5.5.0_3.0_1725379861308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_squad2_finetuned_squad2_covidqa_fix_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|876.6 MB|
+
+## References
+
+https://huggingface.co/chiendvhust/xlm-roberta-base-squad2-finetuned-squad2-covidQA-fix
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline_en.md
new file mode 100644
index 00000000000000..9e3d1bd154d2b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline_en_5.5.0_3.0_1725379789652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline_en_5.5.0_3.0_1725379789652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_squad2_idkmrc_clickbaitspoiling_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|884.8 MB|
+
+## References
+
+https://huggingface.co/intanm/xlm-roberta-base-squad2-idkmrc-clickbaitspoiling
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_str_semeval2024_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_str_semeval2024_finetuned_en.md
new file mode 100644
index 00000000000000..86a75b8658526b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_str_semeval2024_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_str_semeval2024_finetuned XlmRoBertaEmbeddings from kietnt0603
+author: John Snow Labs
+name: xlm_roberta_base_str_semeval2024_finetuned
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_str_semeval2024_finetuned` is a English model originally trained by kietnt0603.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_str_semeval2024_finetuned_en_5.5.0_3.0_1725353566547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_str_semeval2024_finetuned_en_5.5.0_3.0_1725353566547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_str_semeval2024_finetuned","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_str_semeval2024_finetuned","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_str_semeval2024_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/kietnt0603/xlm-roberta-base-str-semeval2024-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_str_semeval2024_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_str_semeval2024_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..544f3440ded9f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_str_semeval2024_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_str_semeval2024_finetuned_pipeline pipeline XlmRoBertaEmbeddings from kietnt0603
+author: John Snow Labs
+name: xlm_roberta_base_str_semeval2024_finetuned_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_str_semeval2024_finetuned_pipeline` is a English model originally trained by kietnt0603.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_str_semeval2024_finetuned_pipeline_en_5.5.0_3.0_1725353621525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_str_semeval2024_finetuned_pipeline_en_5.5.0_3.0_1725353621525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_str_semeval2024_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_str_semeval2024_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_str_semeval2024_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/kietnt0603/xlm-roberta-base-str-semeval2024-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_xlmberttest_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_xlmberttest_en.md
new file mode 100644
index 00000000000000..b4f4d6cb39a2c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_xlmberttest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_xlmberttest XlmRoBertaEmbeddings from JungHun
+author: John Snow Labs
+name: xlm_roberta_base_xlmberttest
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_xlmberttest` is a English model originally trained by JungHun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_xlmberttest_en_5.5.0_3.0_1725391039027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_xlmberttest_en_5.5.0_3.0_1725391039027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_xlmberttest","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_xlmberttest","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_xlmberttest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|893.7 MB|
+
+## References
+
+https://huggingface.co/JungHun/xlm-roberta-base-xlmberttest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_xlmberttest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_xlmberttest_pipeline_en.md
new file mode 100644
index 00000000000000..479b0951798987
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_base_xlmberttest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_xlmberttest_pipeline pipeline XlmRoBertaEmbeddings from JungHun
+author: John Snow Labs
+name: xlm_roberta_base_xlmberttest_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_xlmberttest_pipeline` is a English model originally trained by JungHun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_xlmberttest_pipeline_en_5.5.0_3.0_1725391148253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_xlmberttest_pipeline_en_5.5.0_3.0_1725391148253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_xlmberttest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_xlmberttest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_xlmberttest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|893.7 MB|
+
+## References
+
+https://huggingface.co/JungHun/xlm-roberta-base-xlmberttest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_large_qa_norwegian_eanderson_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_large_qa_norwegian_eanderson_pipeline_en.md
new file mode 100644
index 00000000000000..1be377eea8c562
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_large_qa_norwegian_eanderson_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_large_qa_norwegian_eanderson_pipeline pipeline XlmRoBertaForQuestionAnswering from eanderson
+author: John Snow Labs
+name: xlm_roberta_large_qa_norwegian_eanderson_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_large_qa_norwegian_eanderson_pipeline` is a English model originally trained by eanderson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_large_qa_norwegian_eanderson_pipeline_en_5.5.0_3.0_1725381131924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_large_qa_norwegian_eanderson_pipeline_en_5.5.0_3.0_1725381131924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_large_qa_norwegian_eanderson_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_large_qa_norwegian_eanderson_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_large_qa_norwegian_eanderson_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|851.3 MB|
+
+## References
+
+https://huggingface.co/eanderson/xlm-roberta-large-qa_norwegian
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_XLM_Turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_XLM_Turkish_pipeline_tr.md
new file mode 100644
index 00000000000000..bbb2265d3d94b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_XLM_Turkish_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish xlm_roberta_qa_XLM_Turkish_pipeline pipeline XlmRoBertaForQuestionAnswering from Aybars
+author: John Snow Labs
+name: xlm_roberta_qa_XLM_Turkish_pipeline
+date: 2024-09-03
+tags: [tr, open_source, pipeline, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_XLM_Turkish_pipeline` is a Turkish model originally trained by Aybars.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_XLM_Turkish_pipeline_tr_5.5.0_3.0_1725381466091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_XLM_Turkish_pipeline_tr_5.5.0_3.0_1725381466091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_XLM_Turkish_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_XLM_Turkish_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_XLM_Turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|791.4 MB|
+
+## References
+
+https://huggingface.co/Aybars/XLM_Turkish
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_XLM_Turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_XLM_Turkish_tr.md
new file mode 100644
index 00000000000000..efe5280362f84f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_XLM_Turkish_tr.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: Turkish XlmRoBertaForQuestionAnswering (from Aybars)
+author: John Snow Labs
+name: xlm_roberta_qa_XLM_Turkish
+date: 2024-09-03
+tags: [tr, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `XLM_Turkish` is a Turkish model originally trained by `Aybars`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_XLM_Turkish_tr_5.5.0_3.0_1725381328014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_XLM_Turkish_tr_5.5.0_3.0_1725381328014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_XLM_Turkish","tr") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_XLM_Turkish","tr")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("tr.answer_question.xlm_roberta").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_XLM_Turkish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|791.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Aybars/XLM_Turkish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_addi_german_xlm_r_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_addi_german_xlm_r_pipeline_de.md
new file mode 100644
index 00000000000000..925bbadbabc97c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_addi_german_xlm_r_pipeline_de.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: German xlm_roberta_qa_addi_german_xlm_r_pipeline pipeline XlmRoBertaForQuestionAnswering from Gantenbein
+author: John Snow Labs
+name: xlm_roberta_qa_addi_german_xlm_r_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Question Answering
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_addi_german_xlm_r_pipeline` is a German model originally trained by Gantenbein.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_german_xlm_r_pipeline_de_5.5.0_3.0_1725380327478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_german_xlm_r_pipeline_de_5.5.0_3.0_1725380327478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_addi_german_xlm_r_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_addi_german_xlm_r_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_addi_german_xlm_r_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|778.0 MB|
+
+## References
+
+https://huggingface.co/Gantenbein/ADDI-DE-XLM-R
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_en.md
new file mode 100644
index 00000000000000..d5472b3e44ead0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from teacookies)
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465520
+date: 2024-09-03
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-base-squad2-24465520` is a English model originally trained by `teacookies`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_en_5.5.0_3.0_1725379847747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_en_5.5.0_3.0_1725379847747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465520","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465520","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.xlm_roberta.base_24465520.by_teacookies").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465520|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|887.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465520
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline_en.md
new file mode 100644
index 00000000000000..c3c5b7159876df
--- /dev/null
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline` is a English model originally trained by teacookies.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline_en_5.5.0_3.0_1725379920346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline_en_5.5.0_3.0_1725379920346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465520_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|887.3 MB|
+
+## References
+
+https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465520
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_en.md
new file mode 100644
index 00000000000000..47b84f3af27bc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_qa_finetuned_small_squad_indonesian_rizal XlmRoBertaForQuestionAnswering from mrizalf7
+author: John Snow Labs
+name: xlm_roberta_qa_finetuned_small_squad_indonesian_rizal
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_finetuned_small_squad_indonesian_rizal` is a English model originally trained by mrizalf7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_en_5.5.0_3.0_1725380147227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_en_5.5.0_3.0_1725380147227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_finetuned_small_squad_indonesian_rizal","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_finetuned_small_squad_indonesian_rizal", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_finetuned_small_squad_indonesian_rizal|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|874.1 MB|
+
+## References
+
+https://huggingface.co/mrizalf7/xlm-roberta-qa-finetuned-small-squad-indonesian-rizal
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline_en.md
new file mode 100644
index 00000000000000..c4aafa58765457
--- /dev/null
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline pipeline XlmRoBertaForQuestionAnswering from mrizalf7
+author: John Snow Labs
+name: xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline` is a English model originally trained by mrizalf7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline_en_5.5.0_3.0_1725380214155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline_en_5.5.0_3.0_1725380214155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_finetuned_small_squad_indonesian_rizal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|874.1 MB|
+
+## References
+
+https://huggingface.co/mrizalf7/xlm-roberta-qa-finetuned-small-squad-indonesian-rizal
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_squadv2_xlm_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_squadv2_xlm_roberta_base_en.md
new file mode 100644
index 00000000000000..183252f963d544
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_squadv2_xlm_roberta_base_en.md
@@ -0,0 +1,107 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from seongju)
+author: John Snow Labs
+name: xlm_roberta_qa_squadv2_xlm_roberta_base
+date: 2024-09-03
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squadv2-xlm-roberta-base` is a English model originally trained by `seongju`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_squadv2_xlm_roberta_base_en_5.5.0_3.0_1725380356583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_squadv2_xlm_roberta_base_en_5.5.0_3.0_1725380356583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_squadv2_xlm_roberta_base","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_squadv2_xlm_roberta_base","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.xlm_roberta.base_v2").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_squadv2_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|875.0 MB|
+
+## References
+
+References
+
+- https://huggingface.co/seongju/squadv2-xlm-roberta-base
+- https://rajpurkar.github.io/SQuAD-explorer/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..96847eca5c6244
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline pipeline XlmRoBertaForQuestionAnswering from seongju
+author: John Snow Labs
+name: xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline` is a English model originally trained by seongju.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline_en_5.5.0_3.0_1725380426028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline_en_5.5.0_3.0_1725380426028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_squadv2_xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|875.0 MB|
+
+## References
+
+https://huggingface.co/seongju/squadv2-xlm-roberta-base
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_chinese_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_chinese_pipeline_zh.md
new file mode 100644
index 00000000000000..992ea55b63ada1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_chinese_pipeline_zh.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Chinese xlm_roberta_qa_xlm_roberta_base_chinese_pipeline pipeline XlmRoBertaForQuestionAnswering from bhavikardeshna
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_chinese_pipeline
+date: 2024-09-03
+tags: [zh, open_source, pipeline, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_chinese_pipeline` is a Chinese model originally trained by bhavikardeshna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_chinese_pipeline_zh_5.5.0_3.0_1725380015355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_chinese_pipeline_zh_5.5.0_3.0_1725380015355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_chinese_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_chinese_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_chinese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|887.6 MB|
+
+## References
+
+https://huggingface.co/bhavikardeshna/xlm-roberta-base-chinese
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_chinese_zh.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_chinese_zh.md
new file mode 100644
index 00000000000000..6b53a488739dba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_chinese_zh.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: Chinese XlmRoBertaForQuestionAnswering (from bhavikardeshna)
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_chinese
+date: 2024-09-03
+tags: [zh, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-chinese` is a Chinese model originally trained by `bhavikardeshna`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_chinese_zh_5.5.0_3.0_1725379951783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_chinese_zh_5.5.0_3.0_1725379951783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_chinese","zh") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_xlm_roberta_base_chinese","zh")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("zh.answer_question.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_chinese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|zh|
+|Size:|887.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/bhavikardeshna/xlm-roberta-base-chinese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_finetune_qa_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_finetune_qa_en.md
new file mode 100644
index 00000000000000..98add19fadcec5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_finetune_qa_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from airesearch)
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_finetune_qa
+date: 2024-09-03
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetune-qa` is a English model originally trained by `airesearch`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_finetune_qa_en_5.5.0_3.0_1725381111728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_finetune_qa_en_5.5.0_3.0_1725381111728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_finetune_qa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_xlm_roberta_base_finetune_qa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_finetune_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|864.0 MB|
+
+## References
+
+References
+
+- https://huggingface.co/airesearch/xlm-roberta-base-finetune-qa
+- https://wandb.ai/cstorm125/wangchanberta-qa
+- https://github.com/vistec-AI/thai2transformers/blob/dev/scripts/downstream/train_question_answering_lm_finetuning.py
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline_en.md
new file mode 100644
index 00000000000000..c1c4886f38c0d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline pipeline XlmRoBertaForQuestionAnswering from airesearch
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline` is a English model originally trained by airesearch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline_en_5.5.0_3.0_1725381181751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline_en_5.5.0_3.0_1725381181751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_finetune_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|864.0 MB|
+
+## References
+
+https://huggingface.co/airesearch/xlm-roberta-base-finetune-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_hindi_hi.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_hindi_hi.md
new file mode 100644
index 00000000000000..d5f2bf361b0608
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_hindi_hi.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: Hindi XlmRoBertaForQuestionAnswering (from bhavikardeshna)
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_hindi
+date: 2024-09-03
+tags: [hi, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-hindi` is a Hindi model originally trained by `bhavikardeshna`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_hindi_hi_5.5.0_3.0_1725379421212.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_hindi_hi_5.5.0_3.0_1725379421212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_hindi","hi") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_xlm_roberta_base_hindi","hi")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("hi.answer_question.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_hindi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|hi|
+|Size:|884.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/bhavikardeshna/xlm-roberta-base-hindi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_hindi_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_hindi_pipeline_hi.md
new file mode 100644
index 00000000000000..d712adc6ab0a3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_hindi_pipeline_hi.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hindi xlm_roberta_qa_xlm_roberta_base_hindi_pipeline pipeline XlmRoBertaForQuestionAnswering from bhavikardeshna
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_hindi_pipeline
+date: 2024-09-03
+tags: [hi, open_source, pipeline, onnx]
+task: Question Answering
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_hindi_pipeline` is a Hindi model originally trained by bhavikardeshna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_hindi_pipeline_hi_5.5.0_3.0_1725379483103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_hindi_pipeline_hi_5.5.0_3.0_1725379483103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_hindi_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_hindi_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_hindi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|884.8 MB|
+
+## References
+
+https://huggingface.co/bhavikardeshna/xlm-roberta-base-hindi
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_xquad_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_xquad_en.md
new file mode 100644
index 00000000000000..bdf2896e44bb85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_xquad_en.md
@@ -0,0 +1,107 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from alon-albalak)
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_xquad
+date: 2024-09-03
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-xquad` is a English model originally trained by `alon-albalak`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_xquad_en_5.5.0_3.0_1725380392914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_xquad_en_5.5.0_3.0_1725380392914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_xquad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_xlm_roberta_base_xquad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.xquad.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_xquad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|846.9 MB|
+
+## References
+
+References
+
+- https://huggingface.co/alon-albalak/xlm-roberta-base-xquad
+- https://github.com/deepmind/xquad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_xquad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_xquad_pipeline_en.md
new file mode 100644
index 00000000000000..836a54643791bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_base_xquad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_xlm_roberta_base_xquad_pipeline pipeline XlmRoBertaForQuestionAnswering from alon-albalak
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_xquad_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_xquad_pipeline` is a English model originally trained by alon-albalak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_xquad_pipeline_en_5.5.0_3.0_1725380512909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_xquad_pipeline_en_5.5.0_3.0_1725380512909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_xquad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_xquad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_xquad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|846.9 MB|
+
+## References
+
+https://huggingface.co/alon-albalak/xlm-roberta-base-xquad
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_est_qa_et.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_est_qa_et.md
new file mode 100644
index 00000000000000..21d8a9159d0422
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_est_qa_et.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: Estonian XlmRoBertaForQuestionAnswering (from anukaver)
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_est_qa
+date: 2024-09-03
+tags: [open_source, question_answering, xlmroberta, et, onnx]
+task: Question Answering
+language: et
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-est-qa` is a Estonian model originally trained by `anukaver`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_est_qa_et_5.5.0_3.0_1725381470622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_est_qa_et_5.5.0_3.0_1725381470622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_est_qa","et") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context"))
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_xlm_roberta_est_qa","et")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("et.answer_question.xlm_roberta.by_anukaver").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_est_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|et|
+|Size:|882.5 MB|
+
+## References
+
+References
+
+- https://huggingface.co/anukaver/xlm-roberta-est-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_est_qa_pipeline_et.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_est_qa_pipeline_et.md
new file mode 100644
index 00000000000000..3e76f1325d2b0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlm_roberta_est_qa_pipeline_et.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Estonian xlm_roberta_qa_xlm_roberta_est_qa_pipeline pipeline XlmRoBertaForQuestionAnswering from anukaver
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_est_qa_pipeline
+date: 2024-09-03
+tags: [et, open_source, pipeline, onnx]
+task: Question Answering
+language: et
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_est_qa_pipeline` is a Estonian model originally trained by anukaver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_est_qa_pipeline_et_5.5.0_3.0_1725381535902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_est_qa_pipeline_et_5.5.0_3.0_1725381535902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_est_qa_pipeline", lang = "et")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_est_qa_pipeline", lang = "et")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_est_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|et|
+|Size:|882.5 MB|
+
+## References
+
+https://huggingface.co/anukaver/xlm-roberta-est-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_is.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_is.md
new file mode 100644
index 00000000000000..919226ab9b0269
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_is.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Icelandic xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan XlmRoBertaForQuestionAnswering from saattrupdan
+author: John Snow Labs
+name: xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan
+date: 2024-09-03
+tags: [is, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: is
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan` is a Icelandic model originally trained by saattrupdan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_is_5.5.0_3.0_1725379685629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_is_5.5.0_3.0_1725379685629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan","is") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan", "is")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|is|
+|Size:|874.4 MB|
+
+## References
+
+https://huggingface.co/saattrupdan/xlmr-base-texas-squad-is
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline_is.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline_is.md
new file mode 100644
index 00000000000000..da6a52d4b6cb0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline_is.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Icelandic xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline pipeline XlmRoBertaForQuestionAnswering from saattrupdan
+author: John Snow Labs
+name: xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline
+date: 2024-09-03
+tags: [is, open_source, pipeline, onnx]
+task: Question Answering
+language: is
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline` is a Icelandic model originally trained by saattrupdan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline_is_5.5.0_3.0_1725379752404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline_is_5.5.0_3.0_1725379752404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline", lang = "is")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline", lang = "is")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlmr_base_texas_squad_icelandic_icelandic_saattrupdan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|is|
+|Size:|874.4 MB|
+
+## References
+
+https://huggingface.co/saattrupdan/xlmr-base-texas-squad-is
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_squad_nepali_translated_squad_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_squad_nepali_translated_squad_en.md
new file mode 100644
index 00000000000000..0df9676ad7e3e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_squad_nepali_translated_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_squad_nepali_translated_squad XlmRoBertaForQuestionAnswering from Yunika
+author: John Snow Labs
+name: xlm_roberta_squad_nepali_translated_squad
+date: 2024-09-03
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_squad_nepali_translated_squad` is a English model originally trained by Yunika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_squad_nepali_translated_squad_en_5.5.0_3.0_1725381138758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_squad_nepali_translated_squad_en_5.5.0_3.0_1725381138758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_squad_nepali_translated_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_squad_nepali_translated_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_squad_nepali_translated_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|880.6 MB|
+
+## References
+
+https://huggingface.co/Yunika/xlm-roberta-squad-nepali-translated-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_english_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_english_en.md
new file mode 100644
index 00000000000000..63e052f6449fd3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_english XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_english
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_english` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_english_en_5.5.0_3.0_1725343330996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_english_en_5.5.0_3.0_1725343330996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_english","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_english","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_english_pipeline_en.md
new file mode 100644
index 00000000000000..47d9d1bccbcb8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_english_pipeline pipeline XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_english_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_english_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_english_pipeline_en_5.5.0_3.0_1725343640630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_english_pipeline_en_5.5.0_3.0_1725343640630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_trimmed_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_trimmed_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_italian_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_italian_en.md
new file mode 100644
index 00000000000000..7d199e365736df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_italian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_italian XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_italian
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_italian` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_italian_en_5.5.0_3.0_1725353253583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_italian_en_5.5.0_3.0_1725353253583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_italian","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_italian","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_italian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|526.3 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_italian_pipeline_en.md
new file mode 100644
index 00000000000000..951acd9fe28fd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_italian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_italian_pipeline pipeline XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_italian_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_italian_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_italian_pipeline_en_5.5.0_3.0_1725353412639.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_italian_pipeline_en_5.5.0_3.0_1725353412639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_trimmed_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_trimmed_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|526.3 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_portuguese_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_portuguese_en.md
new file mode 100644
index 00000000000000..c2b4ac88824654
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_portuguese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_portuguese XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_portuguese
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_portuguese` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_portuguese_en_5.5.0_3.0_1725353598784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_portuguese_en_5.5.0_3.0_1725353598784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_portuguese","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_portuguese","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_portuguese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|520.4 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-pt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_portuguese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_portuguese_pipeline_en.md
new file mode 100644
index 00000000000000..ddafbeae520388
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_v_base_trimmed_portuguese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_portuguese_pipeline pipeline XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_portuguese_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_portuguese_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_portuguese_pipeline_en_5.5.0_3.0_1725353757259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_portuguese_pipeline_en_5.5.0_3.0_1725353757259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_trimmed_portuguese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_trimmed_portuguese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_portuguese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|520.4 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-pt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmr_large_toxicity_classifier_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmr_large_toxicity_classifier_pipeline_xx.md
new file mode 100644
index 00000000000000..c180120e6292c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmr_large_toxicity_classifier_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmr_large_toxicity_classifier_pipeline pipeline XlmRoBertaForSequenceClassification from textdetox
+author: John Snow Labs
+name: xlmr_large_toxicity_classifier_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_large_toxicity_classifier_pipeline` is a Multilingual model originally trained by textdetox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_large_toxicity_classifier_pipeline_xx_5.5.0_3.0_1725395226512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_large_toxicity_classifier_pipeline_xx_5.5.0_3.0_1725395226512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_large_toxicity_classifier_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_large_toxicity_classifier_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_large_toxicity_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|876.6 MB|
+
+## References
+
+https://huggingface.co/textdetox/xlmr-large-toxicity-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmr_large_toxicity_classifier_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmr_large_toxicity_classifier_xx.md
new file mode 100644
index 00000000000000..245981351571b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmr_large_toxicity_classifier_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual xlmr_large_toxicity_classifier XlmRoBertaForSequenceClassification from textdetox
+author: John Snow Labs
+name: xlmr_large_toxicity_classifier
+date: 2024-09-03
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_large_toxicity_classifier` is a Multilingual model originally trained by textdetox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_large_toxicity_classifier_xx_5.5.0_3.0_1725395127630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_large_toxicity_classifier_xx_5.5.0_3.0_1725395127630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_large_toxicity_classifier","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_large_toxicity_classifier", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_large_toxicity_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|876.6 MB|
+
+## References
+
+https://huggingface.co/textdetox/xlmr-large-toxicity-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmr_ner_slavic_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmr_ner_slavic_pipeline_xx.md
new file mode 100644
index 00000000000000..841106c277f752
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmr_ner_slavic_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmr_ner_slavic_pipeline pipeline XlmRoBertaForTokenClassification from ivlcic
+author: John Snow Labs
+name: xlmr_ner_slavic_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_ner_slavic_pipeline` is a Multilingual model originally trained by ivlcic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_ner_slavic_pipeline_xx_5.5.0_3.0_1725373155144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_ner_slavic_pipeline_xx_5.5.0_3.0_1725373155144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_ner_slavic_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_ner_slavic_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_ner_slavic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|863.7 MB|
+
+## References
+
+https://huggingface.co/ivlcic/xlmr-ner-slavic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmr_ner_slavic_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmr_ner_slavic_xx.md
new file mode 100644
index 00000000000000..4573ed2fe60588
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmr_ner_slavic_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual xlmr_ner_slavic XlmRoBertaForTokenClassification from ivlcic
+author: John Snow Labs
+name: xlmr_ner_slavic
+date: 2024-09-03
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_ner_slavic` is a Multilingual model originally trained by ivlcic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_ner_slavic_xx_5.5.0_3.0_1725373039512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_ner_slavic_xx_5.5.0_3.0_1725373039512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlmr_ner_slavic","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_ner_slavic", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_ner_slavic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|863.7 MB|
+
+## References
+
+https://huggingface.co/ivlcic/xlmr-ner-slavic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmr_qa_extraction_finnish_en.md b/docs/_posts/ahmedlone127/2024-09-03-xlmr_qa_extraction_finnish_en.md
new file mode 100644
index 00000000000000..6fe6c7c2976286
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmr_qa_extraction_finnish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_qa_extraction_finnish XlmRoBertaForTokenClassification from TurkuNLP
+author: John Snow Labs
+name: xlmr_qa_extraction_finnish
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_qa_extraction_finnish` is a English model originally trained by TurkuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_qa_extraction_finnish_en_5.5.0_3.0_1725322074712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_qa_extraction_finnish_en_5.5.0_3.0_1725322074712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlmr_qa_extraction_finnish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_qa_extraction_finnish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_qa_extraction_finnish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|836.6 MB|
+
+## References
+
+https://huggingface.co/TurkuNLP/xlmr-qa-extraction-fi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_danish_xlmr_ned_da.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_danish_xlmr_ned_da.md
new file mode 100644
index 00000000000000..e561106e0c12fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_danish_xlmr_ned_da.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Danish xlmroberta_classifier_danish_xlmr_ned XlmRoBertaForSequenceClassification from DaNLP
+author: John Snow Labs
+name: xlmroberta_classifier_danish_xlmr_ned
+date: 2024-09-03
+tags: [da, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_classifier_danish_xlmr_ned` is a Danish model originally trained by DaNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_danish_xlmr_ned_da_5.5.0_3.0_1725327993845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_danish_xlmr_ned_da_5.5.0_3.0_1725327993845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_classifier_danish_xlmr_ned","da") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_classifier_danish_xlmr_ned", "da")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_classifier_danish_xlmr_ned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|da|
+|Size:|881.6 MB|
+
+## References
+
+https://huggingface.co/DaNLP/da-xlmr-ned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_deoffxlmr_mono_malyalam_ml.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_deoffxlmr_mono_malyalam_ml.md
new file mode 100644
index 00000000000000..4a928190042a24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_deoffxlmr_mono_malyalam_ml.md
@@ -0,0 +1,105 @@
+---
+layout: model
+title: Malayalam XlmRobertaForSequenceClassification Cased model (from Hate-speech-CNERG)
+author: John Snow Labs
+name: xlmroberta_classifier_deoffxlmr_mono_malyalam
+date: 2024-09-03
+tags: [ml, open_source, xlm_roberta, sequence_classification, classification, onnx]
+task: Text Classification
+language: ml
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `deoffxlmr-mono-malyalam` is a Malayalam model originally trained by `Hate-speech-CNERG`.
+
+## Predicted Entities
+
+`Not_offensive`, `Off_target_group`, `Profanity`, `Off_target_ind`, `Not_in_intended_language`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_deoffxlmr_mono_malyalam_ml_5.5.0_3.0_1725395830965.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_deoffxlmr_mono_malyalam_ml_5.5.0_3.0_1725395830965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+seq_classifier = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_classifier_deoffxlmr_mono_malyalam","ml") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val seq_classifier = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_classifier_deoffxlmr_mono_malyalam","ml")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ml.classify.xlmr_roberta").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_classifier_deoffxlmr_mono_malyalam|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ml|
+|Size:|1.0 GB|
+
+## References
+
+References
+
+- https://huggingface.co/Hate-speech-CNERG/deoffxlmr-mono-malyalam
+- https://www.aclweb.org/anthology/2021.dravidianlangtech-1.38/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline_ml.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline_ml.md
new file mode 100644
index 00000000000000..c4acff6b0f7e04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline_ml.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Malayalam xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline pipeline XlmRoBertaForSequenceClassification from Hate-speech-CNERG
+author: John Snow Labs
+name: xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline
+date: 2024-09-03
+tags: [ml, open_source, pipeline, onnx]
+task: Text Classification
+language: ml
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline` is a Malayalam model originally trained by Hate-speech-CNERG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline_ml_5.5.0_3.0_1725395888828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline_ml_5.5.0_3.0_1725395888828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline", lang = "ml")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline", lang = "ml")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_classifier_deoffxlmr_mono_malyalam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ml|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Hate-speech-CNERG/deoffxlmr-mono-malyalam
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline_sw.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline_sw.md
new file mode 100644
index 00000000000000..0defc269272dc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline_sw.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Swahili (macrolanguage) xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline
+date: 2024-09-03
+tags: [sw, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: sw
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline` is a Swahili (macrolanguage) model originally trained by mbeukman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline_sw_5.5.0_3.0_1725348227617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline_sw_5.5.0_3.0_1725348227617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline", lang = "sw")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline", lang = "sw")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sw|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-igbo-finetuned-ner-swahili
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_sw.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_sw.md
new file mode 100644
index 00000000000000..33dc517ea4ee84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_sw.md
@@ -0,0 +1,115 @@
+---
+layout: model
+title: Swahili XLMRobertaForTokenClassification Base Cased model (from mbeukman)
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili
+date: 2024-09-03
+tags: [sw, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: sw
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-igbo-finetuned-ner-swahili` is a Swahili model originally trained by `mbeukman`.
+
+## Predicted Entities
+
+`PER`, `DATE`, `ORG`, `LOC`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_sw_5.5.0_3.0_1725348176471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili_sw_5.5.0_3.0_1725348176471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili","sw") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili","sw")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("sw.ner.xlmr_roberta.base_finetuned_igbo.by_mbeukman").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_igbo_finetuned_ner_swahili|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|sw|
+|Size:|1.0 GB|
+
+## References
+
+References
+
+- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-igbo-finetuned-ner-swahili
+- https://arxiv.org/abs/2103.11811
+- https://github.com/Michael-Beukman/NERTransfer
+- https://github.com/masakhane-io/masakhane-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_naija_pcm.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_naija_pcm.md
new file mode 100644
index 00000000000000..046c72694237ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_finetuned_naija_pcm.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: Nigerian Pidgin XLMRobertaForTokenClassification Base Cased model (from mbeukman)
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_naija
+date: 2024-09-03
+tags: [pcm, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: pcm
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-ner-naija` is a Nigerian Pidgin model originally trained by `mbeukman`.
+
+## Predicted Entities
+
+`ORG`, `LOC`, `PER`, `DATE`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_naija_pcm_5.5.0_3.0_1725373020269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_naija_pcm_5.5.0_3.0_1725373020269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_naija","pcm") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_naija","pcm")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("pcm.ner.xlmr_roberta.base_finetuned").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_naija|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|pcm|
+|Size:|778.0 MB|
+
+## References
+
+References
+
+- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-ner-naija
+- https://arxiv.org/abs/2103.11811
+- https://github.com/Michael-Beukman/NERTransfer
+- https://www.apache.org/licenses/LICENSE-2.0
+- https://github.com/Michael-Beukman/NERTransfer
+- https://github.com/masakhane-io/masakhane-ner
+- https://arxiv.org/pdf/2103.11811.pdf
+- https://arxiv.org/abs/2103.11811
+- https://arxiv.org/abs/2103.11811
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_indonesian_id.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_indonesian_id.md
new file mode 100644
index 00000000000000..124ab304bfd846
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_indonesian_id.md
@@ -0,0 +1,112 @@
+---
+layout: model
+title: Indonesian XLMRobertaForTokenClassification Base Cased model (from cahya)
+author: John Snow Labs
+name: xlmroberta_ner_base_indonesian
+date: 2024-09-03
+tags: [id, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-indonesian-NER` is a Indonesian model originally trained by `cahya`.
+
+## Predicted Entities
+
+`QTY`, `WOA`, `REG`, `PER`, `PRC`, `LOC`, `ORD`, `MON`, `GPE`, `DAT`, `LAW`, `CRD`, `EVT`, `LAN`, `FAC`, `ORG`, `TIM`, `PRD`, `NOR`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_indonesian_id_5.5.0_3.0_1725349666419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_indonesian_id_5.5.0_3.0_1725349666419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_indonesian","id") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_indonesian","id")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("id.ner.xlmr_roberta.base").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_indonesian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|id|
+|Size:|791.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/cahya/xlm-roberta-base-indonesian-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_indonesian_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_indonesian_pipeline_id.md
new file mode 100644
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+---
+layout: model
+title: Indonesian xlmroberta_ner_base_indonesian_pipeline pipeline XlmRoBertaForTokenClassification from cahya
+author: John Snow Labs
+name: xlmroberta_ner_base_indonesian_pipeline
+date: 2024-09-03
+tags: [id, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_indonesian_pipeline` is a Indonesian model originally trained by cahya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_indonesian_pipeline_id_5.5.0_3.0_1725349799501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_indonesian_pipeline_id_5.5.0_3.0_1725349799501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_base_indonesian_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_base_indonesian_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_indonesian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|791.6 MB|
+
+## References
+
+https://huggingface.co/cahya/xlm-roberta-base-indonesian-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_sadilar_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_sadilar_pipeline_xx.md
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index 00000000000000..50b2c1647788d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_sadilar_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmroberta_ner_base_sadilar_pipeline pipeline XlmRoBertaForTokenClassification from Davlan
+author: John Snow Labs
+name: xlmroberta_ner_base_sadilar_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_sadilar_pipeline` is a Multilingual model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_sadilar_pipeline_xx_5.5.0_3.0_1725374150621.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_sadilar_pipeline_xx_5.5.0_3.0_1725374150621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_base_sadilar_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_base_sadilar_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_sadilar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|806.2 MB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-sadilar-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_sadilar_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_sadilar_xx.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_base_sadilar_xx.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: Multilingual XLMRobertaForTokenClassification Base Cased model (from Davlan)
+author: John Snow Labs
+name: xlmroberta_ner_base_sadilar
+date: 2024-09-03
+tags: [xx, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-sadilar-ner` is a Multilingual model originally trained by `Davlan`.
+
+## Predicted Entities
+
+`DATE`, `PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_sadilar_xx_5.5.0_3.0_1725374007693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_sadilar_xx_5.5.0_3.0_1725374007693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_sadilar","xx") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_sadilar","xx")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("xx.ner.xlmr_roberta.base.by_davlan").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_sadilar|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|806.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Davlan/xlm-roberta-base-sadilar-ner
+- https://www.sadilar.org/index.php/en/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..3f22cbc20ef666
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+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from hugsao123
+author: John Snow Labs
+name: xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline` is a German model originally trained by hugsao123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725372844558.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725372844558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_hugsao123_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/hugsao123/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_iis2009002_base_finetuned_panx_it.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_iis2009002_base_finetuned_panx_it.md
new file mode 100644
index 00000000000000..3f30b1e68c3d24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_iis2009002_base_finetuned_panx_it.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: Italian XLMRobertaForTokenClassification Base Cased model (from iis2009002)
+author: John Snow Labs
+name: xlmroberta_ner_iis2009002_base_finetuned_panx
+date: 2024-09-03
+tags: [it, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-it` is a Italian model originally trained by `iis2009002`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_iis2009002_base_finetuned_panx_it_5.5.0_3.0_1725373904211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_iis2009002_base_finetuned_panx_it_5.5.0_3.0_1725373904211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_iis2009002_base_finetuned_panx","it") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_iis2009002_base_finetuned_panx","it")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("it.ner.xlmr_roberta.xtreme.base_finetuned.by_iis2009002").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_iis2009002_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|it|
+|Size:|828.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/iis2009002/xlm-roberta-base-finetuned-panx-it
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline_it.md
new file mode 100644
index 00000000000000..4c108b2a27b0f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline_it.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Italian xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from iis2009002
+author: John Snow Labs
+name: xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline
+date: 2024-09-03
+tags: [it, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline` is a Italian model originally trained by iis2009002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline_it_5.5.0_3.0_1725373997034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline_it_5.5.0_3.0_1725373997034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_iis2009002_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/iis2009002/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jamie613_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jamie613_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..c9777f5f500e3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jamie613_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from jamie613)
+author: John Snow Labs
+name: xlmroberta_ner_jamie613_base_finetuned_panx
+date: 2024-09-03
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `jamie613`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jamie613_base_finetuned_panx_de_5.5.0_3.0_1725348856401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jamie613_base_finetuned_panx_de_5.5.0_3.0_1725348856401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jamie613_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jamie613_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_jamie613").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_jamie613_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/jamie613/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jamie613_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jamie613_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..5453ebafd1c013
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jamie613_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_jamie613_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from jamie613
+author: John Snow Labs
+name: xlmroberta_ner_jamie613_base_finetuned_panx_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_jamie613_base_finetuned_panx_pipeline` is a German model originally trained by jamie613.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jamie613_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725348923575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jamie613_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725348923575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_jamie613_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_jamie613_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_jamie613_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/jamie613/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jboever_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jboever_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..bfa4fc913761ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jboever_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_jboever_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from jdeboever
+author: John Snow Labs
+name: xlmroberta_ner_jboever_base_finetuned_panx_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_jboever_base_finetuned_panx_pipeline` is a German model originally trained by jdeboever.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jboever_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725348412055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jboever_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725348412055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_jboever_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_jboever_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_jboever_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/jdeboever/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jdang_base_finetuned_panx_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jdang_base_finetuned_panx_pipeline_xx.md
new file mode 100644
index 00000000000000..8f619d991cf1dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jdang_base_finetuned_panx_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmroberta_ner_jdang_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from jdang
+author: John Snow Labs
+name: xlmroberta_ner_jdang_base_finetuned_panx_pipeline
+date: 2024-09-03
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_jdang_base_finetuned_panx_pipeline` is a Multilingual model originally trained by jdang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jdang_base_finetuned_panx_pipeline_xx_5.5.0_3.0_1725372223082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jdang_base_finetuned_panx_pipeline_xx_5.5.0_3.0_1725372223082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_jdang_base_finetuned_panx_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_jdang_base_finetuned_panx_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_jdang_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/jdang/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jdang_base_finetuned_panx_xx.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jdang_base_finetuned_panx_xx.md
new file mode 100644
index 00000000000000..3f18c2ef60a0e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_jdang_base_finetuned_panx_xx.md
@@ -0,0 +1,112 @@
+---
+layout: model
+title: Multilingual XLMRobertaForTokenClassification Base Cased model (from jdang)
+author: John Snow Labs
+name: xlmroberta_ner_jdang_base_finetuned_panx
+date: 2024-09-03
+tags: [de, fr, open_source, xlm_roberta, ner, xx, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de-fr` is a Multilingual model originally trained by `jdang`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jdang_base_finetuned_panx_xx_5.5.0_3.0_1725372139746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jdang_base_finetuned_panx_xx_5.5.0_3.0_1725372139746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jdang_base_finetuned_panx","xx") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jdang_base_finetuned_panx","xx")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("xx.ner.xlmr_roberta.base_finetuned.by_jdang").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_jdang_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|858.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/jdang/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..857ddd80b570ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from mertyrgn
+author: John Snow Labs
+name: xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline` is a German model originally trained by mertyrgn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725347852742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725347852742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_mertyrgn_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/mertyrgn/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_naam_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_naam_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..1816320bb45eab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_naam_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from naam)
+author: John Snow Labs
+name: xlmroberta_ner_naam_base_finetuned_panx
+date: 2024-09-03
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `naam`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_naam_base_finetuned_panx_de_5.5.0_3.0_1725348684876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_naam_base_finetuned_panx_de_5.5.0_3.0_1725348684876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_naam_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_naam_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_naam").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_naam_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/naam/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_netoass_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_netoass_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..da3f0cca6cca07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_netoass_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from netoass)
+author: John Snow Labs
+name: xlmroberta_ner_netoass_base_finetuned_panx
+date: 2024-09-03
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `netoass`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_netoass_base_finetuned_panx_de_5.5.0_3.0_1725349746063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_netoass_base_finetuned_panx_de_5.5.0_3.0_1725349746063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_netoass_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_netoass_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_netoass").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_netoass_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/netoass/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_netoass_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_netoass_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..b23c00553a11f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_netoass_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_netoass_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from netoass
+author: John Snow Labs
+name: xlmroberta_ner_netoass_base_finetuned_panx_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_netoass_base_finetuned_panx_pipeline` is a German model originally trained by netoass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_netoass_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725349812662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_netoass_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725349812662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_netoass_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_netoass_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_netoass_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/netoass/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..d5e565d8d813f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from transformersbook
+author: John Snow Labs
+name: xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline` is a German model originally trained by transformersbook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725372764796.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725372764796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_transformersbook_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/transformersbook/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_ig.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_ig.md
new file mode 100644
index 00000000000000..5f60c1f7f01f10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_ig.md
@@ -0,0 +1,110 @@
+---
+layout: model
+title: Igbo Named Entity Recognition (from mbeukman)
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo
+date: 2024-09-03
+tags: [xlm_roberta, ner, token_classification, ig, open_source, onnx]
+task: Named Entity Recognition
+language: ig
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Named Entity Recognition model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-igbo-finetuned-ner-igbo` is a Igbo model orginally trained by `mbeukman`.
+
+## Predicted Entities
+
+`PER`, `ORG`, `LOC`, `DATE`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_ig_5.5.0_3.0_1725372606474.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_ig_5.5.0_3.0_1725372606474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo","ig") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["Ahụrụ m n'anya na-atọ m ụtọ"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo","ig") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("Ahụrụ m n'anya na-atọ m ụtọ").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ig|
+|Size:|1.0 GB|
+
+## References
+
+References
+
+- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-igbo-finetuned-ner-igbo
+- https://arxiv.org/abs/2103.11811
+- https://github.com/Michael-Beukman/NERTransfer
+- https://www.apache.org/licenses/LICENSE-2.0
+- https://github.com/Michael-Beukman/NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline_ig.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline_ig.md
new file mode 100644
index 00000000000000..ad0a94398c62b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline_ig.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Igbo xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline
+date: 2024-09-03
+tags: [ig, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ig
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline` is a Igbo model originally trained by mbeukman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline_ig_5.5.0_3.0_1725372665671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline_ig_5.5.0_3.0_1725372665671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline", lang = "ig")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline", lang = "ig")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_igbo_finetuned_ner_igbo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ig|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-igbo-finetuned-ner-igbo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_ha.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_ha.md
new file mode 100644
index 00000000000000..b5b00c282d36f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_ha.md
@@ -0,0 +1,116 @@
+---
+layout: model
+title: Hausa Named Entity Recognition (from mbeukman)
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa
+date: 2024-09-03
+tags: [xlm_roberta, ner, token_classification, ha, open_source, onnx]
+task: Named Entity Recognition
+language: ha
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Named Entity Recognition model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-swahili-finetuned-ner-hausa` is a Hausa model orginally trained by `mbeukman`.
+
+## Predicted Entities
+
+`PER`, `ORG`, `LOC`, `DATE`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_ha_5.5.0_3.0_1725372226794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_ha_5.5.0_3.0_1725372226794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa","ha") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["Ina son Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa","ha") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("Ina son Spark NLP").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ha.ner.xlmr_roberta.base_finetuned_swahilis.by_mbeukman").predict("""Ina son Spark NLP""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ha|
+|Size:|1.0 GB|
+
+## References
+
+References
+
+- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-swahili-finetuned-ner-hausa
+- https://arxiv.org/abs/2103.11811
+- https://github.com/Michael-Beukman/NERTransfer
+- https://www.apache.org/licenses/LICENSE-2.0
+- https://github.com/Michael-Beukman
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline_ha.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline_ha.md
new file mode 100644
index 00000000000000..2b64e9baab5066
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline_ha.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hausa xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline
+date: 2024-09-03
+tags: [ha, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ha
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline` is a Hausa model originally trained by mbeukman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline_ha_5.5.0_3.0_1725372302529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline_ha_5.5.0_3.0_1725372302529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline", lang = "ha")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline", lang = "ha")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_swahili_finetuned_ner_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ha|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-swahili-finetuned-ner-hausa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_wikiann_ner_ig.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_wikiann_ner_ig.md
new file mode 100644
index 00000000000000..cd6260f1266706
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_wikiann_ner_ig.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: Igbo Named Entity Recognition (from Davlan)
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_wikiann_ner
+date: 2024-09-03
+tags: [xlm_roberta, ner, token_classification, ig, open_source, onnx]
+task: Named Entity Recognition
+language: ig
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Named Entity Recognition model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-wikiann-ner` is a Igbo model orginally trained by `Davlan`.
+
+## Predicted Entities
+
+`PER`, `ORG`, `LOC`, `DATE`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_wikiann_ner_ig_5.5.0_3.0_1725372184630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_wikiann_ner_ig_5.5.0_3.0_1725372184630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_wikiann_ner","ig") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["Ahụrụ m n'anya na-atọ m ụtọ"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_wikiann_ner","ig") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("Ahụrụ m n'anya na-atọ m ụtọ").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_wikiann_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ig|
+|Size:|858.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Davlan/xlm-roberta-base-wikiann-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline_ig.md b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline_ig.md
new file mode 100644
index 00000000000000..4017f9ce76d6dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline_ig.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Igbo xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline pipeline XlmRoBertaForTokenClassification from Davlan
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline
+date: 2024-09-03
+tags: [ig, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ig
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline` is a Igbo model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline_ig_5.5.0_3.0_1725372303029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline_ig_5.5.0_3.0_1725372303029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline", lang = "ig")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline", lang = "ig")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_wikiann_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ig|
+|Size:|858.7 MB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-wikiann-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-203_hw2_branflake_en.md b/docs/_posts/ahmedlone127/2024-09-04-203_hw2_branflake_en.md
new file mode 100644
index 00000000000000..902fa0740bd8d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-203_hw2_branflake_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 203_hw2_branflake RoBertaForQuestionAnswering from branflake
+author: John Snow Labs
+name: 203_hw2_branflake
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`203_hw2_branflake` is a English model originally trained by branflake.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/203_hw2_branflake_en_5.5.0_3.0_1725483869331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/203_hw2_branflake_en_5.5.0_3.0_1725483869331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("203_hw2_branflake","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("203_hw2_branflake", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|203_hw2_branflake|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.0 MB|
+
+## References
+
+https://huggingface.co/branflake/203_hw2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-2epoch_en.md b/docs/_posts/ahmedlone127/2024-09-04-2epoch_en.md
new file mode 100644
index 00000000000000..c07769ef765877
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-2epoch_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 2epoch MPNetEmbeddings from Watwat100
+author: John Snow Labs
+name: 2epoch
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2epoch` is a English model originally trained by Watwat100.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2epoch_en_5.5.0_3.0_1725470401622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2epoch_en_5.5.0_3.0_1725470401622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("2epoch","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("2epoch","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2epoch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/Watwat100/2epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-2epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-2epoch_pipeline_en.md
new file mode 100644
index 00000000000000..8ff56f95fd3e6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-2epoch_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 2epoch_pipeline pipeline MPNetEmbeddings from Watwat100
+author: John Snow Labs
+name: 2epoch_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2epoch_pipeline` is a English model originally trained by Watwat100.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2epoch_pipeline_en_5.5.0_3.0_1725470421798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2epoch_pipeline_en_5.5.0_3.0_1725470421798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/Watwat100/2epoch
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-32_shot_twitter_2classes_head_body_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-32_shot_twitter_2classes_head_body_pipeline_en.md
new file mode 100644
index 00000000000000..b63f853bfff81d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-32_shot_twitter_2classes_head_body_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 32_shot_twitter_2classes_head_body_pipeline pipeline MPNetEmbeddings from Nhat1904
+author: John Snow Labs
+name: 32_shot_twitter_2classes_head_body_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`32_shot_twitter_2classes_head_body_pipeline` is a English model originally trained by Nhat1904.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/32_shot_twitter_2classes_head_body_pipeline_en_5.5.0_3.0_1725470706020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/32_shot_twitter_2classes_head_body_pipeline_en_5.5.0_3.0_1725470706020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("32_shot_twitter_2classes_head_body_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("32_shot_twitter_2classes_head_body_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|32_shot_twitter_2classes_head_body_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/Nhat1904/32-shot-twitter-2classes-head-body
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-50_sdb_taxxl_truncate_768_en.md b/docs/_posts/ahmedlone127/2024-09-04-50_sdb_taxxl_truncate_768_en.md
new file mode 100644
index 00000000000000..72dfab014a5b06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-50_sdb_taxxl_truncate_768_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 50_sdb_taxxl_truncate_768 DistilBertEmbeddings from sripadhstudy
+author: John Snow Labs
+name: 50_sdb_taxxl_truncate_768
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`50_sdb_taxxl_truncate_768` is a English model originally trained by sripadhstudy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/50_sdb_taxxl_truncate_768_en_5.5.0_3.0_1725418301735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/50_sdb_taxxl_truncate_768_en_5.5.0_3.0_1725418301735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("50_sdb_taxxl_truncate_768","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("50_sdb_taxxl_truncate_768","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|50_sdb_taxxl_truncate_768|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/sripadhstudy/50_SDB_TAxxL_truncate_768
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-50_sdb_taxxl_truncate_768_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-50_sdb_taxxl_truncate_768_pipeline_en.md
new file mode 100644
index 00000000000000..45493cede93534
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-50_sdb_taxxl_truncate_768_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 50_sdb_taxxl_truncate_768_pipeline pipeline DistilBertEmbeddings from sripadhstudy
+author: John Snow Labs
+name: 50_sdb_taxxl_truncate_768_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`50_sdb_taxxl_truncate_768_pipeline` is a English model originally trained by sripadhstudy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/50_sdb_taxxl_truncate_768_pipeline_en_5.5.0_3.0_1725418314475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/50_sdb_taxxl_truncate_768_pipeline_en_5.5.0_3.0_1725418314475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("50_sdb_taxxl_truncate_768_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("50_sdb_taxxl_truncate_768_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|50_sdb_taxxl_truncate_768_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/sripadhstudy/50_SDB_TAxxL_truncate_768
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-579_private_v3_en.md b/docs/_posts/ahmedlone127/2024-09-04-579_private_v3_en.md
new file mode 100644
index 00000000000000..4a85e2a3a25a5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-579_private_v3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 579_private_v3 MPNetEmbeddings from jpcompartir
+author: John Snow Labs
+name: 579_private_v3
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`579_private_v3` is a English model originally trained by jpcompartir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/579_private_v3_en_5.5.0_3.0_1725469995888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/579_private_v3_en_5.5.0_3.0_1725469995888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("579_private_v3","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("579_private_v3","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|579_private_v3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/jpcompartir/579-private-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-600_stmodel_brand_rem_en.md b/docs/_posts/ahmedlone127/2024-09-04-600_stmodel_brand_rem_en.md
new file mode 100644
index 00000000000000..cd9328cabb02c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-600_stmodel_brand_rem_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 600_stmodel_brand_rem MPNetEmbeddings from jamiehudson
+author: John Snow Labs
+name: 600_stmodel_brand_rem
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`600_stmodel_brand_rem` is a English model originally trained by jamiehudson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/600_stmodel_brand_rem_en_5.5.0_3.0_1725470785479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/600_stmodel_brand_rem_en_5.5.0_3.0_1725470785479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("600_stmodel_brand_rem","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("600_stmodel_brand_rem","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|600_stmodel_brand_rem|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/jamiehudson/600-STmodel-brand-rem
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-7_shot_sta_freezed_body_1e_5_batch_8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-7_shot_sta_freezed_body_1e_5_batch_8_pipeline_en.md
new file mode 100644
index 00000000000000..beec34724b76db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-7_shot_sta_freezed_body_1e_5_batch_8_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 7_shot_sta_freezed_body_1e_5_batch_8_pipeline pipeline MPNetEmbeddings from Nhat1904
+author: John Snow Labs
+name: 7_shot_sta_freezed_body_1e_5_batch_8_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`7_shot_sta_freezed_body_1e_5_batch_8_pipeline` is a English model originally trained by Nhat1904.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/7_shot_sta_freezed_body_1e_5_batch_8_pipeline_en_5.5.0_3.0_1725470383739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/7_shot_sta_freezed_body_1e_5_batch_8_pipeline_en_5.5.0_3.0_1725470383739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("7_shot_sta_freezed_body_1e_5_batch_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("7_shot_sta_freezed_body_1e_5_batch_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|7_shot_sta_freezed_body_1e_5_batch_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/Nhat1904/7_shot_STA_freezed_body_1e-5_batch_8
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_en.md b/docs/_posts/ahmedlone127/2024-09-04-ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_en.md
new file mode 100644
index 00000000000000..c8fef8f09b404c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512 RoBertaForSequenceClassification from rajendrabaskota
+author: John Snow Labs
+name: ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512` is a English model originally trained by rajendrabaskota.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_en_5.5.0_3.0_1725485964423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_en_5.5.0_3.0_1725485964423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+https://huggingface.co/rajendrabaskota/ai-human-classification-hc3-wiki-recleaned-dataset-max-length-512
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline_en.md
new file mode 100644
index 00000000000000..58b6243a27b4e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline pipeline RoBertaForSequenceClassification from rajendrabaskota
+author: John Snow Labs
+name: ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline` is a English model originally trained by rajendrabaskota.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline_en_5.5.0_3.0_1725485989654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline_en_5.5.0_3.0_1725485989654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_human_classification_hc3_wiki_recleaned_dataset_max_length_512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+https://huggingface.co/rajendrabaskota/ai-human-classification-hc3-wiki-recleaned-dataset-max-length-512
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_base_chinese_ws_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-04-albert_base_chinese_ws_pipeline_zh.md
new file mode 100644
index 00000000000000..017f89733ca90a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_base_chinese_ws_pipeline_zh.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Chinese albert_base_chinese_ws_pipeline pipeline BertForTokenClassification from ckiplab
+author: John Snow Labs
+name: albert_base_chinese_ws_pipeline
+date: 2024-09-04
+tags: [zh, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_chinese_ws_pipeline` is a Chinese model originally trained by ckiplab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_chinese_ws_pipeline_zh_5.5.0_3.0_1725449515171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_chinese_ws_pipeline_zh_5.5.0_3.0_1725449515171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_chinese_ws_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_chinese_ws_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_chinese_ws_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|37.6 MB|
+
+## References
+
+https://huggingface.co/ckiplab/albert-base-chinese-ws
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_base_qa_coqa_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_base_qa_coqa_1_en.md
new file mode 100644
index 00000000000000..d608805bdef67c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_base_qa_coqa_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_base_qa_coqa_1 AlbertForQuestionAnswering from mateiaass
+author: John Snow Labs
+name: albert_base_qa_coqa_1
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_qa_coqa_1` is a English model originally trained by mateiaass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_1_en_5.5.0_3.0_1725415034685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_qa_coqa_1_en_5.5.0_3.0_1725415034685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_qa_coqa_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_qa_coqa_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/mateiaass/albert-base-qa-coQA-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_albert_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_albert_en.md
new file mode 100644
index 00000000000000..6499f51739f9ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_albert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_albert AlbertEmbeddings from albert
+author: John Snow Labs
+name: albert_base_v2_albert
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_albert` is a English model originally trained by albert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_albert_en_5.5.0_3.0_1725435133783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_albert_en_5.5.0_3.0_1725435133783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("albert_base_v2_albert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("albert_base_v2_albert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_albert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/albert/albert-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_albert_pipeline_en.md
new file mode 100644
index 00000000000000..002f7630ae8ddf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_albert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_v2_albert_pipeline pipeline AlbertEmbeddings from albert
+author: John Snow Labs
+name: albert_base_v2_albert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_albert_pipeline` is a English model originally trained by albert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_albert_pipeline_en_5.5.0_3.0_1725435136123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_albert_pipeline_en_5.5.0_3.0_1725435136123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_v2_albert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_v2_albert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_albert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/albert/albert-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_qqp_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_qqp_en.md
new file mode 100644
index 00000000000000..874e0b3e1c4bba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_qqp_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English albert_base_v2_qqp AlbertForSequenceClassification from Alireza1044
+author: John Snow Labs
+name: albert_base_v2_qqp
+date: 2024-09-04
+tags: [albert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_qqp` is a English model originally trained by Alireza1044.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_qqp_en_5.5.0_3.0_1725464614717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_qqp_en_5.5.0_3.0_1725464614717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_base_v2_qqp","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, sequenceClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val sequenceClassifier = AlbertForSequenceClassification  
+    .pretrained("albert_base_v2_qqp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, sequenceClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_qqp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/Alireza1044/albert-base-v2-qqp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_rotten_tomatoes_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_rotten_tomatoes_en.md
new file mode 100644
index 00000000000000..0f90dc4aa53033
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_rotten_tomatoes_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English albert_base_v2_rotten_tomatoes AlbertForSequenceClassification from textattack
+author: John Snow Labs
+name: albert_base_v2_rotten_tomatoes
+date: 2024-09-04
+tags: [albert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_rotten_tomatoes` is a English model originally trained by textattack.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_rotten_tomatoes_en_5.5.0_3.0_1725435081193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_rotten_tomatoes_en_5.5.0_3.0_1725435081193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_base_v2_rotten_tomatoes","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, sequenceClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val sequenceClassifier = AlbertForSequenceClassification  
+    .pretrained("albert_base_v2_rotten_tomatoes", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, sequenceClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_rotten_tomatoes|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/textattack/albert-base-v2-rotten-tomatoes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_rte_textattack_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_rte_textattack_en.md
new file mode 100644
index 00000000000000..f4506400191775
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_rte_textattack_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_rte_textattack AlbertForSequenceClassification from textattack
+author: John Snow Labs
+name: albert_base_v2_rte_textattack
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_rte_textattack` is a English model originally trained by textattack.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_rte_textattack_en_5.5.0_3.0_1725441431113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_rte_textattack_en_5.5.0_3.0_1725441431113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_base_v2_rte_textattack","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_base_v2_rte_textattack", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_rte_textattack|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/textattack/albert-base-v2-RTE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_imdb_en.md
new file mode 100644
index 00000000000000..d6c0c25e7b4e1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_imdb AlbertForSequenceClassification from JeffreyJIANG
+author: John Snow Labs
+name: albert_imdb
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_imdb` is a English model originally trained by JeffreyJIANG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_imdb_en_5.5.0_3.0_1725488492127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_imdb_en_5.5.0_3.0_1725488492127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_imdb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_imdb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_imdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/JeffreyJIANG/albert-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..907d5305c1f7a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_imdb_pipeline pipeline AlbertForSequenceClassification from JeffreyJIANG
+author: John Snow Labs
+name: albert_imdb_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_imdb_pipeline` is a English model originally trained by JeffreyJIANG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_imdb_pipeline_en_5.5.0_3.0_1725488494558.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_imdb_pipeline_en_5.5.0_3.0_1725488494558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/JeffreyJIANG/albert-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_japanese_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_japanese_v2_en.md
new file mode 100644
index 00000000000000..510ad7ea9c92f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_japanese_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_japanese_v2 AlbertEmbeddings from ALINEAR
+author: John Snow Labs
+name: albert_japanese_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_japanese_v2` is a English model originally trained by ALINEAR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_japanese_v2_en_5.5.0_3.0_1725457772954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_japanese_v2_en_5.5.0_3.0_1725457772954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("albert_japanese_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("albert_japanese_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_japanese_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|42.9 MB|
+
+## References
+
+https://huggingface.co/ALINEAR/albert-japanese-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_large_arabic_ar.md b/docs/_posts/ahmedlone127/2024-09-04-albert_large_arabic_ar.md
new file mode 100644
index 00000000000000..1d7e1482cc0f93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_large_arabic_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic albert_large_arabic AlbertEmbeddings from asafaya
+author: John Snow Labs
+name: albert_large_arabic
+date: 2024-09-04
+tags: [ar, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_large_arabic` is a Arabic model originally trained by asafaya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_large_arabic_ar_5.5.0_3.0_1725457834037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_large_arabic_ar_5.5.0_3.0_1725457834037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("albert_large_arabic","ar") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("albert_large_arabic","ar") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_large_arabic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|ar|
+|Size:|62.8 MB|
+
+## References
+
+https://huggingface.co/asafaya/albert-large-arabic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_large_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-albert_large_arabic_pipeline_ar.md
new file mode 100644
index 00000000000000..6e3e3c5098d9c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_large_arabic_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic albert_large_arabic_pipeline pipeline AlbertEmbeddings from asafaya
+author: John Snow Labs
+name: albert_large_arabic_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_large_arabic_pipeline` is a Arabic model originally trained by asafaya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_large_arabic_pipeline_ar_5.5.0_3.0_1725457837327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_large_arabic_pipeline_ar_5.5.0_3.0_1725457837327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_large_arabic_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_large_arabic_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_large_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|62.8 MB|
+
+## References
+
+https://huggingface.co/asafaya/albert-large-arabic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_persian_farsi_base_v2_fa.md b/docs/_posts/ahmedlone127/2024-09-04-albert_persian_farsi_base_v2_fa.md
new file mode 100644
index 00000000000000..2ef01d6c11981a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_persian_farsi_base_v2_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian albert_persian_farsi_base_v2 AlbertEmbeddings from m3hrdadfi
+author: John Snow Labs
+name: albert_persian_farsi_base_v2
+date: 2024-09-04
+tags: [fa, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_persian_farsi_base_v2` is a Persian model originally trained by m3hrdadfi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_base_v2_fa_5.5.0_3.0_1725457640129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_base_v2_fa_5.5.0_3.0_1725457640129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("albert_persian_farsi_base_v2","fa") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("albert_persian_farsi_base_v2","fa") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_persian_farsi_base_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|fa|
+|Size:|66.3 MB|
+
+## References
+
+https://huggingface.co/m3hrdadfi/albert-fa-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_persian_farsi_base_v2_sentiment_multi_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-04-albert_persian_farsi_base_v2_sentiment_multi_pipeline_fa.md
new file mode 100644
index 00000000000000..fb6a3badd2012d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_persian_farsi_base_v2_sentiment_multi_pipeline_fa.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Persian albert_persian_farsi_base_v2_sentiment_multi_pipeline pipeline AlbertForSequenceClassification from m3hrdadfi
+author: John Snow Labs
+name: albert_persian_farsi_base_v2_sentiment_multi_pipeline
+date: 2024-09-04
+tags: [fa, open_source, pipeline, onnx]
+task: Text Classification
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_persian_farsi_base_v2_sentiment_multi_pipeline` is a Persian model originally trained by m3hrdadfi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_base_v2_sentiment_multi_pipeline_fa_5.5.0_3.0_1725441317206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_base_v2_sentiment_multi_pipeline_fa_5.5.0_3.0_1725441317206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_persian_farsi_base_v2_sentiment_multi_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_persian_farsi_base_v2_sentiment_multi_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_persian_farsi_base_v2_sentiment_multi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|68.6 MB|
+
+## References
+
+https://huggingface.co/m3hrdadfi/albert-fa-base-v2-sentiment-multi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_small_kor_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_small_kor_v1_en.md
new file mode 100644
index 00000000000000..e8a421577eb6e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_small_kor_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_small_kor_v1 AlbertEmbeddings from bongsoo
+author: John Snow Labs
+name: albert_small_kor_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_small_kor_v1` is a English model originally trained by bongsoo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_small_kor_v1_en_5.5.0_3.0_1725457762268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_small_kor_v1_en_5.5.0_3.0_1725457762268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("albert_small_kor_v1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("albert_small_kor_v1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_small_kor_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|41.8 MB|
+
+## References
+
+https://huggingface.co/bongsoo/albert-small-kor-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_xlarge_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_xlarge_v2_en.md
new file mode 100644
index 00000000000000..c28b1365943603
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_xlarge_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_xlarge_v2 AlbertEmbeddings from albert
+author: John Snow Labs
+name: albert_xlarge_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_xlarge_v2` is a English model originally trained by albert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_xlarge_v2_en_5.5.0_3.0_1725435571475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_xlarge_v2_en_5.5.0_3.0_1725435571475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("albert_xlarge_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("albert_xlarge_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_xlarge_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|204.7 MB|
+
+## References
+
+https://huggingface.co/albert/albert-xlarge-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_xlarge_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_xlarge_v2_pipeline_en.md
new file mode 100644
index 00000000000000..8bf2f6860303df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_xlarge_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_xlarge_v2_pipeline pipeline AlbertEmbeddings from albert
+author: John Snow Labs
+name: albert_xlarge_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_xlarge_v2_pipeline` is a English model originally trained by albert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_xlarge_v2_pipeline_en_5.5.0_3.0_1725435581127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_xlarge_v2_pipeline_en_5.5.0_3.0_1725435581127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_xlarge_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_xlarge_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_xlarge_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|204.7 MB|
+
+## References
+
+https://huggingface.co/albert/albert-xlarge-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_xxlarge_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_xxlarge_v2_en.md
new file mode 100644
index 00000000000000..01890e512aba41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_xxlarge_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_xxlarge_v2 AlbertEmbeddings from albert
+author: John Snow Labs
+name: albert_xxlarge_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_xxlarge_v2` is a English model originally trained by albert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_xxlarge_v2_en_5.5.0_3.0_1725435656603.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_xxlarge_v2_en_5.5.0_3.0_1725435656603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("albert_xxlarge_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("albert_xxlarge_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_xxlarge_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|771.0 MB|
+
+## References
+
+https://huggingface.co/albert/albert-xxlarge-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_xxlarge_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_xxlarge_v2_pipeline_en.md
new file mode 100644
index 00000000000000..bb275cbcb48322
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_xxlarge_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_xxlarge_v2_pipeline pipeline AlbertEmbeddings from albert
+author: John Snow Labs
+name: albert_xxlarge_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_xxlarge_v2_pipeline` is a English model originally trained by albert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_xxlarge_v2_pipeline_en_5.5.0_3.0_1725435693880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_xxlarge_v2_pipeline_en_5.5.0_3.0_1725435693880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_xxlarge_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_xxlarge_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_xxlarge_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|771.0 MB|
+
+## References
+
+https://huggingface.co/albert/albert-xxlarge-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_1_en.md
new file mode 100644
index 00000000000000..78a42be62857f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_1 MPNetEmbeddings from abhijitt
+author: John Snow Labs
+name: all_mpnet_base_v2_1
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_1` is a English model originally trained by abhijitt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_1_en_5.5.0_3.0_1725470659628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_1_en_5.5.0_3.0_1725470659628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/abhijitt/all-mpnet-base-v2_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline_en.md
new file mode 100644
index 00000000000000..b63ebf980968f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline pipeline MPNetEmbeddings from azikoss
+author: John Snow Labs
+name: all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline` is a English model originally trained by azikoss.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline_en_5.5.0_3.0_1725469889091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline_en_5.5.0_3.0_1725469889091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_airdialogue_unlabelled_and_labelled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/azikoss/all-mpnet-base-v2-airdialogue-unlabelled-and-labelled
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_en.md b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_en.md
new file mode 100644
index 00000000000000..bf6d8351dc19f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid MPNetEmbeddings from AhmetAytar
+author: John Snow Labs
+name: all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid` is a English model originally trained by AhmetAytar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_en_5.5.0_3.0_1725470116544.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_en_5.5.0_3.0_1725470116544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|929.3 KB|
+
+## References
+
+https://huggingface.co/AhmetAytar/all-mpnet-base-v2-fine-tuned_17_textbook_with_small_chunks_grobid
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline_en.md
new file mode 100644
index 00000000000000..fe82855e3ea3f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline pipeline MPNetEmbeddings from AhmetAytar
+author: John Snow Labs
+name: all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline` is a English model originally trained by AhmetAytar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline_en_5.5.0_3.0_1725470118390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline_en_5.5.0_3.0_1725470118390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_fine_tuned_17_textbook_with_small_chunks_grobid_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|935.1 KB|
+
+## References
+
+https://huggingface.co/AhmetAytar/all-mpnet-base-v2-fine-tuned_17_textbook_with_small_chunks_grobid
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..21f6531d52a6af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline pipeline MPNetEmbeddings from binhcode25-finetuned
+author: John Snow Labs
+name: all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline` is a English model originally trained by binhcode25-finetuned.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline_en_5.5.0_3.0_1725470910139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline_en_5.5.0_3.0_1725470910139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_fine_tuned_epochs_8_binhcode25_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/binhcode25-finetuned/all-mpnet-base-v2-fine-tuned-epochs-8
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline_en.md
new file mode 100644
index 00000000000000..47b562af384e8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline pipeline MPNetEmbeddings from event-nlp
+author: John Snow Labs
+name: all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline` is a English model originally trained by event-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline_en_5.5.0_3.0_1725469882187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline_en_5.5.0_3.0_1725469882187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_fine_tuned_epochs_8_event_nlp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/event-nlp/all-mpnet-base-v2-fine-tuned-epochs-8
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-answer_equivalence_roberta_large_zongxia_en.md b/docs/_posts/ahmedlone127/2024-09-04-answer_equivalence_roberta_large_zongxia_en.md
new file mode 100644
index 00000000000000..db71269c706d44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-answer_equivalence_roberta_large_zongxia_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English answer_equivalence_roberta_large_zongxia RoBertaForSequenceClassification from Zongxia
+author: John Snow Labs
+name: answer_equivalence_roberta_large_zongxia
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_equivalence_roberta_large_zongxia` is a English model originally trained by Zongxia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_equivalence_roberta_large_zongxia_en_5.5.0_3.0_1725485101023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_equivalence_roberta_large_zongxia_en_5.5.0_3.0_1725485101023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("answer_equivalence_roberta_large_zongxia","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("answer_equivalence_roberta_large_zongxia", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|answer_equivalence_roberta_large_zongxia|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Zongxia/answer_equivalence_roberta-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-answer_equivalence_roberta_large_zongxia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-answer_equivalence_roberta_large_zongxia_pipeline_en.md
new file mode 100644
index 00000000000000..5b0c26350f9337
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-answer_equivalence_roberta_large_zongxia_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English answer_equivalence_roberta_large_zongxia_pipeline pipeline RoBertaForSequenceClassification from Zongxia
+author: John Snow Labs
+name: answer_equivalence_roberta_large_zongxia_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`answer_equivalence_roberta_large_zongxia_pipeline` is a English model originally trained by Zongxia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/answer_equivalence_roberta_large_zongxia_pipeline_en_5.5.0_3.0_1725485176286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/answer_equivalence_roberta_large_zongxia_pipeline_en_5.5.0_3.0_1725485176286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("answer_equivalence_roberta_large_zongxia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("answer_equivalence_roberta_large_zongxia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|answer_equivalence_roberta_large_zongxia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Zongxia/answer_equivalence_roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-argureviews_component_deberta_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-argureviews_component_deberta_v1_en.md
new file mode 100644
index 00000000000000..1c2e95240ab2f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-argureviews_component_deberta_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English argureviews_component_deberta_v1 DeBertaForSequenceClassification from nihiluis
+author: John Snow Labs
+name: argureviews_component_deberta_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`argureviews_component_deberta_v1` is a English model originally trained by nihiluis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/argureviews_component_deberta_v1_en_5.5.0_3.0_1725469018944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/argureviews_component_deberta_v1_en_5.5.0_3.0_1725469018944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("argureviews_component_deberta_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("argureviews_component_deberta_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|argureviews_component_deberta_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/nihiluis/argureviews-component-deberta_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-argureviews_specificity_deberta_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-argureviews_specificity_deberta_v1_en.md
new file mode 100644
index 00000000000000..d70755768a8eb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-argureviews_specificity_deberta_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English argureviews_specificity_deberta_v1 DeBertaForSequenceClassification from nihiluis
+author: John Snow Labs
+name: argureviews_specificity_deberta_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`argureviews_specificity_deberta_v1` is a English model originally trained by nihiluis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/argureviews_specificity_deberta_v1_en_5.5.0_3.0_1725468292204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/argureviews_specificity_deberta_v1_en_5.5.0_3.0_1725468292204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("argureviews_specificity_deberta_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("argureviews_specificity_deberta_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|argureviews_specificity_deberta_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/nihiluis/argureviews-specificity-deberta_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-argureviews_specificity_deberta_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-argureviews_specificity_deberta_v1_pipeline_en.md
new file mode 100644
index 00000000000000..c1674ed566ab03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-argureviews_specificity_deberta_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English argureviews_specificity_deberta_v1_pipeline pipeline DeBertaForSequenceClassification from nihiluis
+author: John Snow Labs
+name: argureviews_specificity_deberta_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`argureviews_specificity_deberta_v1_pipeline` is a English model originally trained by nihiluis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/argureviews_specificity_deberta_v1_pipeline_en_5.5.0_3.0_1725468389145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/argureviews_specificity_deberta_v1_pipeline_en_5.5.0_3.0_1725468389145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("argureviews_specificity_deberta_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("argureviews_specificity_deberta_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|argureviews_specificity_deberta_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/nihiluis/argureviews-specificity-deberta_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-arzwiki_20230101_roberta_mlm_ar.md b/docs/_posts/ahmedlone127/2024-09-04-arzwiki_20230101_roberta_mlm_ar.md
new file mode 100644
index 00000000000000..783c8dab119e47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-arzwiki_20230101_roberta_mlm_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic arzwiki_20230101_roberta_mlm RoBertaEmbeddings from SaiedAlshahrani
+author: John Snow Labs
+name: arzwiki_20230101_roberta_mlm
+date: 2024-09-04
+tags: [ar, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arzwiki_20230101_roberta_mlm` is a Arabic model originally trained by SaiedAlshahrani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arzwiki_20230101_roberta_mlm_ar_5.5.0_3.0_1725412415095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arzwiki_20230101_roberta_mlm_ar_5.5.0_3.0_1725412415095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("arzwiki_20230101_roberta_mlm","ar") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("arzwiki_20230101_roberta_mlm","ar") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arzwiki_20230101_roberta_mlm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|ar|
+|Size:|311.7 MB|
+
+## References
+
+https://huggingface.co/SaiedAlshahrani/arzwiki_20230101_roberta_mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-arzwiki_20230101_roberta_mlm_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-arzwiki_20230101_roberta_mlm_pipeline_ar.md
new file mode 100644
index 00000000000000..cb51fd4fbebc71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-arzwiki_20230101_roberta_mlm_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic arzwiki_20230101_roberta_mlm_pipeline pipeline RoBertaEmbeddings from SaiedAlshahrani
+author: John Snow Labs
+name: arzwiki_20230101_roberta_mlm_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arzwiki_20230101_roberta_mlm_pipeline` is a Arabic model originally trained by SaiedAlshahrani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arzwiki_20230101_roberta_mlm_pipeline_ar_5.5.0_3.0_1725412435549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arzwiki_20230101_roberta_mlm_pipeline_ar_5.5.0_3.0_1725412435549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("arzwiki_20230101_roberta_mlm_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arzwiki_20230101_roberta_mlm_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arzwiki_20230101_roberta_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|311.8 MB|
+
+## References
+
+https://huggingface.co/SaiedAlshahrani/arzwiki_20230101_roberta_mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-asr_santhosh_kumar_en.md b/docs/_posts/ahmedlone127/2024-09-04-asr_santhosh_kumar_en.md
new file mode 100644
index 00000000000000..070f0e387f7b87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-asr_santhosh_kumar_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English asr_santhosh_kumar WhisperForCTC from Santhosh-kumar
+author: John Snow Labs
+name: asr_santhosh_kumar
+date: 2024-09-04
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_santhosh_kumar` is a English model originally trained by Santhosh-kumar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_santhosh_kumar_en_5.5.0_3.0_1725427395748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_santhosh_kumar_en_5.5.0_3.0_1725427395748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("asr_santhosh_kumar","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("asr_santhosh_kumar", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|asr_santhosh_kumar|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Santhosh-kumar/ASR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-asr_santhosh_kumar_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-asr_santhosh_kumar_pipeline_en.md
new file mode 100644
index 00000000000000..c7c13c152417c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-asr_santhosh_kumar_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English asr_santhosh_kumar_pipeline pipeline WhisperForCTC from Santhosh-kumar
+author: John Snow Labs
+name: asr_santhosh_kumar_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_santhosh_kumar_pipeline` is a English model originally trained by Santhosh-kumar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_santhosh_kumar_pipeline_en_5.5.0_3.0_1725427489797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_santhosh_kumar_pipeline_en_5.5.0_3.0_1725427489797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("asr_santhosh_kumar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("asr_santhosh_kumar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|asr_santhosh_kumar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Santhosh-kumar/ASR
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-astroentities_en.md b/docs/_posts/ahmedlone127/2024-09-04-astroentities_en.md
new file mode 100644
index 00000000000000..ef70437592b2a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-astroentities_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English astroentities DistilBertForTokenClassification from teamzalenski
+author: John Snow Labs
+name: astroentities
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`astroentities` is a English model originally trained by teamzalenski.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/astroentities_en_5.5.0_3.0_1725492824393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/astroentities_en_5.5.0_3.0_1725492824393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("astroentities","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("astroentities", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|astroentities|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/teamzalenski/astroentities
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-atte_4_en.md b/docs/_posts/ahmedlone127/2024-09-04-atte_4_en.md
new file mode 100644
index 00000000000000..33466e45b98fb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-atte_4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English atte_4 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: atte_4
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atte_4` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atte_4_en_5.5.0_3.0_1725452291664.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atte_4_en_5.5.0_3.0_1725452291664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("atte_4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("atte_4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atte_4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Atte_4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-atte_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-atte_4_pipeline_en.md
new file mode 100644
index 00000000000000..ba4db885685545
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-atte_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English atte_4_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: atte_4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atte_4_pipeline` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atte_4_pipeline_en_5.5.0_3.0_1725452315959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atte_4_pipeline_en_5.5.0_3.0_1725452315959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("atte_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("atte_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atte_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Atte_4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-autonlp_covid_fake_news_36839110_en.md b/docs/_posts/ahmedlone127/2024-09-04-autonlp_covid_fake_news_36839110_en.md
new file mode 100644
index 00000000000000..6860f987d44863
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-autonlp_covid_fake_news_36839110_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autonlp_covid_fake_news_36839110 AlbertForSequenceClassification from dtam
+author: John Snow Labs
+name: autonlp_covid_fake_news_36839110
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autonlp_covid_fake_news_36839110` is a English model originally trained by dtam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autonlp_covid_fake_news_36839110_en_5.5.0_3.0_1725488607242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autonlp_covid_fake_news_36839110_en_5.5.0_3.0_1725488607242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("autonlp_covid_fake_news_36839110","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("autonlp_covid_fake_news_36839110", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autonlp_covid_fake_news_36839110|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|833.9 MB|
+
+## References
+
+https://huggingface.co/dtam/autonlp-covid-fake-news-36839110
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-autotrain_2_xlmr_r_53880126783_en.md b/docs/_posts/ahmedlone127/2024-09-04-autotrain_2_xlmr_r_53880126783_en.md
new file mode 100644
index 00000000000000..2b7de319f16257
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-autotrain_2_xlmr_r_53880126783_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_2_xlmr_r_53880126783 XlmRoBertaForTokenClassification from tinyYhorm
+author: John Snow Labs
+name: autotrain_2_xlmr_r_53880126783
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_2_xlmr_r_53880126783` is a English model originally trained by tinyYhorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_2_xlmr_r_53880126783_en_5.5.0_3.0_1725437819691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_2_xlmr_r_53880126783_en_5.5.0_3.0_1725437819691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("autotrain_2_xlmr_r_53880126783","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("autotrain_2_xlmr_r_53880126783", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_2_xlmr_r_53880126783|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|769.9 MB|
+
+## References
+
+https://huggingface.co/tinyYhorm/autotrain-2-xlmr-r-53880126783
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-autotrain_2_xlmr_r_53880126783_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-autotrain_2_xlmr_r_53880126783_pipeline_en.md
new file mode 100644
index 00000000000000..c386663ed6d327
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-autotrain_2_xlmr_r_53880126783_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_2_xlmr_r_53880126783_pipeline pipeline XlmRoBertaForTokenClassification from tinyYhorm
+author: John Snow Labs
+name: autotrain_2_xlmr_r_53880126783_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_2_xlmr_r_53880126783_pipeline` is a English model originally trained by tinyYhorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_2_xlmr_r_53880126783_pipeline_en_5.5.0_3.0_1725437968523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_2_xlmr_r_53880126783_pipeline_en_5.5.0_3.0_1725437968523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_2_xlmr_r_53880126783_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_2_xlmr_r_53880126783_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_2_xlmr_r_53880126783_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|769.9 MB|
+
+## References
+
+https://huggingface.co/tinyYhorm/autotrain-2-xlmr-r-53880126783
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-autotrain_3_xlmr_fulltext_53881126794_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-autotrain_3_xlmr_fulltext_53881126794_pipeline_en.md
new file mode 100644
index 00000000000000..6b63e4fd458466
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-autotrain_3_xlmr_fulltext_53881126794_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_3_xlmr_fulltext_53881126794_pipeline pipeline XlmRoBertaForTokenClassification from tinyYhorm
+author: John Snow Labs
+name: autotrain_3_xlmr_fulltext_53881126794_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_3_xlmr_fulltext_53881126794_pipeline` is a English model originally trained by tinyYhorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_3_xlmr_fulltext_53881126794_pipeline_en_5.5.0_3.0_1725423916080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_3_xlmr_fulltext_53881126794_pipeline_en_5.5.0_3.0_1725423916080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_3_xlmr_fulltext_53881126794_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_3_xlmr_fulltext_53881126794_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_3_xlmr_fulltext_53881126794_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|769.5 MB|
+
+## References
+
+https://huggingface.co/tinyYhorm/autotrain-3-xlmr-fulltext-53881126794
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-autotrain_aws_bot_en.md b/docs/_posts/ahmedlone127/2024-09-04-autotrain_aws_bot_en.md
new file mode 100644
index 00000000000000..454ac680844e19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-autotrain_aws_bot_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_aws_bot MPNetForSequenceClassification from riyaz-31
+author: John Snow Labs
+name: autotrain_aws_bot
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_aws_bot` is a English model originally trained by riyaz-31.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_aws_bot_en_5.5.0_3.0_1725421723629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_aws_bot_en_5.5.0_3.0_1725421723629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("autotrain_aws_bot","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("autotrain_aws_bot", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_aws_bot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/riyaz-31/autotrain-aws-bot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-autotrain_aws_bot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-autotrain_aws_bot_pipeline_en.md
new file mode 100644
index 00000000000000..f4c3442ddad312
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-autotrain_aws_bot_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_aws_bot_pipeline pipeline MPNetForSequenceClassification from riyaz-31
+author: John Snow Labs
+name: autotrain_aws_bot_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_aws_bot_pipeline` is a English model originally trained by riyaz-31.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_aws_bot_pipeline_en_5.5.0_3.0_1725421744734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_aws_bot_pipeline_en_5.5.0_3.0_1725421744734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_aws_bot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_aws_bot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_aws_bot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/riyaz-31/autotrain-aws-bot
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-autotrain_okr_iptal_v3_47629116653_en.md b/docs/_posts/ahmedlone127/2024-09-04-autotrain_okr_iptal_v3_47629116653_en.md
new file mode 100644
index 00000000000000..e8b5e62e99a1cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-autotrain_okr_iptal_v3_47629116653_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_okr_iptal_v3_47629116653 XlmRoBertaForSequenceClassification from ekincanozcelik
+author: John Snow Labs
+name: autotrain_okr_iptal_v3_47629116653
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_v3_47629116653` is a English model originally trained by ekincanozcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v3_47629116653_en_5.5.0_3.0_1725411124741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v3_47629116653_en_5.5.0_3.0_1725411124741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_v3_47629116653","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_v3_47629116653", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_okr_iptal_v3_47629116653|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|778.0 MB|
+
+## References
+
+https://huggingface.co/ekincanozcelik/autotrain-okr_iptal_v3-47629116653
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-autotrain_okr_iptal_v3_47629116653_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-autotrain_okr_iptal_v3_47629116653_pipeline_en.md
new file mode 100644
index 00000000000000..a24cc43b3991e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-autotrain_okr_iptal_v3_47629116653_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_okr_iptal_v3_47629116653_pipeline pipeline XlmRoBertaForSequenceClassification from ekincanozcelik
+author: John Snow Labs
+name: autotrain_okr_iptal_v3_47629116653_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_v3_47629116653_pipeline` is a English model originally trained by ekincanozcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v3_47629116653_pipeline_en_5.5.0_3.0_1725411273768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v3_47629116653_pipeline_en_5.5.0_3.0_1725411273768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_okr_iptal_v3_47629116653_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_okr_iptal_v3_47629116653_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_okr_iptal_v3_47629116653_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|778.0 MB|
+
+## References
+
+https://huggingface.co/ekincanozcelik/autotrain-okr_iptal_v3-47629116653
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline_en.md
new file mode 100644
index 00000000000000..7d1403d1c5f864
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline pipeline RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline` is a English model originally trained by lielbin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline_en_5.5.0_3.0_1725483364980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline_en_5.5.0_3.0_1725483364980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_wikipedia_2_5_0_1_finetuned_qamr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|32.0 MB|
+
+## References
+
+https://huggingface.co/lielbin/babyberta-Wikipedia_2.5-0.1-finetuned-QAMR
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bc5cdr_clinicalbert_ner_en.md b/docs/_posts/ahmedlone127/2024-09-04-bc5cdr_clinicalbert_ner_en.md
new file mode 100644
index 00000000000000..70c91e88bd053a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bc5cdr_clinicalbert_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bc5cdr_clinicalbert_ner DistilBertForTokenClassification from judithrosell
+author: John Snow Labs
+name: bc5cdr_clinicalbert_ner
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bc5cdr_clinicalbert_ner` is a English model originally trained by judithrosell.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bc5cdr_clinicalbert_ner_en_5.5.0_3.0_1725475782971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bc5cdr_clinicalbert_ner_en_5.5.0_3.0_1725475782971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("bc5cdr_clinicalbert_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("bc5cdr_clinicalbert_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bc5cdr_clinicalbert_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.3 MB|
+
+## References
+
+https://huggingface.co/judithrosell/BC5CDR_ClinicalBERT_NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bc5cdr_clinicalbert_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bc5cdr_clinicalbert_ner_pipeline_en.md
new file mode 100644
index 00000000000000..12e0eb9729dc24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bc5cdr_clinicalbert_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bc5cdr_clinicalbert_ner_pipeline pipeline DistilBertForTokenClassification from judithrosell
+author: John Snow Labs
+name: bc5cdr_clinicalbert_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bc5cdr_clinicalbert_ner_pipeline` is a English model originally trained by judithrosell.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bc5cdr_clinicalbert_ner_pipeline_en_5.5.0_3.0_1725475807586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bc5cdr_clinicalbert_ner_pipeline_en_5.5.0_3.0_1725475807586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bc5cdr_clinicalbert_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bc5cdr_clinicalbert_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bc5cdr_clinicalbert_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/judithrosell/BC5CDR_ClinicalBERT_NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_base_uncased_amazon_polarity_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_base_uncased_amazon_polarity_en.md
new file mode 100644
index 00000000000000..1554d192b18fbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_base_uncased_amazon_polarity_en.md
@@ -0,0 +1,105 @@
+---
+layout: model
+title: English BertForSequenceClassification Base Uncased model (from fabriceyhc)
+author: John Snow Labs
+name: bert_classifier_base_uncased_amazon_polarity
+date: 2024-09-04
+tags: [bert, sequence_classification, classification, open_source, en, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-amazon_polarity` is a English model originally trained by `fabriceyhc`.
+
+## Predicted Entities
+
+`positive`, `negative`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_base_uncased_amazon_polarity_en_5.5.0_3.0_1725433139785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_base_uncased_amazon_polarity_en_5.5.0_3.0_1725433139785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_uncased_amazon_polarity","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_uncased_amazon_polarity","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded))
+
+val data = Seq("PUT YOUR STRING HERE").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.classify.bert.amazon.uncased_base").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_base_uncased_amazon_polarity|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/fabriceyhc/bert-base-uncased-amazon_polarity
+- https://paperswithcode.com/sota?task=Text+Classification&dataset=amazon_polarity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_base_uncased_amazon_polarity_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_base_uncased_amazon_polarity_pipeline_en.md
new file mode 100644
index 00000000000000..c7d8d78e5211b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_base_uncased_amazon_polarity_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_base_uncased_amazon_polarity_pipeline pipeline BertForSequenceClassification from fabriceyhc
+author: John Snow Labs
+name: bert_classifier_base_uncased_amazon_polarity_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_base_uncased_amazon_polarity_pipeline` is a English model originally trained by fabriceyhc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_base_uncased_amazon_polarity_pipeline_en_5.5.0_3.0_1725433160773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_base_uncased_amazon_polarity_pipeline_en_5.5.0_3.0_1725433160773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_classifier_base_uncased_amazon_polarity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_base_uncased_amazon_polarity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_base_uncased_amazon_polarity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/fabriceyhc/bert-base-uncased-amazon_polarity
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sanskrit_saskta_sub4_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sanskrit_saskta_sub4_en.md
new file mode 100644
index 00000000000000..d6c3d8874b1d27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sanskrit_saskta_sub4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_classifier_sanskrit_saskta_sub4 BertForSequenceClassification from researchaccount
+author: John Snow Labs
+name: bert_classifier_sanskrit_saskta_sub4
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub4` is a English model originally trained by researchaccount.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub4_en_5.5.0_3.0_1725432724246.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub4_en_5.5.0_3.0_1725432724246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_sanskrit_saskta_sub4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sanskrit_saskta_sub4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|610.9 MB|
+
+## References
+
+https://huggingface.co/researchaccount/sa_sub4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sanskrit_saskta_sub4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sanskrit_saskta_sub4_pipeline_en.md
new file mode 100644
index 00000000000000..18af78825e8fb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sanskrit_saskta_sub4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_sanskrit_saskta_sub4_pipeline pipeline BertForSequenceClassification from researchaccount
+author: John Snow Labs
+name: bert_classifier_sanskrit_saskta_sub4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sanskrit_saskta_sub4_pipeline` is a English model originally trained by researchaccount.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub4_pipeline_en_5.5.0_3.0_1725432754917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sanskrit_saskta_sub4_pipeline_en_5.5.0_3.0_1725432754917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_classifier_sanskrit_saskta_sub4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_sanskrit_saskta_sub4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sanskrit_saskta_sub4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|610.9 MB|
+
+## References
+
+https://huggingface.co/researchaccount/sa_sub4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sead_l_6_h_256_a_8_rte_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sead_l_6_h_256_a_8_rte_en.md
new file mode 100644
index 00000000000000..fb5d610a68aafe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sead_l_6_h_256_a_8_rte_en.md
@@ -0,0 +1,111 @@
+---
+layout: model
+title: English BertForSequenceClassification Cased model (from course5i)
+author: John Snow Labs
+name: bert_classifier_sead_l_6_h_256_a_8_rte
+date: 2024-09-04
+tags: [en, open_source, bert, sequence_classification, classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `SEAD-L-6_H-256_A-8-rte` is a English model originally trained by `course5i`.
+
+## Predicted Entities
+
+`0`, `1`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_rte_en_5.5.0_3.0_1725432609266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_rte_en_5.5.0_3.0_1725432609266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_256_a_8_rte","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_sead_l_6_h_256_a_8_rte","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.classify.bert.glue_rte.6l_256d_a8a_256d.by_course5i").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sead_l_6_h_256_a_8_rte|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|47.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/course5i/SEAD-L-6_H-256_A-8-rte
+- https://arxiv.org/abs/1910.01108
+- https://arxiv.org/abs/1909.10351
+- https://arxiv.org/abs/2002.10957
+- https://arxiv.org/abs/1810.04805
+- https://arxiv.org/abs/1804.07461
+- https://arxiv.org/abs/1905.00537
+- https://www.adasci.org/journals/lattice-35309407/?volumes=true&open=621a3b18edc4364e8a96cb63
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sead_l_6_h_256_a_8_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sead_l_6_h_256_a_8_rte_pipeline_en.md
new file mode 100644
index 00000000000000..5a62bc480a74f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sead_l_6_h_256_a_8_rte_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_sead_l_6_h_256_a_8_rte_pipeline pipeline BertForSequenceClassification from course5i
+author: John Snow Labs
+name: bert_classifier_sead_l_6_h_256_a_8_rte_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sead_l_6_h_256_a_8_rte_pipeline` is a English model originally trained by course5i.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_rte_pipeline_en_5.5.0_3.0_1725432612233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_rte_pipeline_en_5.5.0_3.0_1725432612233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_classifier_sead_l_6_h_256_a_8_rte_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_sead_l_6_h_256_a_8_rte_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sead_l_6_h_256_a_8_rte_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|47.3 MB|
+
+## References
+
+https://huggingface.co/course5i/SEAD-L-6_H-256_A-8-rte
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_spanish_news_classification_headlines_untrained_es.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_spanish_news_classification_headlines_untrained_es.md
new file mode 100644
index 00000000000000..7e6a6b6c30de5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_spanish_news_classification_headlines_untrained_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish bert_classifier_spanish_news_classification_headlines_untrained BertForSequenceClassification from M47Labs
+author: John Snow Labs
+name: bert_classifier_spanish_news_classification_headlines_untrained
+date: 2024-09-04
+tags: [es, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_spanish_news_classification_headlines_untrained` is a Castilian, Spanish model originally trained by M47Labs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_spanish_news_classification_headlines_untrained_es_5.5.0_3.0_1725432523355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_spanish_news_classification_headlines_untrained_es_5.5.0_3.0_1725432523355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_classifier_spanish_news_classification_headlines_untrained","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_spanish_news_classification_headlines_untrained", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_spanish_news_classification_headlines_untrained|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/M47Labs/spanish_news_classification_headlines_untrained
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sponsorblock_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sponsorblock_v2_en.md
new file mode 100644
index 00000000000000..2438299cc2cff4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sponsorblock_v2_en.md
@@ -0,0 +1,104 @@
+---
+layout: model
+title: English BertForSequenceClassification Cased model (from Xenova)
+author: John Snow Labs
+name: bert_classifier_sponsorblock_v2
+date: 2024-09-04
+tags: [bert, sequence_classification, classification, open_source, en, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `sponsorblock-classifier-v2` is a English model originally trained by `Xenova`.
+
+## Predicted Entities
+
+`SELFPROMO`, `NONE`, `SPONSOR`, `INTERACTION`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sponsorblock_v2_en_5.5.0_3.0_1725432786971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sponsorblock_v2_en_5.5.0_3.0_1725432786971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_sponsorblock_v2","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_sponsorblock_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded))
+
+val data = Seq("PUT YOUR STRING HERE").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.classify.bert.v2").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sponsorblock_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Xenova/sponsorblock-classifier-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sponsorblock_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sponsorblock_v2_pipeline_en.md
new file mode 100644
index 00000000000000..f8729054391e21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_sponsorblock_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_sponsorblock_v2_pipeline pipeline BertForSequenceClassification from Xenova
+author: John Snow Labs
+name: bert_classifier_sponsorblock_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sponsorblock_v2_pipeline` is a English model originally trained by Xenova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_sponsorblock_v2_pipeline_en_5.5.0_3.0_1725432811957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sponsorblock_v2_pipeline_en_5.5.0_3.0_1725432811957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_classifier_sponsorblock_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_sponsorblock_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sponsorblock_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Xenova/sponsorblock-classifier-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_ner_anglicisms_spanish_mbert_es.md b/docs/_posts/ahmedlone127/2024-09-04-bert_ner_anglicisms_spanish_mbert_es.md
new file mode 100644
index 00000000000000..ecbbd81bab4184
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_ner_anglicisms_spanish_mbert_es.md
@@ -0,0 +1,116 @@
+---
+layout: model
+title: Spanish Named Entity Recognition (from lirondos)
+author: John Snow Labs
+name: bert_ner_anglicisms_spanish_mbert
+date: 2024-09-04
+tags: [bert, ner, token_classification, es, open_source, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Named Entity Recognition model, uploaded to Hugging Face, adapted and imported into Spark NLP. `anglicisms-spanish-mbert` is a Spanish model orginally trained by `lirondos`.
+
+## Predicted Entities
+
+`OTHER`, `ENG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_anglicisms_spanish_mbert_es_5.5.0_3.0_1725450381234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_anglicisms_spanish_mbert_es_5.5.0_3.0_1725450381234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_ner_anglicisms_spanish_mbert","es") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["Amo Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_anglicisms_spanish_mbert","es") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("Amo Spark NLP").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("es.ner.bert").predict("""Amo Spark NLP""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_anglicisms_spanish_mbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|665.1 MB|
+
+## References
+
+References
+
+- https://huggingface.co/lirondos/anglicisms-spanish-mbert
+- https://github.com/lirondos/coalas/
+- https://github.com/lirondos/coalas/
+- https://github.com/lirondos/coalas/
+- https://arxiv.org/abs/2203.16169
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english_xx.md b/docs/_posts/ahmedlone127/2024-09-04-bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english_xx.md
new file mode 100644
index 00000000000000..5a810a2b66fd4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english BertForTokenClassification from StivenLancheros
+author: John Snow Labs
+name: bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english
+date: 2024-09-04
+tags: [xx, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english` is a Multilingual model originally trained by StivenLancheros.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english_xx_5.5.0_3.0_1725477486781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english_xx_5.5.0_3.0_1725477486781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmented_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/StivenLancheros/biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_EN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_ner_pii_multi_lingual_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_ner_pii_multi_lingual_en.md
new file mode 100644
index 00000000000000..341ddf93deeace
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_ner_pii_multi_lingual_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_ner_pii_multi_lingual BertForTokenClassification from vuminhtue
+author: John Snow Labs
+name: bert_ner_pii_multi_lingual
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_pii_multi_lingual` is a English model originally trained by vuminhtue.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_pii_multi_lingual_en_5.5.0_3.0_1725449736464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_pii_multi_lingual_en_5.5.0_3.0_1725449736464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_pii_multi_lingual","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_pii_multi_lingual", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_pii_multi_lingual|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|625.6 MB|
+
+## References
+
+https://huggingface.co/vuminhtue/Bert_NER_PII_Multi_Lingual
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_sayula_popoluca_estbert_xpos_128_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_sayula_popoluca_estbert_xpos_128_pipeline_en.md
new file mode 100644
index 00000000000000..9bcfb2bb5be8e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_sayula_popoluca_estbert_xpos_128_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_sayula_popoluca_estbert_xpos_128_pipeline pipeline BertForTokenClassification from tartuNLP
+author: John Snow Labs
+name: bert_sayula_popoluca_estbert_xpos_128_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sayula_popoluca_estbert_xpos_128_pipeline` is a English model originally trained by tartuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sayula_popoluca_estbert_xpos_128_pipeline_en_5.5.0_3.0_1725478143063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sayula_popoluca_estbert_xpos_128_pipeline_en_5.5.0_3.0_1725478143063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_sayula_popoluca_estbert_xpos_128_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_sayula_popoluca_estbert_xpos_128_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_sayula_popoluca_estbert_xpos_128_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+https://huggingface.co/tartuNLP/EstBERT_XPOS_128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_en.md
new file mode 100644
index 00000000000000..d0afd97dc449ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1 MPNetEmbeddings from abhijitt
+author: John Snow Labs
+name: bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1` is a English model originally trained by abhijitt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_en_5.5.0_3.0_1725470408881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_en_5.5.0_3.0_1725470408881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/abhijitt/bert_st_qa_all-mpnet-base-v2-epochs-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline_en.md
new file mode 100644
index 00000000000000..a4d9c9a97f9aa5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline pipeline MPNetEmbeddings from abhijitt
+author: John Snow Labs
+name: bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline` is a English model originally trained by abhijitt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline_en_5.5.0_3.0_1725470430220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline_en_5.5.0_3.0_1725470430220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_southern_sotho_qa_all_mpnet_base_v2_epochs_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/abhijitt/bert_st_qa_all-mpnet-base-v2-epochs-1
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline_en.md
new file mode 100644
index 00000000000000..370b722840cda9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline pipeline MPNetEmbeddings from abhijitt
+author: John Snow Labs
+name: bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline` is a English model originally trained by abhijitt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline_en_5.5.0_3.0_1725470790961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline_en_5.5.0_3.0_1725470790961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/abhijitt/bert_st_qa_multi-qa-mpnet-base-dot-v1-epochs-10
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_base_swedish_lowermix_reallysimple_ner_sv.md b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_base_swedish_lowermix_reallysimple_ner_sv.md
new file mode 100644
index 00000000000000..9316cf720bfc04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_base_swedish_lowermix_reallysimple_ner_sv.md
@@ -0,0 +1,99 @@
+---
+layout: model
+title: Swedish BertForTokenClassification Base Cased model (from KBLab)
+author: John Snow Labs
+name: bert_token_classifier_base_swedish_lowermix_reallysimple_ner
+date: 2024-09-04
+tags: [sv, open_source, bert, token_classification, ner, onnx]
+task: Named Entity Recognition
+language: sv
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-swedish-lowermix-reallysimple-ner` is a Swedish model originally trained by `KBLab`.
+
+## Predicted Entities
+
+`ORG`, `PRS`, `TME`, `EVN`, `MSR`, `WRK`, `OBJ`, `LOC`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_base_swedish_lowermix_reallysimple_ner_sv_5.5.0_3.0_1725477967384.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_base_swedish_lowermix_reallysimple_ner_sv_5.5.0_3.0_1725477967384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_base_swedish_lowermix_reallysimple_ner","sv") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_base_swedish_lowermix_reallysimple_ner","sv")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_base_swedish_lowermix_reallysimple_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|sv|
+|Size:|465.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/KBLab/bert-base-swedish-lowermix-reallysimple-ner
+- https://kb-labb.github.io/posts/2022-02-07-sucx3_ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_berturk_128k_keyword_discriminator_tr.md b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_berturk_128k_keyword_discriminator_tr.md
new file mode 100644
index 00000000000000..4da3010f77cd2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_berturk_128k_keyword_discriminator_tr.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: Turkish BertForTokenClassification Cased model (from yanekyuk)
+author: John Snow Labs
+name: bert_token_classifier_berturk_128k_keyword_discriminator
+date: 2024-09-04
+tags: [tr, open_source, bert, token_classification, ner, onnx]
+task: Named Entity Recognition
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `berturk-128k-keyword-discriminator` is a Turkish model originally trained by `yanekyuk`.
+
+## Predicted Entities
+
+`ENT`, `CON`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_berturk_128k_keyword_discriminator_tr_5.5.0_3.0_1725477952101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_berturk_128k_keyword_discriminator_tr_5.5.0_3.0_1725477952101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_berturk_128k_keyword_discriminator","tr") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_berturk_128k_keyword_discriminator","tr")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_berturk_128k_keyword_discriminator|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|tr|
+|Size:|689.0 MB|
+
+## References
+
+References
+
+- https://huggingface.co/yanekyuk/berturk-128k-keyword-discriminator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_danish_botxo_ner_dane_da.md b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_danish_botxo_ner_dane_da.md
new file mode 100644
index 00000000000000..96a8c4cbebfd4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_danish_botxo_ner_dane_da.md
@@ -0,0 +1,112 @@
+---
+layout: model
+title: Danish BertForTokenClassification Cased model (from Maltehb)
+author: John Snow Labs
+name: bert_token_classifier_danish_botxo_ner_dane
+date: 2024-09-04
+tags: [da, open_source, bert, token_classification, ner, onnx]
+task: Named Entity Recognition
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `danish-bert-botxo-ner-dane` is a Danish model originally trained by `Maltehb`.
+
+## Predicted Entities
+
+`ORG`, `PER`, `[CLS]`, `[SEP]`, `LOC`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_danish_botxo_ner_dane_da_5.5.0_3.0_1725450239519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_danish_botxo_ner_dane_da_5.5.0_3.0_1725450239519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_danish_botxo_ner_dane","da") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_danish_botxo_ner_dane","da")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_danish_botxo_ner_dane|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|da|
+|Size:|412.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Maltehb/danish-bert-botxo-ner-dane
+- #danish-bert-version-2-uncased-by-certainlyhttpscertainlyio-previously-known-as-botxo-finetuned-for-named-entity-recognition-on-the-dane-datasethttpsdanlpalexandradk304bd159d5dedatasetsddtzip-hvingelby-et-al-2020-by-malte-højmark-bertelsen
+- https://certainly.io/
+- https://danlp.alexandra.dk/304bd159d5de/datasets/ddt.zip
+- https://certainly.io/
+- https://danlp.alexandra.dk/304bd159d5de/datasets/ddt.zip
+- https://certainly.io/
+- https://github.com/certainlyio/nordic_bert
+- https://www.certainly.io/blog/danish-bert-model/
+- https://www.dropbox.com/s/19cjaoqvv2jicq9/danish_bert_uncased_v2.zip?dl=1
+- https://github.com/botxo/nordic_bert
+- https://www.aclweb.org/anthology/2020.lrec-1.565
+- https://twitter.com/malteH_B
+- https://www.linkedin.com/in/malte-h%C3%B8jmark-bertelsen-9a618017b/
+- https://www.instagram.com/maltemusen/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_danish_botxo_ner_dane_pipeline_da.md b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_danish_botxo_ner_dane_pipeline_da.md
new file mode 100644
index 00000000000000..294f4a42f5f199
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_danish_botxo_ner_dane_pipeline_da.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Danish bert_token_classifier_danish_botxo_ner_dane_pipeline pipeline BertForTokenClassification from Maltehb
+author: John Snow Labs
+name: bert_token_classifier_danish_botxo_ner_dane_pipeline
+date: 2024-09-04
+tags: [da, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: da
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_token_classifier_danish_botxo_ner_dane_pipeline` is a Danish model originally trained by Maltehb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_danish_botxo_ner_dane_pipeline_da_5.5.0_3.0_1725450260285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_danish_botxo_ner_dane_pipeline_da_5.5.0_3.0_1725450260285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_token_classifier_danish_botxo_ner_dane_pipeline", lang = "da")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_token_classifier_danish_botxo_ner_dane_pipeline", lang = "da")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_danish_botxo_ner_dane_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|da|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/Maltehb/danish-bert-botxo-ner-dane
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_parsbert_ner_fa.md b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_parsbert_ner_fa.md
new file mode 100644
index 00000000000000..7096a855bce4cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_parsbert_ner_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian bert_token_classifier_parsbert_ner BertForTokenClassification from HooshvareLab
+author: John Snow Labs
+name: bert_token_classifier_parsbert_ner
+date: 2024-09-04
+tags: [fa, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_token_classifier_parsbert_ner` is a Persian model originally trained by HooshvareLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_parsbert_ner_fa_5.5.0_3.0_1725477866735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_parsbert_ner_fa_5.5.0_3.0_1725477866735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_token_classifier_parsbert_ner","fa") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_parsbert_ner", "fa")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_parsbert_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|fa|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/bert-base-parsbert-ner-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_parsbert_ner_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_parsbert_ner_pipeline_fa.md
new file mode 100644
index 00000000000000..6f5c28e20df9a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_token_classifier_parsbert_ner_pipeline_fa.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Persian bert_token_classifier_parsbert_ner_pipeline pipeline BertForTokenClassification from HooshvareLab
+author: John Snow Labs
+name: bert_token_classifier_parsbert_ner_pipeline
+date: 2024-09-04
+tags: [fa, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_token_classifier_parsbert_ner_pipeline` is a Persian model originally trained by HooshvareLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_parsbert_ner_pipeline_fa_5.5.0_3.0_1725477897238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_parsbert_ner_pipeline_fa_5.5.0_3.0_1725477897238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_token_classifier_parsbert_ner_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_token_classifier_parsbert_ner_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_parsbert_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/bert-base-parsbert-ner-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bertrade_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-04-bertrade_camembert_en.md
new file mode 100644
index 00000000000000..c5a812c4d586a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bertrade_camembert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bertrade_camembert CamemBertEmbeddings from lgrobol
+author: John Snow Labs
+name: bertrade_camembert
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertrade_camembert` is a English model originally trained by lgrobol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertrade_camembert_en_5.5.0_3.0_1725442657307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertrade_camembert_en_5.5.0_3.0_1725442657307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("bertrade_camembert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("bertrade_camembert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertrade_camembert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/lgrobol/BERTrade-camemBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bertrade_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bertrade_camembert_pipeline_en.md
new file mode 100644
index 00000000000000..1cfa5f6e062bee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bertrade_camembert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bertrade_camembert_pipeline pipeline CamemBertEmbeddings from lgrobol
+author: John Snow Labs
+name: bertrade_camembert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertrade_camembert_pipeline` is a English model originally trained by lgrobol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertrade_camembert_pipeline_en_5.5.0_3.0_1725442678048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertrade_camembert_pipeline_en_5.5.0_3.0_1725442678048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertrade_camembert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertrade_camembert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertrade_camembert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/lgrobol/BERTrade-camemBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-beto_finetuned_ner_3_es.md b/docs/_posts/ahmedlone127/2024-09-04-beto_finetuned_ner_3_es.md
new file mode 100644
index 00000000000000..588ef2ec3d4dd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-beto_finetuned_ner_3_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish beto_finetuned_ner_3 BertForTokenClassification from ifis
+author: John Snow Labs
+name: beto_finetuned_ner_3
+date: 2024-09-04
+tags: [es, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner_3` is a Castilian, Spanish model originally trained by ifis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_3_es_5.5.0_3.0_1725450364675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_3_es_5.5.0_3.0_1725450364675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("beto_finetuned_ner_3","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("beto_finetuned_ner_3", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beto_finetuned_ner_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|409.6 MB|
+
+## References
+
+https://huggingface.co/ifis/BETO-finetuned-ner-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bias_detection_model_en.md b/docs/_posts/ahmedlone127/2024-09-04-bias_detection_model_en.md
new file mode 100644
index 00000000000000..65b9dd7bdddeab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bias_detection_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bias_detection_model DistilBertForTokenClassification from GXLooong
+author: John Snow Labs
+name: bias_detection_model
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_detection_model` is a English model originally trained by GXLooong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_detection_model_en_5.5.0_3.0_1725461186280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_detection_model_en_5.5.0_3.0_1725461186280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("bias_detection_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("bias_detection_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_detection_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/GXLooong/bias_detection_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bias_detection_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bias_detection_model_pipeline_en.md
new file mode 100644
index 00000000000000..baa440215d1242
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bias_detection_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bias_detection_model_pipeline pipeline DistilBertForTokenClassification from GXLooong
+author: John Snow Labs
+name: bias_detection_model_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_detection_model_pipeline` is a English model originally trained by GXLooong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_detection_model_pipeline_en_5.5.0_3.0_1725461197986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_detection_model_pipeline_en_5.5.0_3.0_1725461197986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bias_detection_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bias_detection_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_detection_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/GXLooong/bias_detection_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-binary_token_classification_model_en.md b/docs/_posts/ahmedlone127/2024-09-04-binary_token_classification_model_en.md
new file mode 100644
index 00000000000000..376f4c734489b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-binary_token_classification_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English binary_token_classification_model DistilBertForTokenClassification from sjtukai
+author: John Snow Labs
+name: binary_token_classification_model
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`binary_token_classification_model` is a English model originally trained by sjtukai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/binary_token_classification_model_en_5.5.0_3.0_1725476440170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/binary_token_classification_model_en_5.5.0_3.0_1725476440170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("binary_token_classification_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("binary_token_classification_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|binary_token_classification_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sjtukai/binary_token_classification_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-biobert_huner_chemical_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-biobert_huner_chemical_v1_en.md
new file mode 100644
index 00000000000000..02c8aee238324b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-biobert_huner_chemical_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biobert_huner_chemical_v1 BertForTokenClassification from aitslab
+author: John Snow Labs
+name: biobert_huner_chemical_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_huner_chemical_v1` is a English model originally trained by aitslab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_huner_chemical_v1_en_5.5.0_3.0_1725449906021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_huner_chemical_v1_en_5.5.0_3.0_1725449906021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("biobert_huner_chemical_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("biobert_huner_chemical_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_huner_chemical_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/aitslab/biobert_huner_chemical_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-biobert_huner_chemical_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-biobert_huner_chemical_v1_pipeline_en.md
new file mode 100644
index 00000000000000..4264c33ff06c32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-biobert_huner_chemical_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biobert_huner_chemical_v1_pipeline pipeline BertForTokenClassification from aitslab
+author: John Snow Labs
+name: biobert_huner_chemical_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_huner_chemical_v1_pipeline` is a English model originally trained by aitslab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_huner_chemical_v1_pipeline_en_5.5.0_3.0_1725449926093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_huner_chemical_v1_pipeline_en_5.5.0_3.0_1725449926093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobert_huner_chemical_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobert_huner_chemical_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_huner_chemical_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/aitslab/biobert_huner_chemical_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-blair_roberta_base_generative_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-blair_roberta_base_generative_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..002933411fe624
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-blair_roberta_base_generative_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English blair_roberta_base_generative_sentiment_pipeline pipeline RoBertaForSequenceClassification from alapanik
+author: John Snow Labs
+name: blair_roberta_base_generative_sentiment_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`blair_roberta_base_generative_sentiment_pipeline` is a English model originally trained by alapanik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/blair_roberta_base_generative_sentiment_pipeline_en_5.5.0_3.0_1725452927916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/blair_roberta_base_generative_sentiment_pipeline_en_5.5.0_3.0_1725452927916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("blair_roberta_base_generative_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("blair_roberta_base_generative_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|blair_roberta_base_generative_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.1 MB|
+
+## References
+
+https://huggingface.co/alapanik/blair-roberta-base-generative-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-blink_crossencoder_bert_large_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-04-blink_crossencoder_bert_large_uncased_en.md
new file mode 100644
index 00000000000000..078954da91f752
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-blink_crossencoder_bert_large_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English blink_crossencoder_bert_large_uncased BertForSequenceClassification from shomez
+author: John Snow Labs
+name: blink_crossencoder_bert_large_uncased
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`blink_crossencoder_bert_large_uncased` is a English model originally trained by shomez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/blink_crossencoder_bert_large_uncased_en_5.5.0_3.0_1725432874362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/blink_crossencoder_bert_large_uncased_en_5.5.0_3.0_1725432874362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("blink_crossencoder_bert_large_uncased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("blink_crossencoder_bert_large_uncased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|blink_crossencoder_bert_large_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/shomez/blink-crossencoder-bert-large-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-blink_crossencoder_bert_large_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-blink_crossencoder_bert_large_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..05377f02a46cef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-blink_crossencoder_bert_large_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English blink_crossencoder_bert_large_uncased_pipeline pipeline BertForSequenceClassification from shomez
+author: John Snow Labs
+name: blink_crossencoder_bert_large_uncased_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`blink_crossencoder_bert_large_uncased_pipeline` is a English model originally trained by shomez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/blink_crossencoder_bert_large_uncased_pipeline_en_5.5.0_3.0_1725432935906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/blink_crossencoder_bert_large_uncased_pipeline_en_5.5.0_3.0_1725432935906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("blink_crossencoder_bert_large_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("blink_crossencoder_bert_large_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|blink_crossencoder_bert_large_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/shomez/blink-crossencoder-bert-large-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bmg_translation_lug_english_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-bmg_translation_lug_english_v2_en.md
new file mode 100644
index 00000000000000..f16bf0c48fb1ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bmg_translation_lug_english_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bmg_translation_lug_english_v2 MarianTransformer from atwine
+author: John Snow Labs
+name: bmg_translation_lug_english_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bmg_translation_lug_english_v2` is a English model originally trained by atwine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bmg_translation_lug_english_v2_en_5.5.0_3.0_1725494321261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bmg_translation_lug_english_v2_en_5.5.0_3.0_1725494321261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("bmg_translation_lug_english_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("bmg_translation_lug_english_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bmg_translation_lug_english_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|513.4 MB|
+
+## References
+
+https://huggingface.co/atwine/bmg-translation-lug-en-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bmg_translation_lug_english_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-bmg_translation_lug_english_v2_pipeline_en.md
new file mode 100644
index 00000000000000..e0bd8c527d0205
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bmg_translation_lug_english_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bmg_translation_lug_english_v2_pipeline pipeline MarianTransformer from atwine
+author: John Snow Labs
+name: bmg_translation_lug_english_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bmg_translation_lug_english_v2_pipeline` is a English model originally trained by atwine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bmg_translation_lug_english_v2_pipeline_en_5.5.0_3.0_1725494349179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bmg_translation_lug_english_v2_pipeline_en_5.5.0_3.0_1725494349179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bmg_translation_lug_english_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bmg_translation_lug_english_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bmg_translation_lug_english_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|514.0 MB|
+
+## References
+
+https://huggingface.co/atwine/bmg-translation-lug-en-v2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bob_oriya_not_bob_en.md b/docs/_posts/ahmedlone127/2024-09-04-bob_oriya_not_bob_en.md
new file mode 100644
index 00000000000000..0799f01880c2d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bob_oriya_not_bob_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bob_oriya_not_bob DistilBertForSequenceClassification from MathNcl
+author: John Snow Labs
+name: bob_oriya_not_bob
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bob_oriya_not_bob` is a English model originally trained by MathNcl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bob_oriya_not_bob_en_5.5.0_3.0_1725490127642.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bob_oriya_not_bob_en_5.5.0_3.0_1725490127642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bob_oriya_not_bob","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bob_oriya_not_bob", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bob_oriya_not_bob|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MathNcl/Bob_or_not_Bob
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-book_recognizer_en.md b/docs/_posts/ahmedlone127/2024-09-04-book_recognizer_en.md
new file mode 100644
index 00000000000000..376f73df4d0721
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-book_recognizer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English book_recognizer DistilBertForSequenceClassification from LaLaf93
+author: John Snow Labs
+name: book_recognizer
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`book_recognizer` is a English model originally trained by LaLaf93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/book_recognizer_en_5.5.0_3.0_1725489781725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/book_recognizer_en_5.5.0_3.0_1725489781725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("book_recognizer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("book_recognizer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|book_recognizer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LaLaf93/book_recognizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-brand_classification_20240715_model_distilbert_0_9835_en.md b/docs/_posts/ahmedlone127/2024-09-04-brand_classification_20240715_model_distilbert_0_9835_en.md
new file mode 100644
index 00000000000000..1c4f31f9452b76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-brand_classification_20240715_model_distilbert_0_9835_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brand_classification_20240715_model_distilbert_0_9835 DistilBertForSequenceClassification from jointriple
+author: John Snow Labs
+name: brand_classification_20240715_model_distilbert_0_9835
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brand_classification_20240715_model_distilbert_0_9835` is a English model originally trained by jointriple.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brand_classification_20240715_model_distilbert_0_9835_en_5.5.0_3.0_1725489960301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brand_classification_20240715_model_distilbert_0_9835_en_5.5.0_3.0_1725489960301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("brand_classification_20240715_model_distilbert_0_9835","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("brand_classification_20240715_model_distilbert_0_9835", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brand_classification_20240715_model_distilbert_0_9835|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|252.9 MB|
+
+## References
+
+https://huggingface.co/jointriple/brand_classification_20240715_model_distilbert_0_9835
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-brand_classification_20240715_model_distilbert_0_9835_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-brand_classification_20240715_model_distilbert_0_9835_pipeline_en.md
new file mode 100644
index 00000000000000..1cd3755927afe7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-brand_classification_20240715_model_distilbert_0_9835_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brand_classification_20240715_model_distilbert_0_9835_pipeline pipeline DistilBertForSequenceClassification from jointriple
+author: John Snow Labs
+name: brand_classification_20240715_model_distilbert_0_9835_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brand_classification_20240715_model_distilbert_0_9835_pipeline` is a English model originally trained by jointriple.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brand_classification_20240715_model_distilbert_0_9835_pipeline_en_5.5.0_3.0_1725489972469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brand_classification_20240715_model_distilbert_0_9835_pipeline_en_5.5.0_3.0_1725489972469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brand_classification_20240715_model_distilbert_0_9835_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brand_classification_20240715_model_distilbert_0_9835_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brand_classification_20240715_model_distilbert_0_9835_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|253.0 MB|
+
+## References
+
+https://huggingface.co/jointriple/brand_classification_20240715_model_distilbert_0_9835
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bsc_bio_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-bsc_bio_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..45e23ab0565626
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bsc_bio_spanish_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish bsc_bio_spanish_pipeline pipeline RoBertaEmbeddings from PlanTL-GOB-ES
+author: John Snow Labs
+name: bsc_bio_spanish_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_spanish_pipeline` is a Castilian, Spanish model originally trained by PlanTL-GOB-ES.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_spanish_pipeline_es_5.5.0_3.0_1725413276995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_spanish_pipeline_es_5.5.0_3.0_1725413276995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bsc_bio_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bsc_bio_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|295.5 MB|
+
+## References
+
+https://huggingface.co/PlanTL-GOB-ES/bsc-bio-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_eli5_mlm_model_jzkv5_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_eli5_mlm_model_jzkv5_en.md
new file mode 100644
index 00000000000000..d2358ba2ee013d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_eli5_mlm_model_jzkv5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_jzkv5 RoBertaEmbeddings from jzkv5
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_jzkv5
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_jzkv5` is a English model originally trained by jzkv5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_jzkv5_en_5.5.0_3.0_1725412308675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_jzkv5_en_5.5.0_3.0_1725412308675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_jzkv5","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_jzkv5","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_jzkv5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jzkv5/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_eli5_mlm_model_jzkv5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_eli5_mlm_model_jzkv5_pipeline_en.md
new file mode 100644
index 00000000000000..7c8f852d525741
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_eli5_mlm_model_jzkv5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_jzkv5_pipeline pipeline RoBertaEmbeddings from jzkv5
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_jzkv5_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_jzkv5_pipeline` is a English model originally trained by jzkv5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_jzkv5_pipeline_en_5.5.0_3.0_1725412328716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_jzkv5_pipeline_en_5.5.0_3.0_1725412328716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_jzkv5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_jzkv5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_jzkv5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jzkv5/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_model_2_nicolehao7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_model_2_nicolehao7_pipeline_en.md
new file mode 100644
index 00000000000000..7163e02c9a18e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_model_2_nicolehao7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_2_nicolehao7_pipeline pipeline DistilBertForSequenceClassification from nicolehao7
+author: John Snow Labs
+name: burmese_awesome_model_2_nicolehao7_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_2_nicolehao7_pipeline` is a English model originally trained by nicolehao7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_2_nicolehao7_pipeline_en_5.5.0_3.0_1725490282038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_2_nicolehao7_pipeline_en_5.5.0_3.0_1725490282038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_2_nicolehao7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_2_nicolehao7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_2_nicolehao7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/nicolehao7/my_awesome_model_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_40_len_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_40_len_en.md
new file mode 100644
index 00000000000000..6498400ad99e8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_40_len_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_40_len RoBertaForQuestionAnswering from yashwan2003
+author: John Snow Labs
+name: burmese_awesome_qa_model_40_len
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_40_len` is a English model originally trained by yashwan2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_40_len_en_5.5.0_3.0_1725483814742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_40_len_en_5.5.0_3.0_1725483814742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("burmese_awesome_qa_model_40_len","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("burmese_awesome_qa_model_40_len", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_40_len|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/yashwan2003/my_awesome_qa_model_40_len
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_johann_h_a_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_johann_h_a_en.md
new file mode 100644
index 00000000000000..02662d8b6e05c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_johann_h_a_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_johann_h_a DistilBertForQuestionAnswering from johann-h-a
+author: John Snow Labs
+name: burmese_awesome_qa_model_johann_h_a
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_johann_h_a` is a English model originally trained by johann-h-a.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_johann_h_a_en_5.5.0_3.0_1725465678854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_johann_h_a_en_5.5.0_3.0_1725465678854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_johann_h_a","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_johann_h_a", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_johann_h_a|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/johann-h-a/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_johann_h_a_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_johann_h_a_pipeline_en.md
new file mode 100644
index 00000000000000..07e9b0ecb5c726
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_qa_model_johann_h_a_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_johann_h_a_pipeline pipeline DistilBertForQuestionAnswering from johann-h-a
+author: John Snow Labs
+name: burmese_awesome_qa_model_johann_h_a_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_johann_h_a_pipeline` is a English model originally trained by johann-h-a.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_johann_h_a_pipeline_en_5.5.0_3.0_1725465691518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_johann_h_a_pipeline_en_5.5.0_3.0_1725465691518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_johann_h_a_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_johann_h_a_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_johann_h_a_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/johann-h-a/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_roberta_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_roberta_model_pipeline_en.md
new file mode 100644
index 00000000000000..83840cf97e91a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_roberta_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_roberta_model_pipeline pipeline DistilBertForTokenClassification from Meli-nlp
+author: John Snow Labs
+name: burmese_awesome_roberta_model_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_roberta_model_pipeline` is a English model originally trained by Meli-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_roberta_model_pipeline_en_5.5.0_3.0_1725461308528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_roberta_model_pipeline_en_5.5.0_3.0_1725461308528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_roberta_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_roberta_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_roberta_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|367.9 MB|
+
+## References
+
+https://huggingface.co/Meli-nlp/my_awesome_roberta_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_setfit_model_watwat100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_setfit_model_watwat100_pipeline_en.md
new file mode 100644
index 00000000000000..1f7b47a4bf19d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_setfit_model_watwat100_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_watwat100_pipeline pipeline MPNetEmbeddings from Watwat100
+author: John Snow Labs
+name: burmese_awesome_setfit_model_watwat100_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_watwat100_pipeline` is a English model originally trained by Watwat100.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_watwat100_pipeline_en_5.5.0_3.0_1725470410718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_watwat100_pipeline_en_5.5.0_3.0_1725470410718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_setfit_model_watwat100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_watwat100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_watwat100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/Watwat100/my-awesome-setfit-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_actor_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_actor_en.md
new file mode 100644
index 00000000000000..98ebf50aff8ccd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_actor_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_actor DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_actor
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_actor` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_actor_en_5.5.0_3.0_1725461087508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_actor_en_5.5.0_3.0_1725461087508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_actor","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_actor", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_actor|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_Actor
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_neg_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_neg_en.md
new file mode 100644
index 00000000000000..dd3dceed0860ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_neg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_all_neg DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_all_neg
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_neg` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_neg_en_5.5.0_3.0_1725460486574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_neg_en_5.5.0_3.0_1725460486574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_neg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_neg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_all_neg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_NEG
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_neg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_neg_pipeline_en.md
new file mode 100644
index 00000000000000..c0fdc6af2715e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_neg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_all_neg_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_all_neg_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_neg_pipeline` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_neg_pipeline_en_5.5.0_3.0_1725460498363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_neg_pipeline_en_5.5.0_3.0_1725460498363.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_all_neg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_all_neg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_all_neg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_NEG
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_time_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_time_en.md
new file mode 100644
index 00000000000000..d4e55c1a260043
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_all_time_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_all_time DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_all_time
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_time` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_time_en_5.5.0_3.0_1725448780201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_time_en_5.5.0_3.0_1725448780201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_time","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_time", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_all_time|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_Time
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_almifosa_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_almifosa_en.md
new file mode 100644
index 00000000000000..cf96007e89b69c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_almifosa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_almifosa DistilBertForTokenClassification from almifosa
+author: John Snow Labs
+name: burmese_awesome_wnut_model_almifosa
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_almifosa` is a English model originally trained by almifosa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_almifosa_en_5.5.0_3.0_1725448198940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_almifosa_en_5.5.0_3.0_1725448198940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_almifosa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_almifosa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_almifosa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/almifosa/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_asrajgct_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_asrajgct_pipeline_en.md
new file mode 100644
index 00000000000000..76c25a1a9359fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_asrajgct_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_asrajgct_pipeline pipeline DistilBertForTokenClassification from asrajgct
+author: John Snow Labs
+name: burmese_awesome_wnut_model_asrajgct_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_asrajgct_pipeline` is a English model originally trained by asrajgct.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_asrajgct_pipeline_en_5.5.0_3.0_1725475776767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_asrajgct_pipeline_en_5.5.0_3.0_1725475776767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_asrajgct_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_asrajgct_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_asrajgct_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/asrajgct/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_charliefederer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_charliefederer_pipeline_en.md
new file mode 100644
index 00000000000000..612e0a0d2ad65b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_charliefederer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_charliefederer_pipeline pipeline DistilBertForTokenClassification from Charliefederer
+author: John Snow Labs
+name: burmese_awesome_wnut_model_charliefederer_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_charliefederer_pipeline` is a English model originally trained by Charliefederer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_charliefederer_pipeline_en_5.5.0_3.0_1725492457451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_charliefederer_pipeline_en_5.5.0_3.0_1725492457451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_charliefederer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_charliefederer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_charliefederer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Charliefederer/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_claire5776_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_claire5776_en.md
new file mode 100644
index 00000000000000..83bfb63e1f0d68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_claire5776_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_claire5776 DistilBertForTokenClassification from claire5776
+author: John Snow Labs
+name: burmese_awesome_wnut_model_claire5776
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_claire5776` is a English model originally trained by claire5776.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_claire5776_en_5.5.0_3.0_1725448590150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_claire5776_en_5.5.0_3.0_1725448590150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_claire5776","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_claire5776", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_claire5776|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/claire5776/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_derf989_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_derf989_en.md
new file mode 100644
index 00000000000000..ecbe295083bf91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_derf989_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_derf989 DistilBertForTokenClassification from Derf989
+author: John Snow Labs
+name: burmese_awesome_wnut_model_derf989
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_derf989` is a English model originally trained by Derf989.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_derf989_en_5.5.0_3.0_1725460817327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_derf989_en_5.5.0_3.0_1725460817327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_derf989","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_derf989", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_derf989|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Derf989/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_derf989_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_derf989_pipeline_en.md
new file mode 100644
index 00000000000000..5c48f394ae6e46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_derf989_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_derf989_pipeline pipeline DistilBertForTokenClassification from Derf989
+author: John Snow Labs
+name: burmese_awesome_wnut_model_derf989_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_derf989_pipeline` is a English model originally trained by Derf989.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_derf989_pipeline_en_5.5.0_3.0_1725460829175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_derf989_pipeline_en_5.5.0_3.0_1725460829175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_derf989_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_derf989_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_derf989_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Derf989/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_diodiodada_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_diodiodada_pipeline_en.md
new file mode 100644
index 00000000000000..261efef97edbbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_diodiodada_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_diodiodada_pipeline pipeline DistilBertForTokenClassification from diodiodada
+author: John Snow Labs
+name: burmese_awesome_wnut_model_diodiodada_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_diodiodada_pipeline` is a English model originally trained by diodiodada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_diodiodada_pipeline_en_5.5.0_3.0_1725461113869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_diodiodada_pipeline_en_5.5.0_3.0_1725461113869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_diodiodada_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_diodiodada_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_diodiodada_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/diodiodada/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_faaany_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_faaany_en.md
new file mode 100644
index 00000000000000..3f5b679fe055b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_faaany_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_faaany DistilBertForTokenClassification from faaany
+author: John Snow Labs
+name: burmese_awesome_wnut_model_faaany
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_faaany` is a English model originally trained by faaany.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_faaany_en_5.5.0_3.0_1725449004377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_faaany_en_5.5.0_3.0_1725449004377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_faaany","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_faaany", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_faaany|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/faaany/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_faaany_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_faaany_pipeline_en.md
new file mode 100644
index 00000000000000..7b6e48e0a2eb6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_faaany_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_faaany_pipeline pipeline DistilBertForTokenClassification from faaany
+author: John Snow Labs
+name: burmese_awesome_wnut_model_faaany_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_faaany_pipeline` is a English model originally trained by faaany.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_faaany_pipeline_en_5.5.0_3.0_1725449016818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_faaany_pipeline_en_5.5.0_3.0_1725449016818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_faaany_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_faaany_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_faaany_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/faaany/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_gaogao8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_gaogao8_pipeline_en.md
new file mode 100644
index 00000000000000..1778b662b85387
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_gaogao8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_gaogao8_pipeline pipeline DistilBertForTokenClassification from gaogao8
+author: John Snow Labs
+name: burmese_awesome_wnut_model_gaogao8_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_gaogao8_pipeline` is a English model originally trained by gaogao8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_gaogao8_pipeline_en_5.5.0_3.0_1725475776683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_gaogao8_pipeline_en_5.5.0_3.0_1725475776683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_gaogao8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_gaogao8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_gaogao8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gaogao8/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_giuliozab_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_giuliozab_pipeline_en.md
new file mode 100644
index 00000000000000..0a48b7701f1e27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_giuliozab_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_giuliozab_pipeline pipeline DistilBertForTokenClassification from GiulioZab
+author: John Snow Labs
+name: burmese_awesome_wnut_model_giuliozab_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_giuliozab_pipeline` is a English model originally trained by GiulioZab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_giuliozab_pipeline_en_5.5.0_3.0_1725476374532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_giuliozab_pipeline_en_5.5.0_3.0_1725476374532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_giuliozab_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_giuliozab_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_giuliozab_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/GiulioZab/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_hcy5561_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_hcy5561_en.md
new file mode 100644
index 00000000000000..0b9ca038be2b88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_hcy5561_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_hcy5561 DistilBertForTokenClassification from hcy5561
+author: John Snow Labs
+name: burmese_awesome_wnut_model_hcy5561
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_hcy5561` is a English model originally trained by hcy5561.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_hcy5561_en_5.5.0_3.0_1725448909203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_hcy5561_en_5.5.0_3.0_1725448909203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_hcy5561","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_hcy5561", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_hcy5561|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/hcy5561/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_hrodriguez_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_hrodriguez_en.md
new file mode 100644
index 00000000000000..45ea779123cffb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_hrodriguez_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_hrodriguez DistilBertForTokenClassification from hrodriguez
+author: John Snow Labs
+name: burmese_awesome_wnut_model_hrodriguez
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_hrodriguez` is a English model originally trained by hrodriguez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_hrodriguez_en_5.5.0_3.0_1725476107208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_hrodriguez_en_5.5.0_3.0_1725476107208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_hrodriguez","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_hrodriguez", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_hrodriguez|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/hrodriguez/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jaivy9_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jaivy9_en.md
new file mode 100644
index 00000000000000..2c6da0f90af48e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jaivy9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_jaivy9 DistilBertForTokenClassification from Jaivy9
+author: John Snow Labs
+name: burmese_awesome_wnut_model_jaivy9
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_jaivy9` is a English model originally trained by Jaivy9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jaivy9_en_5.5.0_3.0_1725475890778.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jaivy9_en_5.5.0_3.0_1725475890778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_jaivy9","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_jaivy9", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_jaivy9|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Jaivy9/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jaivy9_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jaivy9_pipeline_en.md
new file mode 100644
index 00000000000000..b1d18d9617cff7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jaivy9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_jaivy9_pipeline pipeline DistilBertForTokenClassification from Jaivy9
+author: John Snow Labs
+name: burmese_awesome_wnut_model_jaivy9_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_jaivy9_pipeline` is a English model originally trained by Jaivy9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jaivy9_pipeline_en_5.5.0_3.0_1725475902705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jaivy9_pipeline_en_5.5.0_3.0_1725475902705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_jaivy9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_jaivy9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_jaivy9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Jaivy9/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jhhan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jhhan_pipeline_en.md
new file mode 100644
index 00000000000000..dc51bad2642c1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_jhhan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_jhhan_pipeline pipeline DistilBertForTokenClassification from JHhan
+author: John Snow Labs
+name: burmese_awesome_wnut_model_jhhan_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_jhhan_pipeline` is a English model originally trained by JHhan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jhhan_pipeline_en_5.5.0_3.0_1725475776633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jhhan_pipeline_en_5.5.0_3.0_1725475776633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_jhhan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_jhhan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_jhhan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/JHhan/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_kirisamereimu_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_kirisamereimu_en.md
new file mode 100644
index 00000000000000..70a1bd828f3107
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_kirisamereimu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_kirisamereimu DistilBertForTokenClassification from KirisameReimu
+author: John Snow Labs
+name: burmese_awesome_wnut_model_kirisamereimu
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_kirisamereimu` is a English model originally trained by KirisameReimu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_kirisamereimu_en_5.5.0_3.0_1725448883244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_kirisamereimu_en_5.5.0_3.0_1725448883244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_kirisamereimu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_kirisamereimu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_kirisamereimu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/KirisameReimu/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_lmattes_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_lmattes_en.md
new file mode 100644
index 00000000000000..d6ffffcf6241a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_lmattes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_lmattes DistilBertForTokenClassification from lmattes
+author: John Snow Labs
+name: burmese_awesome_wnut_model_lmattes
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_lmattes` is a English model originally trained by lmattes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_lmattes_en_5.5.0_3.0_1725492979483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_lmattes_en_5.5.0_3.0_1725492979483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_lmattes","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_lmattes", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_lmattes|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/lmattes/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_malduwais_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_malduwais_pipeline_en.md
new file mode 100644
index 00000000000000..671ec65640ee95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_malduwais_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_malduwais_pipeline pipeline DistilBertForTokenClassification from malduwais
+author: John Snow Labs
+name: burmese_awesome_wnut_model_malduwais_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_malduwais_pipeline` is a English model originally trained by malduwais.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_malduwais_pipeline_en_5.5.0_3.0_1725448329921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_malduwais_pipeline_en_5.5.0_3.0_1725448329921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_malduwais_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_malduwais_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_malduwais_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/malduwais/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_minhminh09_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_minhminh09_en.md
new file mode 100644
index 00000000000000..fe3aa41d1bc557
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_minhminh09_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_minhminh09 DistilBertForTokenClassification from MinhMinh09
+author: John Snow Labs
+name: burmese_awesome_wnut_model_minhminh09
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_minhminh09` is a English model originally trained by MinhMinh09.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_minhminh09_en_5.5.0_3.0_1725448516671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_minhminh09_en_5.5.0_3.0_1725448516671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_minhminh09","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_minhminh09", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_minhminh09|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MinhMinh09/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_moumitanettojanamanna_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_moumitanettojanamanna_en.md
new file mode 100644
index 00000000000000..49c73c2a97e857
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_moumitanettojanamanna_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_moumitanettojanamanna DistilBertForTokenClassification from MoumitaNettoJanaManna
+author: John Snow Labs
+name: burmese_awesome_wnut_model_moumitanettojanamanna
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_moumitanettojanamanna` is a English model originally trained by MoumitaNettoJanaManna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_moumitanettojanamanna_en_5.5.0_3.0_1725475998939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_moumitanettojanamanna_en_5.5.0_3.0_1725475998939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_moumitanettojanamanna","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_moumitanettojanamanna", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_moumitanettojanamanna|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MoumitaNettoJanaManna/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_prbee_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_prbee_en.md
new file mode 100644
index 00000000000000..b90ffec1b48801
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_prbee_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_prbee DistilBertForTokenClassification from PrBee
+author: John Snow Labs
+name: burmese_awesome_wnut_model_prbee
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_prbee` is a English model originally trained by PrBee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_prbee_en_5.5.0_3.0_1725460654897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_prbee_en_5.5.0_3.0_1725460654897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_prbee","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_prbee", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_prbee|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/PrBee/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_robinsh2023_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_robinsh2023_en.md
new file mode 100644
index 00000000000000..15a6abb9da6a8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_robinsh2023_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_robinsh2023 DistilBertForTokenClassification from Robinsh2023
+author: John Snow Labs
+name: burmese_awesome_wnut_model_robinsh2023
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_robinsh2023` is a English model originally trained by Robinsh2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_robinsh2023_en_5.5.0_3.0_1725449029171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_robinsh2023_en_5.5.0_3.0_1725449029171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_robinsh2023","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_robinsh2023", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_robinsh2023|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Robinsh2023/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sai2970_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sai2970_en.md
new file mode 100644
index 00000000000000..d41a230baaee9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sai2970_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_sai2970 DistilBertForTokenClassification from Sai2970
+author: John Snow Labs
+name: burmese_awesome_wnut_model_sai2970
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sai2970` is a English model originally trained by Sai2970.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sai2970_en_5.5.0_3.0_1725492760722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sai2970_en_5.5.0_3.0_1725492760722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sai2970","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sai2970", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_sai2970|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Sai2970/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sai2970_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sai2970_pipeline_en.md
new file mode 100644
index 00000000000000..cdacad96375549
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sai2970_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_sai2970_pipeline pipeline DistilBertForTokenClassification from Sai2970
+author: John Snow Labs
+name: burmese_awesome_wnut_model_sai2970_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sai2970_pipeline` is a English model originally trained by Sai2970.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sai2970_pipeline_en_5.5.0_3.0_1725492772955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sai2970_pipeline_en_5.5.0_3.0_1725492772955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_sai2970_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_sai2970_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_sai2970_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Sai2970/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sgonzalezsilot_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sgonzalezsilot_en.md
new file mode 100644
index 00000000000000..7f2ddc07a8951b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_sgonzalezsilot_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_sgonzalezsilot DistilBertForTokenClassification from sgonzalezsilot
+author: John Snow Labs
+name: burmese_awesome_wnut_model_sgonzalezsilot
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sgonzalezsilot` is a English model originally trained by sgonzalezsilot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sgonzalezsilot_en_5.5.0_3.0_1725493010006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sgonzalezsilot_en_5.5.0_3.0_1725493010006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sgonzalezsilot","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sgonzalezsilot", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_sgonzalezsilot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sgonzalezsilot/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_urisoo_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_urisoo_en.md
new file mode 100644
index 00000000000000..81e7490724543e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_urisoo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_urisoo DistilBertForTokenClassification from urisoo
+author: John Snow Labs
+name: burmese_awesome_wnut_model_urisoo
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_urisoo` is a English model originally trained by urisoo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_urisoo_en_5.5.0_3.0_1725476111314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_urisoo_en_5.5.0_3.0_1725476111314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_urisoo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_urisoo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_urisoo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/urisoo/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_wzchen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_wzchen_pipeline_en.md
new file mode 100644
index 00000000000000..d07861649affef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_wzchen_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_wzchen_pipeline pipeline DistilBertForTokenClassification from wzChen
+author: John Snow Labs
+name: burmese_awesome_wnut_model_wzchen_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_wzchen_pipeline` is a English model originally trained by wzChen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_wzchen_pipeline_en_5.5.0_3.0_1725460965188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_wzchen_pipeline_en_5.5.0_3.0_1725460965188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_wzchen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_wzchen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_wzchen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/wzChen/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_saprotection_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_saprotection_en.md
new file mode 100644
index 00000000000000..d3e9396dbb43f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_saprotection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_saprotection DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_saprotection
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_saprotection` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_saprotection_en_5.5.0_3.0_1725460897653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_saprotection_en_5.5.0_3.0_1725460897653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_saprotection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_saprotection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_saprotection|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_SAprotection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_target_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_target_en.md
new file mode 100644
index 00000000000000..cb372757df796f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_target_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_target DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_target
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_target` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_target_en_5.5.0_3.0_1725493122424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_target_en_5.5.0_3.0_1725493122424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_target","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_target", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_target|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_Target
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_distilbert_en.md
new file mode 100644
index 00000000000000..61d08dfb7276eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_distilbert DistilBertForTokenClassification from yamini0506
+author: John Snow Labs
+name: burmese_distilbert
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_distilbert` is a English model originally trained by yamini0506.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_distilbert_en_5.5.0_3.0_1725460687595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_distilbert_en_5.5.0_3.0_1725460687595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_distilbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/yamini0506/my_distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..b4afba4b1dd398
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_distilbert_pipeline pipeline DistilBertForTokenClassification from yamini0506
+author: John Snow Labs
+name: burmese_distilbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_distilbert_pipeline` is a English model originally trained by yamini0506.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_distilbert_pipeline_en_5.5.0_3.0_1725460699424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_distilbert_pipeline_en_5.5.0_3.0_1725460699424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/yamini0506/my_distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_ws_extraction_model_27th_mar_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_ws_extraction_model_27th_mar_en.md
new file mode 100644
index 00000000000000..6cbe0ab83f7294
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_ws_extraction_model_27th_mar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ws_extraction_model_27th_mar DistilBertForTokenClassification from manimaranpa07
+author: John Snow Labs
+name: burmese_ws_extraction_model_27th_mar
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ws_extraction_model_27th_mar` is a English model originally trained by manimaranpa07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_27th_mar_en_5.5.0_3.0_1725448694504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_27th_mar_en_5.5.0_3.0_1725448694504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_ws_extraction_model_27th_mar","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_ws_extraction_model_27th_mar", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ws_extraction_model_27th_mar|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/manimaranpa07/my_Ws_extraction_model_27th_mar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_ws_extraction_model_27th_mar_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_ws_extraction_model_27th_mar_pipeline_en.md
new file mode 100644
index 00000000000000..bfc94e41311354
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_ws_extraction_model_27th_mar_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_ws_extraction_model_27th_mar_pipeline pipeline DistilBertForTokenClassification from manimaranpa07
+author: John Snow Labs
+name: burmese_ws_extraction_model_27th_mar_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ws_extraction_model_27th_mar_pipeline` is a English model originally trained by manimaranpa07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_27th_mar_pipeline_en_5.5.0_3.0_1725448706465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_27th_mar_pipeline_en_5.5.0_3.0_1725448706465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_ws_extraction_model_27th_mar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_ws_extraction_model_27th_mar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ws_extraction_model_27th_mar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/manimaranpa07/my_Ws_extraction_model_27th_mar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-camembert_base_dataikunlp_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-04-camembert_base_dataikunlp_pipeline_fr.md
new file mode 100644
index 00000000000000..49aa45422c1730
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-camembert_base_dataikunlp_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French camembert_base_dataikunlp_pipeline pipeline CamemBertEmbeddings from DataikuNLP
+author: John Snow Labs
+name: camembert_base_dataikunlp_pipeline
+date: 2024-09-04
+tags: [fr, open_source, pipeline, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_base_dataikunlp_pipeline` is a French model originally trained by DataikuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_dataikunlp_pipeline_fr_5.5.0_3.0_1725408482521.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_dataikunlp_pipeline_fr_5.5.0_3.0_1725408482521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("camembert_base_dataikunlp_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("camembert_base_dataikunlp_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_base_dataikunlp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/DataikuNLP/camembert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-camembert_base_test_model_mindcraft_nl_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-camembert_base_test_model_mindcraft_nl_pipeline_en.md
new file mode 100644
index 00000000000000..61024981956433
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-camembert_base_test_model_mindcraft_nl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English camembert_base_test_model_mindcraft_nl_pipeline pipeline CamemBertEmbeddings from mindcraft-nl
+author: John Snow Labs
+name: camembert_base_test_model_mindcraft_nl_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_base_test_model_mindcraft_nl_pipeline` is a English model originally trained by mindcraft-nl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_test_model_mindcraft_nl_pipeline_en_5.5.0_3.0_1725443980681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_test_model_mindcraft_nl_pipeline_en_5.5.0_3.0_1725443980681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("camembert_base_test_model_mindcraft_nl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("camembert_base_test_model_mindcraft_nl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_base_test_model_mindcraft_nl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mindcraft-nl/camembert-base-test-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3_en.md b/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3_en.md
new file mode 100644
index 00000000000000..4d90cfde9319dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3 CamemBertForSequenceClassification from AntoineD
+author: John Snow Labs
+name: camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3` is a English model originally trained by AntoineD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3_en_5.5.0_3.0_1725466903901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3_en_5.5.0_3.0_1725466903901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_ccnet_classification_analyse_visage_classifier_only_french_lr1e_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|265.9 MB|
+
+## References
+
+https://huggingface.co/AntoineD/camembert_ccnet_classification_analyse_visage_classifier-only_fr_lr1e-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_en.md b/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_en.md
new file mode 100644
index 00000000000000..10776742297625
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3 CamemBertForSequenceClassification from AntoineD
+author: John Snow Labs
+name: camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3` is a English model originally trained by AntoineD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_en_5.5.0_3.0_1725466494928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_en_5.5.0_3.0_1725466494928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|265.9 MB|
+
+## References
+
+https://huggingface.co/AntoineD/camembert_ccnet_classification_tools_classifier-only_fr_lr1e-3_V3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline_en.md
new file mode 100644
index 00000000000000..5a8d167df908a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline pipeline CamemBertForSequenceClassification from AntoineD
+author: John Snow Labs
+name: camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline` is a English model originally trained by AntoineD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline_en_5.5.0_3.0_1725466572671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline_en_5.5.0_3.0_1725466572671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_ccnet_classification_tools_classifier_only_french_lr1e_3_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|265.9 MB|
+
+## References
+
+https://huggingface.co/AntoineD/camembert_ccnet_classification_tools_classifier-only_fr_lr1e-3_V3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-camembert_mlm_en.md b/docs/_posts/ahmedlone127/2024-09-04-camembert_mlm_en.md
new file mode 100644
index 00000000000000..2959d08cd2b632
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-camembert_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English camembert_mlm CamemBertEmbeddings from Jodsa
+author: John Snow Labs
+name: camembert_mlm
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_mlm` is a English model originally trained by Jodsa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_mlm_en_5.5.0_3.0_1725444973257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_mlm_en_5.5.0_3.0_1725444973257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("camembert_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("camembert_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_mlm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|417.9 MB|
+
+## References
+
+https://huggingface.co/Jodsa/camembert_mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-car_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-04-car_sentiment_en.md
new file mode 100644
index 00000000000000..2576ae9883635d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-car_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English car_sentiment DistilBertForSequenceClassification from af41
+author: John Snow Labs
+name: car_sentiment
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_sentiment` is a English model originally trained by af41.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/car_sentiment_en_5.5.0_3.0_1725489504588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_sentiment_en_5.5.0_3.0_1725489504588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("car_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("car_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/af41/car_sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cft_clip_en.md b/docs/_posts/ahmedlone127/2024-09-04-cft_clip_en.md
new file mode 100644
index 00000000000000..b8b60da04dd45e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cft_clip_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English cft_clip CLIPForZeroShotClassification from humane-lab
+author: John Snow Labs
+name: cft_clip
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cft_clip` is a English model originally trained by humane-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cft_clip_en_5.5.0_3.0_1725455827723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cft_clip_en_5.5.0_3.0_1725455827723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("cft_clip","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("cft_clip","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cft_clip|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/humane-lab/CFT-CLIP
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cft_clip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-cft_clip_pipeline_en.md
new file mode 100644
index 00000000000000..391f68dd0bd37b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cft_clip_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cft_clip_pipeline pipeline CLIPForZeroShotClassification from humane-lab
+author: John Snow Labs
+name: cft_clip_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cft_clip_pipeline` is a English model originally trained by humane-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cft_clip_pipeline_en_5.5.0_3.0_1725455948885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cft_clip_pipeline_en_5.5.0_3.0_1725455948885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cft_clip_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cft_clip_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cft_clip_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/humane-lab/CFT-CLIP
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-chatrag_deberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-chatrag_deberta_pipeline_en.md
new file mode 100644
index 00000000000000..902cd451980707
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-chatrag_deberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English chatrag_deberta_pipeline pipeline DeBertaForSequenceClassification from AgentPublic
+author: John Snow Labs
+name: chatrag_deberta_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chatrag_deberta_pipeline` is a English model originally trained by AgentPublic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chatrag_deberta_pipeline_en_5.5.0_3.0_1725439963751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chatrag_deberta_pipeline_en_5.5.0_3.0_1725439963751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chatrag_deberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chatrag_deberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chatrag_deberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.5 MB|
+
+## References
+
+https://huggingface.co/AgentPublic/chatrag-deberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-checkpoint_13600_en.md b/docs/_posts/ahmedlone127/2024-09-04-checkpoint_13600_en.md
new file mode 100644
index 00000000000000..faa4da571bed0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-checkpoint_13600_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English checkpoint_13600 XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: checkpoint_13600
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkpoint_13600` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoint_13600_en_5.5.0_3.0_1725417284180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoint_13600_en_5.5.0_3.0_1725417284180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("checkpoint_13600","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("checkpoint_13600","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|checkpoint_13600|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-13600
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-checkpoint_13600_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-checkpoint_13600_pipeline_en.md
new file mode 100644
index 00000000000000..cf45375a2be55d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-checkpoint_13600_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English checkpoint_13600_pipeline pipeline XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: checkpoint_13600_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkpoint_13600_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoint_13600_pipeline_en_5.5.0_3.0_1725417345883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoint_13600_pipeline_en_5.5.0_3.0_1725417345883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("checkpoint_13600_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("checkpoint_13600_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|checkpoint_13600_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-13600
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-classify_isin_step3_en.md b/docs/_posts/ahmedlone127/2024-09-04-classify_isin_step3_en.md
new file mode 100644
index 00000000000000..002e786325d450
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-classify_isin_step3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English classify_isin_step3 AlbertForSequenceClassification from calculito
+author: John Snow Labs
+name: classify_isin_step3
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classify_isin_step3` is a English model originally trained by calculito.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classify_isin_step3_en_5.5.0_3.0_1725488132003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classify_isin_step3_en_5.5.0_3.0_1725488132003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("classify_isin_step3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("classify_isin_step3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classify_isin_step3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|45.5 MB|
+
+## References
+
+https://huggingface.co/calculito/classify-ISIN-STEP3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-classify_isin_step3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-classify_isin_step3_pipeline_en.md
new file mode 100644
index 00000000000000..184bc449a6f601
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-classify_isin_step3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English classify_isin_step3_pipeline pipeline AlbertForSequenceClassification from calculito
+author: John Snow Labs
+name: classify_isin_step3_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classify_isin_step3_pipeline` is a English model originally trained by calculito.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classify_isin_step3_pipeline_en_5.5.0_3.0_1725488134429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classify_isin_step3_pipeline_en_5.5.0_3.0_1725488134429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("classify_isin_step3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("classify_isin_step3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classify_isin_step3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|45.5 MB|
+
+## References
+
+https://huggingface.co/calculito/classify-ISIN-STEP3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline_en.md
new file mode 100644
index 00000000000000..cfcf3b16444df4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline pipeline DistilBertForTokenClassification from judithrosell
+author: John Snow Labs
+name: clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline` is a English model originally trained by judithrosell.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline_en_5.5.0_3.0_1725476435999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline_en_5.5.0_3.0_1725476435999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_bionlp13cg_ner_nepal_bhasa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.5 MB|
+
+## References
+
+https://huggingface.co/judithrosell/ClinicalBERT_BioNLP13CG_NER_new
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_14_model_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_14_model_en.md
new file mode 100644
index 00000000000000..b01928961c526b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_14_model_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_14_model CLIPForZeroShotClassification from shaunster
+author: John Snow Labs
+name: clip_14_model
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_14_model` is a English model originally trained by shaunster.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_14_model_en_5.5.0_3.0_1725456728883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_14_model_en_5.5.0_3.0_1725456728883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_14_model","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_14_model","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_14_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|567.9 MB|
+
+## References
+
+https://huggingface.co/shaunster/clip_14_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_14_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_14_model_pipeline_en.md
new file mode 100644
index 00000000000000..f813529f492113
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_14_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_14_model_pipeline pipeline CLIPForZeroShotClassification from shaunster
+author: John Snow Labs
+name: clip_14_model_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_14_model_pipeline` is a English model originally trained by shaunster.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_14_model_pipeline_en_5.5.0_3.0_1725456756949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_14_model_pipeline_en_5.5.0_3.0_1725456756949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_14_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_14_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_14_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|567.9 MB|
+
+## References
+
+https://huggingface.co/shaunster/clip_14_model
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_base_10240_checkpoint210_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_base_10240_checkpoint210_en.md
new file mode 100644
index 00000000000000..e8574ff28cf897
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_base_10240_checkpoint210_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_base_10240_checkpoint210 CLIPForZeroShotClassification from gowitheflowlab
+author: John Snow Labs
+name: clip_base_10240_checkpoint210
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_10240_checkpoint210` is a English model originally trained by gowitheflowlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_10240_checkpoint210_en_5.5.0_3.0_1725491290269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_10240_checkpoint210_en_5.5.0_3.0_1725491290269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_10240_checkpoint210","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_10240_checkpoint210","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_base_10240_checkpoint210|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|509.7 MB|
+
+## References
+
+https://huggingface.co/gowitheflowlab/clip-base-10240-checkpoint210
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_base_10240_checkpoint210_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_base_10240_checkpoint210_pipeline_en.md
new file mode 100644
index 00000000000000..dcd6183d8b0081
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_base_10240_checkpoint210_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_base_10240_checkpoint210_pipeline pipeline CLIPForZeroShotClassification from gowitheflowlab
+author: John Snow Labs
+name: clip_base_10240_checkpoint210_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_10240_checkpoint210_pipeline` is a English model originally trained by gowitheflowlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_10240_checkpoint210_pipeline_en_5.5.0_3.0_1725491336225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_10240_checkpoint210_pipeline_en_5.5.0_3.0_1725491336225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_base_10240_checkpoint210_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_base_10240_checkpoint210_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_base_10240_checkpoint210_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.8 MB|
+
+## References
+
+https://huggingface.co/gowitheflowlab/clip-base-10240-checkpoint210
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_base_patch16_supervised_mulitilingual_1200_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_base_patch16_supervised_mulitilingual_1200_en.md
new file mode 100644
index 00000000000000..d10eaf900c1989
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_base_patch16_supervised_mulitilingual_1200_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_base_patch16_supervised_mulitilingual_1200 CLIPForZeroShotClassification from gowitheflowlab
+author: John Snow Labs
+name: clip_base_patch16_supervised_mulitilingual_1200
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_1200` is a English model originally trained by gowitheflowlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_1200_en_5.5.0_3.0_1725456901384.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_1200_en_5.5.0_3.0_1725456901384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_1200","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_base_patch16_supervised_mulitilingual_1200","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_base_patch16_supervised_mulitilingual_1200|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|509.7 MB|
+
+## References
+
+https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-1200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_base_patch16_supervised_mulitilingual_1200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_base_patch16_supervised_mulitilingual_1200_pipeline_en.md
new file mode 100644
index 00000000000000..1962e8da53c45b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_base_patch16_supervised_mulitilingual_1200_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_base_patch16_supervised_mulitilingual_1200_pipeline pipeline CLIPForZeroShotClassification from gowitheflowlab
+author: John Snow Labs
+name: clip_base_patch16_supervised_mulitilingual_1200_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_base_patch16_supervised_mulitilingual_1200_pipeline` is a English model originally trained by gowitheflowlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_1200_pipeline_en_5.5.0_3.0_1725456949239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_base_patch16_supervised_mulitilingual_1200_pipeline_en_5.5.0_3.0_1725456949239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_1200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_base_patch16_supervised_mulitilingual_1200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_base_patch16_supervised_mulitilingual_1200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.7 MB|
+
+## References
+
+https://huggingface.co/gowitheflowlab/clip-base-patch16-supervised-mulitilingual-1200
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_clip_finetuned_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_clip_finetuned_v2_en.md
new file mode 100644
index 00000000000000..702f6b68854966
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_clip_finetuned_v2_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_clip_finetuned_v2 CLIPForZeroShotClassification from kpalczewski-displate
+author: John Snow Labs
+name: clip_clip_finetuned_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_clip_finetuned_v2` is a English model originally trained by kpalczewski-displate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_clip_finetuned_v2_en_5.5.0_3.0_1725490680168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_clip_finetuned_v2_en_5.5.0_3.0_1725490680168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_clip_finetuned_v2","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_clip_finetuned_v2","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_clip_finetuned_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|567.3 MB|
+
+## References
+
+https://huggingface.co/kpalczewski-displate/clip-clip-finetuned-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_clip_finetuned_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_clip_finetuned_v2_pipeline_en.md
new file mode 100644
index 00000000000000..339f788de7120e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_clip_finetuned_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_clip_finetuned_v2_pipeline pipeline CLIPForZeroShotClassification from kpalczewski-displate
+author: John Snow Labs
+name: clip_clip_finetuned_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_clip_finetuned_v2_pipeline` is a English model originally trained by kpalczewski-displate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_clip_finetuned_v2_pipeline_en_5.5.0_3.0_1725490708795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_clip_finetuned_v2_pipeline_en_5.5.0_3.0_1725490708795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_clip_finetuned_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_clip_finetuned_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_clip_finetuned_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|567.3 MB|
+
+## References
+
+https://huggingface.co/kpalczewski-displate/clip-clip-finetuned-v2
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_demo_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_demo_en.md
new file mode 100644
index 00000000000000..3765bd225f3120
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_demo_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_demo CLIPForZeroShotClassification from zabir735
+author: John Snow Labs
+name: clip_demo
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_demo` is a English model originally trained by zabir735.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_demo_en_5.5.0_3.0_1725455218865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_demo_en_5.5.0_3.0_1725455218865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_demo","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_demo","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_demo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|561.2 MB|
+
+## References
+
+https://huggingface.co/zabir735/clip-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_en.md
new file mode 100644
index 00000000000000..567b99c56c9c21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai CLIPForZeroShotClassification from Solenya-ai
+author: John Snow Labs
+name: clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai` is a English model originally trained by Solenya-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_en_5.5.0_3.0_1725455218803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_en_5.5.0_3.0_1725455218803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|561.8 MB|
+
+## References
+
+https://huggingface.co/Solenya-ai/CLIP-ViT-B-16-DataComp.XL-s13B-b90K
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline_en.md
new file mode 100644
index 00000000000000..a3fd103ce75c9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline pipeline CLIPForZeroShotClassification from Solenya-ai
+author: John Snow Labs
+name: clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline` is a English model originally trained by Solenya-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline_en_5.5.0_3.0_1725455248728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline_en_5.5.0_3.0_1725455248728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_b_16_datacomp_xl_s13b_b90k_solenya_ai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|561.8 MB|
+
+## References
+
+https://huggingface.co/Solenya-ai/CLIP-ViT-B-16-DataComp.XL-s13B-b90K
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch322_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch322_pipeline_en.md
new file mode 100644
index 00000000000000..63a136be72c3f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch322_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_base_patch322_pipeline pipeline CLIPForZeroShotClassification from sergioprada
+author: John Snow Labs
+name: clip_vit_base_patch322_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch322_pipeline` is a English model originally trained by sergioprada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch322_pipeline_en_5.5.0_3.0_1725456511652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch322_pipeline_en_5.5.0_3.0_1725456511652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_base_patch322_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_base_patch322_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch322_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/sergioprada/clip-vit-base-patch322
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_img_text_relevancy_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_img_text_relevancy_en.md
new file mode 100644
index 00000000000000..8e49d6e1d6ae02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_img_text_relevancy_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_base_patch32_img_text_relevancy CLIPForZeroShotClassification from jancuhel
+author: John Snow Labs
+name: clip_vit_base_patch32_img_text_relevancy
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_img_text_relevancy` is a English model originally trained by jancuhel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_img_text_relevancy_en_5.5.0_3.0_1725456490421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_img_text_relevancy_en_5.5.0_3.0_1725456490421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_img_text_relevancy","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_img_text_relevancy","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_img_text_relevancy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/jancuhel/clip-vit-base-patch32-img-text-relevancy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_img_text_relevancy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_img_text_relevancy_pipeline_en.md
new file mode 100644
index 00000000000000..4eb9e2ec69370d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_img_text_relevancy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_base_patch32_img_text_relevancy_pipeline pipeline CLIPForZeroShotClassification from jancuhel
+author: John Snow Labs
+name: clip_vit_base_patch32_img_text_relevancy_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_img_text_relevancy_pipeline` is a English model originally trained by jancuhel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_img_text_relevancy_pipeline_en_5.5.0_3.0_1725456583607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_img_text_relevancy_pipeline_en_5.5.0_3.0_1725456583607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_base_patch32_img_text_relevancy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_base_patch32_img_text_relevancy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_img_text_relevancy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/jancuhel/clip-vit-base-patch32-img-text-relevancy
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_ericlewis_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_ericlewis_en.md
new file mode 100644
index 00000000000000..79348e4d72b88e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_ericlewis_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_l_14_laion2b_s32b_b82k_ericlewis CLIPForZeroShotClassification from ericlewis
+author: John Snow Labs
+name: clip_vit_l_14_laion2b_s32b_b82k_ericlewis
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_l_14_laion2b_s32b_b82k_ericlewis` is a English model originally trained by ericlewis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_laion2b_s32b_b82k_ericlewis_en_5.5.0_3.0_1725456193412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_laion2b_s32b_b82k_ericlewis_en_5.5.0_3.0_1725456193412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_l_14_laion2b_s32b_b82k_ericlewis","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_l_14_laion2b_s32b_b82k_ericlewis","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_l_14_laion2b_s32b_b82k_ericlewis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/ericlewis/CLIP-ViT-L-14-laion2B-s32B-b82K
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline_en.md
new file mode 100644
index 00000000000000..23fcdddf02ac85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline pipeline CLIPForZeroShotClassification from ericlewis
+author: John Snow Labs
+name: clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline` is a English model originally trained by ericlewis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline_en_5.5.0_3.0_1725456273419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline_en_5.5.0_3.0_1725456273419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_l_14_laion2b_s32b_b82k_ericlewis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/ericlewis/CLIP-ViT-L-14-laion2B-s32B-b82K
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline_en.md
new file mode 100644
index 00000000000000..dadfba970e3f67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline pipeline CLIPForZeroShotClassification from laion
+author: John Snow Labs
+name: clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline` is a English model originally trained by laion.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline_en_5.5.0_3.0_1725456280363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline_en_5.5.0_3.0_1725456280363.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_l_14_laion2b_s32b_b82k_laion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/laion/CLIP-ViT-L-14-laion2B-s32B-b82K
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_336_q_mm_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_336_q_mm_en.md
new file mode 100644
index 00000000000000..879f9dc846f2f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_336_q_mm_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_large_patch14_336_q_mm CLIPForZeroShotClassification from Q-MM
+author: John Snow Labs
+name: clip_vit_large_patch14_336_q_mm
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_336_q_mm` is a English model originally trained by Q-MM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_336_q_mm_en_5.5.0_3.0_1725491370813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_336_q_mm_en_5.5.0_3.0_1725491370813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_336_q_mm","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_336_q_mm","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_large_patch14_336_q_mm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Q-MM/clip-vit-large-patch14-336
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_finetuned_dresser_sofas_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_finetuned_dresser_sofas_en.md
new file mode 100644
index 00000000000000..2f144488081592
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_finetuned_dresser_sofas_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_large_patch14_finetuned_dresser_sofas CLIPForZeroShotClassification from vinluvie
+author: John Snow Labs
+name: clip_vit_large_patch14_finetuned_dresser_sofas
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_finetuned_dresser_sofas` is a English model originally trained by vinluvie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_finetuned_dresser_sofas_en_5.5.0_3.0_1725491619078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_finetuned_dresser_sofas_en_5.5.0_3.0_1725491619078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_finetuned_dresser_sofas","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_finetuned_dresser_sofas","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_large_patch14_finetuned_dresser_sofas|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/vinluvie/clip-vit-large-patch14-finetuned-dresser-sofas
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_korean_ko.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_korean_ko.md
new file mode 100644
index 00000000000000..f8eee90270ed39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_korean_ko.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: Korean clip_vit_large_patch14_korean CLIPForZeroShotClassification from Bingsu
+author: John Snow Labs
+name: clip_vit_large_patch14_korean
+date: 2024-09-04
+tags: [ko, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_korean` is a Korean model originally trained by Bingsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_korean_ko_5.5.0_3.0_1725491986540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_korean_ko_5.5.0_3.0_1725491986540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_korean","ko") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_large_patch14_korean","ko") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_large_patch14_korean|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|ko|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Bingsu/clip-vit-large-patch14-ko
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_korean_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_korean_pipeline_ko.md
new file mode 100644
index 00000000000000..616cba1711fb32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_large_patch14_korean_pipeline_ko.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Korean clip_vit_large_patch14_korean_pipeline pipeline CLIPForZeroShotClassification from Bingsu
+author: John Snow Labs
+name: clip_vit_large_patch14_korean_pipeline
+date: 2024-09-04
+tags: [ko, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_large_patch14_korean_pipeline` is a Korean model originally trained by Bingsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_korean_pipeline_ko_5.5.0_3.0_1725492221124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_large_patch14_korean_pipeline_ko_5.5.0_3.0_1725492221124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_large_patch14_korean_pipeline", lang = "ko")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_large_patch14_korean_pipeline", lang = "ko")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_large_patch14_korean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ko|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Bingsu/clip-vit-large-patch14-ko
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-codebert_python_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-codebert_python_pipeline_en.md
new file mode 100644
index 00000000000000..09135c559a09ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-codebert_python_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English codebert_python_pipeline pipeline RoBertaEmbeddings from neulab
+author: John Snow Labs
+name: codebert_python_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codebert_python_pipeline` is a English model originally trained by neulab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codebert_python_pipeline_en_5.5.0_3.0_1725412772738.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codebert_python_pipeline_en_5.5.0_3.0_1725412772738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("codebert_python_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("codebert_python_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|codebert_python_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/neulab/codebert-python
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cola_deberta_v3_large_en.md b/docs/_posts/ahmedlone127/2024-09-04-cola_deberta_v3_large_en.md
new file mode 100644
index 00000000000000..012e6ec5790b5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cola_deberta_v3_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cola_deberta_v3_large DeBertaForSequenceClassification from Hieu-Hien
+author: John Snow Labs
+name: cola_deberta_v3_large
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cola_deberta_v3_large` is a English model originally trained by Hieu-Hien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cola_deberta_v3_large_en_5.5.0_3.0_1725468951726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cola_deberta_v3_large_en_5.5.0_3.0_1725468951726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cola_deberta_v3_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cola_deberta_v3_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cola_deberta_v3_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Hieu-Hien/cola-deberta-v3-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cola_deberta_v3_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-cola_deberta_v3_large_pipeline_en.md
new file mode 100644
index 00000000000000..8a29a8dc41b0a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cola_deberta_v3_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cola_deberta_v3_large_pipeline pipeline DeBertaForSequenceClassification from Hieu-Hien
+author: John Snow Labs
+name: cola_deberta_v3_large_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cola_deberta_v3_large_pipeline` is a English model originally trained by Hieu-Hien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cola_deberta_v3_large_pipeline_en_5.5.0_3.0_1725469093566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cola_deberta_v3_large_pipeline_en_5.5.0_3.0_1725469093566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cola_deberta_v3_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cola_deberta_v3_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cola_deberta_v3_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Hieu-Hien/cola-deberta-v3-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cold_fusion_itr13_seed2_en.md b/docs/_posts/ahmedlone127/2024-09-04-cold_fusion_itr13_seed2_en.md
new file mode 100644
index 00000000000000..f08e6fd6425fd8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cold_fusion_itr13_seed2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cold_fusion_itr13_seed2 RoBertaForSequenceClassification from ibm
+author: John Snow Labs
+name: cold_fusion_itr13_seed2
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_itr13_seed2` is a English model originally trained by ibm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_itr13_seed2_en_5.5.0_3.0_1725485114684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_itr13_seed2_en_5.5.0_3.0_1725485114684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("cold_fusion_itr13_seed2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("cold_fusion_itr13_seed2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cold_fusion_itr13_seed2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/ibm/ColD-Fusion-itr13-seed2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-comfact_deberta_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-comfact_deberta_v2_en.md
new file mode 100644
index 00000000000000..5bda4f175c8ef3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-comfact_deberta_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English comfact_deberta_v2 DeBertaForSequenceClassification from mismayil
+author: John Snow Labs
+name: comfact_deberta_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comfact_deberta_v2` is a English model originally trained by mismayil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comfact_deberta_v2_en_5.5.0_3.0_1725439690734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comfact_deberta_v2_en_5.5.0_3.0_1725439690734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("comfact_deberta_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("comfact_deberta_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|comfact_deberta_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/mismayil/comfact-deberta-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-consenbert_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-consenbert_v1_en.md
new file mode 100644
index 00000000000000..dcce92136ee044
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-consenbert_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English consenbert_v1 RoBertaForSequenceClassification from SoloAlphus
+author: John Snow Labs
+name: consenbert_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`consenbert_v1` is a English model originally trained by SoloAlphus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/consenbert_v1_en_5.5.0_3.0_1725453098504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/consenbert_v1_en_5.5.0_3.0_1725453098504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("consenbert_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("consenbert_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|consenbert_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|421.0 MB|
+
+## References
+
+https://huggingface.co/SoloAlphus/ConSenBert-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-consenbert_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-consenbert_v1_pipeline_en.md
new file mode 100644
index 00000000000000..7f9941113fbac3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-consenbert_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English consenbert_v1_pipeline pipeline RoBertaForSequenceClassification from SoloAlphus
+author: John Snow Labs
+name: consenbert_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`consenbert_v1_pipeline` is a English model originally trained by SoloAlphus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/consenbert_v1_pipeline_en_5.5.0_3.0_1725453139019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/consenbert_v1_pipeline_en_5.5.0_3.0_1725453139019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("consenbert_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("consenbert_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|consenbert_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|421.0 MB|
+
+## References
+
+https://huggingface.co/SoloAlphus/ConSenBert-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-convention_collective_cross_encoder_en.md b/docs/_posts/ahmedlone127/2024-09-04-convention_collective_cross_encoder_en.md
new file mode 100644
index 00000000000000..46a4955af70fc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-convention_collective_cross_encoder_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English convention_collective_cross_encoder CamemBertForSequenceClassification from Bylaw
+author: John Snow Labs
+name: convention_collective_cross_encoder
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convention_collective_cross_encoder` is a English model originally trained by Bylaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convention_collective_cross_encoder_en_5.5.0_3.0_1725466723567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convention_collective_cross_encoder_en_5.5.0_3.0_1725466723567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("convention_collective_cross_encoder","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("convention_collective_cross_encoder", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convention_collective_cross_encoder|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Bylaw/convention-collective-cross-encoder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-convention_collective_cross_encoder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-convention_collective_cross_encoder_pipeline_en.md
new file mode 100644
index 00000000000000..7c60a084b8338b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-convention_collective_cross_encoder_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English convention_collective_cross_encoder_pipeline pipeline CamemBertForSequenceClassification from Bylaw
+author: John Snow Labs
+name: convention_collective_cross_encoder_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convention_collective_cross_encoder_pipeline` is a English model originally trained by Bylaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convention_collective_cross_encoder_pipeline_en_5.5.0_3.0_1725466786257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convention_collective_cross_encoder_pipeline_en_5.5.0_3.0_1725466786257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("convention_collective_cross_encoder_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("convention_collective_cross_encoder_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convention_collective_cross_encoder_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Bylaw/convention-collective-cross-encoder
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cpegen_vv_en.md b/docs/_posts/ahmedlone127/2024-09-04-cpegen_vv_en.md
new file mode 100644
index 00000000000000..3d281b5380e766
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cpegen_vv_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cpegen_vv DistilBertForTokenClassification from Neurona
+author: John Snow Labs
+name: cpegen_vv
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpegen_vv` is a English model originally trained by Neurona.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cpegen_vv_en_5.5.0_3.0_1725449049572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpegen_vv_en_5.5.0_3.0_1725449049572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("cpegen_vv","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("cpegen_vv", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cpegen_vv|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Neurona/cpegen_vv
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cree_fewshot_en.md b/docs/_posts/ahmedlone127/2024-09-04-cree_fewshot_en.md
new file mode 100644
index 00000000000000..83610e32f03c08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cree_fewshot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cree_fewshot MPNetEmbeddings from pig4431
+author: John Snow Labs
+name: cree_fewshot
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cree_fewshot` is a English model originally trained by pig4431.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cree_fewshot_en_5.5.0_3.0_1725470789418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cree_fewshot_en_5.5.0_3.0_1725470789418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("cree_fewshot","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("cree_fewshot","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cree_fewshot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/pig4431/CR_fewshot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cross_encoder_stsb_deberta_v3_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-cross_encoder_stsb_deberta_v3_large_pipeline_en.md
new file mode 100644
index 00000000000000..6ade687a2fb0c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cross_encoder_stsb_deberta_v3_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cross_encoder_stsb_deberta_v3_large_pipeline pipeline DeBertaForSequenceClassification from yunyu
+author: John Snow Labs
+name: cross_encoder_stsb_deberta_v3_large_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_encoder_stsb_deberta_v3_large_pipeline` is a English model originally trained by yunyu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_encoder_stsb_deberta_v3_large_pipeline_en_5.5.0_3.0_1725440443742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_encoder_stsb_deberta_v3_large_pipeline_en_5.5.0_3.0_1725440443742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cross_encoder_stsb_deberta_v3_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cross_encoder_stsb_deberta_v3_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_encoder_stsb_deberta_v3_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/yunyu/cross-encoder-stsb-deberta-v3-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-crossencoder_distilcamembert_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2024-09-04-crossencoder_distilcamembert_mmarcofr_fr.md
new file mode 100644
index 00000000000000..ef9a994b29856e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-crossencoder_distilcamembert_mmarcofr_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French crossencoder_distilcamembert_mmarcofr CamemBertForSequenceClassification from antoinelouis
+author: John Snow Labs
+name: crossencoder_distilcamembert_mmarcofr
+date: 2024-09-04
+tags: [fr, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_distilcamembert_mmarcofr` is a French model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_distilcamembert_mmarcofr_fr_5.5.0_3.0_1725480833457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_distilcamembert_mmarcofr_fr_5.5.0_3.0_1725480833457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("crossencoder_distilcamembert_mmarcofr","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("crossencoder_distilcamembert_mmarcofr", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crossencoder_distilcamembert_mmarcofr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|255.7 MB|
+
+## References
+
+https://huggingface.co/antoinelouis/crossencoder-distilcamembert-mmarcoFR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-crossencoder_distilcamembert_mmarcofr_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-04-crossencoder_distilcamembert_mmarcofr_pipeline_fr.md
new file mode 100644
index 00000000000000..d12eca62462e07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-crossencoder_distilcamembert_mmarcofr_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French crossencoder_distilcamembert_mmarcofr_pipeline pipeline CamemBertForSequenceClassification from antoinelouis
+author: John Snow Labs
+name: crossencoder_distilcamembert_mmarcofr_pipeline
+date: 2024-09-04
+tags: [fr, open_source, pipeline, onnx]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_distilcamembert_mmarcofr_pipeline` is a French model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_distilcamembert_mmarcofr_pipeline_fr_5.5.0_3.0_1725480845510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_distilcamembert_mmarcofr_pipeline_fr_5.5.0_3.0_1725480845510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("crossencoder_distilcamembert_mmarcofr_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("crossencoder_distilcamembert_mmarcofr_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crossencoder_distilcamembert_mmarcofr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|255.8 MB|
+
+## References
+
+https://huggingface.co/antoinelouis/crossencoder-distilcamembert-mmarcoFR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cs4248_roberta_wolof_search_mix_epoch_3_en.md b/docs/_posts/ahmedlone127/2024-09-04-cs4248_roberta_wolof_search_mix_epoch_3_en.md
new file mode 100644
index 00000000000000..c104c8546c7c3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cs4248_roberta_wolof_search_mix_epoch_3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cs4248_roberta_wolof_search_mix_epoch_3 RoBertaForQuestionAnswering from BenjaminLHR
+author: John Snow Labs
+name: cs4248_roberta_wolof_search_mix_epoch_3
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs4248_roberta_wolof_search_mix_epoch_3` is a English model originally trained by BenjaminLHR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs4248_roberta_wolof_search_mix_epoch_3_en_5.5.0_3.0_1725484244859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs4248_roberta_wolof_search_mix_epoch_3_en_5.5.0_3.0_1725484244859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("cs4248_roberta_wolof_search_mix_epoch_3","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("cs4248_roberta_wolof_search_mix_epoch_3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs4248_roberta_wolof_search_mix_epoch_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/BenjaminLHR/cs4248-roberta-wo-search-mix-epoch-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ct_cos_xlmr_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-04-ct_cos_xlmr_squadv2_en.md
new file mode 100644
index 00000000000000..2df7828e9becbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ct_cos_xlmr_squadv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ct_cos_xlmr_squadv2 XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_cos_xlmr_squadv2
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_xlmr_squadv2` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_squadv2_en_5.5.0_3.0_1725481613598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_squadv2_en_5.5.0_3.0_1725481613598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_cos_xlmr_squadv2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_cos_xlmr_squadv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_cos_xlmr_squadv2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|876.0 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-cos-xlmr-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ct_cos_xlmr_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ct_cos_xlmr_squadv2_pipeline_en.md
new file mode 100644
index 00000000000000..493311f3efe1f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ct_cos_xlmr_squadv2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ct_cos_xlmr_squadv2_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_cos_xlmr_squadv2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_xlmr_squadv2_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_squadv2_pipeline_en_5.5.0_3.0_1725481680127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_squadv2_pipeline_en_5.5.0_3.0_1725481680127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ct_cos_xlmr_squadv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ct_cos_xlmr_squadv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_cos_xlmr_squadv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|876.0 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-cos-xlmr-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ct_mse_xlmr_20230920_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ct_mse_xlmr_20230920_1_pipeline_en.md
new file mode 100644
index 00000000000000..5f20905ae399cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ct_mse_xlmr_20230920_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ct_mse_xlmr_20230920_1_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_mse_xlmr_20230920_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_xlmr_20230920_1_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_20230920_1_pipeline_en_5.5.0_3.0_1725482796344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_20230920_1_pipeline_en_5.5.0_3.0_1725482796344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ct_mse_xlmr_20230920_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ct_mse_xlmr_20230920_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_mse_xlmr_20230920_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|876.0 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-mse-xlmr-20230920-1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dagpap24_deberta_base_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dagpap24_deberta_base_ft_pipeline_en.md
new file mode 100644
index 00000000000000..3ba971c8e079c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dagpap24_deberta_base_ft_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dagpap24_deberta_base_ft_pipeline pipeline DeBertaForTokenClassification from swimmingcrab
+author: John Snow Labs
+name: dagpap24_deberta_base_ft_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dagpap24_deberta_base_ft_pipeline` is a English model originally trained by swimmingcrab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dagpap24_deberta_base_ft_pipeline_en_5.5.0_3.0_1725471727027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dagpap24_deberta_base_ft_pipeline_en_5.5.0_3.0_1725471727027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dagpap24_deberta_base_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dagpap24_deberta_base_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dagpap24_deberta_base_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|660.5 MB|
+
+## References
+
+https://huggingface.co/swimmingcrab/DAGPap24-deberta-base-ft
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dataset_model_en.md b/docs/_posts/ahmedlone127/2024-09-04-dataset_model_en.md
new file mode 100644
index 00000000000000..4d5a8d0414438b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dataset_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dataset_model DistilBertForTokenClassification from KHEYH
+author: John Snow Labs
+name: dataset_model
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dataset_model` is a English model originally trained by KHEYH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dataset_model_en_5.5.0_3.0_1725476529437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dataset_model_en_5.5.0_3.0_1725476529437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("dataset_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("dataset_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dataset_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/KHEYH/dataset_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-datasnipper_finerdistilbert_fullsequence_en.md b/docs/_posts/ahmedlone127/2024-09-04-datasnipper_finerdistilbert_fullsequence_en.md
new file mode 100644
index 00000000000000..ecae1c44687204
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-datasnipper_finerdistilbert_fullsequence_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English datasnipper_finerdistilbert_fullsequence DistilBertForTokenClassification from gvisser
+author: John Snow Labs
+name: datasnipper_finerdistilbert_fullsequence
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`datasnipper_finerdistilbert_fullsequence` is a English model originally trained by gvisser.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/datasnipper_finerdistilbert_fullsequence_en_5.5.0_3.0_1725476279663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/datasnipper_finerdistilbert_fullsequence_en_5.5.0_3.0_1725476279663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("datasnipper_finerdistilbert_fullsequence","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("datasnipper_finerdistilbert_fullsequence", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|datasnipper_finerdistilbert_fullsequence|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|248.0 MB|
+
+## References
+
+https://huggingface.co/gvisser/DataSnipper_FinerDistilBert_FullSequence
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dbbuc_5p_en.md b/docs/_posts/ahmedlone127/2024-09-04-dbbuc_5p_en.md
new file mode 100644
index 00000000000000..b54b8896b07d6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dbbuc_5p_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dbbuc_5p DistilBertForTokenClassification from cria111
+author: John Snow Labs
+name: dbbuc_5p
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbbuc_5p` is a English model originally trained by cria111.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbbuc_5p_en_5.5.0_3.0_1725476023721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbbuc_5p_en_5.5.0_3.0_1725476023721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("dbbuc_5p","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("dbbuc_5p", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbbuc_5p|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cria111/dbbuc_5p
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dbbuc_5p_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dbbuc_5p_pipeline_en.md
new file mode 100644
index 00000000000000..261ef707a39773
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dbbuc_5p_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dbbuc_5p_pipeline pipeline DistilBertForTokenClassification from cria111
+author: John Snow Labs
+name: dbbuc_5p_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbbuc_5p_pipeline` is a English model originally trained by cria111.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbbuc_5p_pipeline_en_5.5.0_3.0_1725476036250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbbuc_5p_pipeline_en_5.5.0_3.0_1725476036250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dbbuc_5p_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dbbuc_5p_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbbuc_5p_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cria111/dbbuc_5p
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dbert_pii_detection_model_omshikhare_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dbert_pii_detection_model_omshikhare_pipeline_en.md
new file mode 100644
index 00000000000000..05d7ccedde534d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dbert_pii_detection_model_omshikhare_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dbert_pii_detection_model_omshikhare_pipeline pipeline DistilBertForTokenClassification from omshikhare
+author: John Snow Labs
+name: dbert_pii_detection_model_omshikhare_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbert_pii_detection_model_omshikhare_pipeline` is a English model originally trained by omshikhare.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbert_pii_detection_model_omshikhare_pipeline_en_5.5.0_3.0_1725460403247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbert_pii_detection_model_omshikhare_pipeline_en_5.5.0_3.0_1725460403247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dbert_pii_detection_model_omshikhare_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dbert_pii_detection_model_omshikhare_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbert_pii_detection_model_omshikhare_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/omshikhare/dbert_pii_detection_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta3base_1024_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta3base_1024_en.md
new file mode 100644
index 00000000000000..bd123cdbcd5e51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta3base_1024_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta3base_1024 DeBertaForTokenClassification from kabir5297
+author: John Snow Labs
+name: deberta3base_1024
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta3base_1024` is a English model originally trained by kabir5297.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta3base_1024_en_5.5.0_3.0_1725475068532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta3base_1024_en_5.5.0_3.0_1725475068532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta3base_1024","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta3base_1024", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta3base_1024|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|581.9 MB|
+
+## References
+
+https://huggingface.co/kabir5297/deberta3base_1024
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta3base_1024_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta3base_1024_pipeline_en.md
new file mode 100644
index 00000000000000..ad1cc477ea70c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta3base_1024_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta3base_1024_pipeline pipeline DeBertaForTokenClassification from kabir5297
+author: John Snow Labs
+name: deberta3base_1024_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta3base_1024_pipeline` is a English model originally trained by kabir5297.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta3base_1024_pipeline_en_5.5.0_3.0_1725475130421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta3base_1024_pipeline_en_5.5.0_3.0_1725475130421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta3base_1024_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta3base_1024_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta3base_1024_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|582.0 MB|
+
+## References
+
+https://huggingface.co/kabir5297/deberta3base_1024
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_amazon_reviews_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_amazon_reviews_v2_en.md
new file mode 100644
index 00000000000000..af3ea90d33e537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_amazon_reviews_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_amazon_reviews_v2 DeBertaForSequenceClassification from masapasa
+author: John Snow Labs
+name: deberta_amazon_reviews_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_amazon_reviews_v2` is a English model originally trained by masapasa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v2_en_5.5.0_3.0_1725461745346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v2_en_5.5.0_3.0_1725461745346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_amazon_reviews_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_amazon_reviews_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_amazon_reviews_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|555.6 MB|
+
+## References
+
+https://huggingface.co/masapasa/deberta_amazon_reviews_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_amazon_reviews_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_amazon_reviews_v2_pipeline_en.md
new file mode 100644
index 00000000000000..c7dd7a891ca9f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_amazon_reviews_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_amazon_reviews_v2_pipeline pipeline DeBertaForSequenceClassification from masapasa
+author: John Snow Labs
+name: deberta_amazon_reviews_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_amazon_reviews_v2_pipeline` is a English model originally trained by masapasa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v2_pipeline_en_5.5.0_3.0_1725461829166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v2_pipeline_en_5.5.0_3.0_1725461829166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_amazon_reviews_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_amazon_reviews_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_amazon_reviews_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|555.6 MB|
+
+## References
+
+https://huggingface.co/masapasa/deberta_amazon_reviews_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_base_german_fluency_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_base_german_fluency_pipeline_en.md
new file mode 100644
index 00000000000000..507181161e8cd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_base_german_fluency_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_base_german_fluency_pipeline pipeline DeBertaForSequenceClassification from EIStakovskii
+author: John Snow Labs
+name: deberta_base_german_fluency_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base_german_fluency_pipeline` is a English model originally trained by EIStakovskii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_base_german_fluency_pipeline_en_5.5.0_3.0_1725439177572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_german_fluency_pipeline_en_5.5.0_3.0_1725439177572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_base_german_fluency_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_base_german_fluency_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_base_german_fluency_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|605.0 MB|
+
+## References
+
+https://huggingface.co/EIStakovskii/deberta-base-german_fluency
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_base_metaphor_detection_english_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_base_metaphor_detection_english_en.md
new file mode 100644
index 00000000000000..111329e1471d0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_base_metaphor_detection_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_base_metaphor_detection_english DeBertaForTokenClassification from HiTZ
+author: John Snow Labs
+name: deberta_base_metaphor_detection_english
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base_metaphor_detection_english` is a English model originally trained by HiTZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_base_metaphor_detection_english_en_5.5.0_3.0_1725475472046.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_metaphor_detection_english_en_5.5.0_3.0_1725475472046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_base_metaphor_detection_english","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_base_metaphor_detection_english", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_base_metaphor_detection_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|596.9 MB|
+
+## References
+
+https://huggingface.co/HiTZ/deberta-base-metaphor-detection-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_classifier_feedback_1024_pseudo_final_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_classifier_feedback_1024_pseudo_final_en.md
new file mode 100644
index 00000000000000..5ebe50445b1069
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_classifier_feedback_1024_pseudo_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_classifier_feedback_1024_pseudo_final DeBertaForTokenClassification from TTian
+author: John Snow Labs
+name: deberta_classifier_feedback_1024_pseudo_final
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_classifier_feedback_1024_pseudo_final` is a English model originally trained by TTian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_classifier_feedback_1024_pseudo_final_en_5.5.0_3.0_1725472663415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_classifier_feedback_1024_pseudo_final_en_5.5.0_3.0_1725472663415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_classifier_feedback_1024_pseudo_final","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_classifier_feedback_1024_pseudo_final", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_classifier_feedback_1024_pseudo_final|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/TTian/deberta-classifier-feedback-1024-pseudo-final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_small_22feb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_small_22feb_pipeline_en.md
new file mode 100644
index 00000000000000..2d34eb82e0b964
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_small_22feb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_small_22feb_pipeline pipeline DeBertaForTokenClassification from codeaze
+author: John Snow Labs
+name: deberta_small_22feb_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_small_22feb_pipeline` is a English model originally trained by codeaze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_small_22feb_pipeline_en_5.5.0_3.0_1725474460099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_small_22feb_pipeline_en_5.5.0_3.0_1725474460099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_small_22feb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_small_22feb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_small_22feb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/codeaze/deberta_small_22feb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_token_classifer_v3_base_food_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_token_classifer_v3_base_food_en.md
new file mode 100644
index 00000000000000..b3bec5c30434e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_token_classifer_v3_base_food_en.md
@@ -0,0 +1,116 @@
+---
+layout: model
+title: English DeBertaForTokenClassification (from davanstrien)
+author: John Snow Labs
+name: deberta_token_classifer_v3_base_food
+date: 2024-09-04
+tags: [token_classification, deberta, openvino, en, open_source]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: openvino
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+“
+DeBertaForTokenClassification can load DeBERTA Models v2 and v3 with a token classification head on top (a linear layer on top of the hidden-states output) e.g. for Named-Entity-Recognition (NER) tasks.
+
+deberta_token_classifer_v3_base_food is a fine-tuned DeBERTa model that is ready to be used for Token Classification task such as Named Entity Recognition and it achieves state-of-the-art performance.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_token_classifer_v3_base_food_en_5.5.0_3.0_1725494292416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_token_classifer_v3_base_food_en_5.5.0_3.0_1725494292416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+document_assembler = DocumentAssembler()\ 
+.setInputCol("text")\
+.setOutputCol("document")
+
+tokenizer = Tokenizer()\
+.setInputCols(['document'])\
+.setOutputCol('token') 
+
+tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_token_classifer_v3_base_food", "en")\
+.setInputCols(["document", "token"])\
+.setOutputCol("ner")\
+.setCaseSensitive(True)\ 
+.setMaxSentenceLength(512) 
+
+# since output column is IOB/IOB2 style, NerConverter can extract entities
+ner_converter = NerConverter()\
+.setInputCols(['document', 'token', 'ner'])\
+.setOutputCol('entities') 
+
+pipeline = Pipeline(stages=[
+document_assembler,
+tokenizer,
+tokenClassifier,
+ner_converter
+])
+
+example = spark.createDataFrame([['I really liked that movie!']]).toDF("text")
+result = pipeline.fit(example).transform(example)
+
+
+
+```
+```scala
+
+val document_assembler = new DocumentAssembler()
+.setInputCol("text")
+.setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+.setInputCols("document")
+.setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_token_classifer_v3_base_food", "en")
+.setInputCols("document", "token")
+.setOutputCol("ner")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+// since output column is IOB/IOB2 style, NerConverter can extract entities
+val ner_converter = NerConverter() 
+.setInputCols("document", "token", "ner") 
+.setOutputCol("entities")
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, tokenClassifier, ner_converter))
+
+val example = Seq("I really liked that movie!").toDS.toDF("text")
+
+val result = pipeline.fit(example).transform(example)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_token_classifer_v3_base_food|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[token, document]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|609.7 MB|
+|Case sensitive:|true|
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_tomatoes_sentiment_voodoo72_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_tomatoes_sentiment_voodoo72_pipeline_en.md
new file mode 100644
index 00000000000000..9777a0aeb8ca74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_tomatoes_sentiment_voodoo72_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_tomatoes_sentiment_voodoo72_pipeline pipeline DeBertaForSequenceClassification from voodoo72
+author: John Snow Labs
+name: deberta_tomatoes_sentiment_voodoo72_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_tomatoes_sentiment_voodoo72_pipeline` is a English model originally trained by voodoo72.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_tomatoes_sentiment_voodoo72_pipeline_en_5.5.0_3.0_1725438908190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_tomatoes_sentiment_voodoo72_pipeline_en_5.5.0_3.0_1725438908190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_tomatoes_sentiment_voodoo72_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_tomatoes_sentiment_voodoo72_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_tomatoes_sentiment_voodoo72_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|589.9 MB|
+
+## References
+
+https://huggingface.co/voodoo72/deberta-tomatoes-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_base_japanese_finetuned_emotion_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_base_japanese_finetuned_emotion_en.md
new file mode 100644
index 00000000000000..a95029de65a682
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_base_japanese_finetuned_emotion_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v2_base_japanese_finetuned_emotion DeBertaForSequenceClassification from nasuka
+author: John Snow Labs
+name: deberta_v2_base_japanese_finetuned_emotion
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_base_japanese_finetuned_emotion` is a English model originally trained by nasuka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_emotion_en_5.5.0_3.0_1725439809742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_base_japanese_finetuned_emotion_en_5.5.0_3.0_1725439809742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v2_base_japanese_finetuned_emotion","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v2_base_japanese_finetuned_emotion", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v2_base_japanese_finetuned_emotion|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|421.2 MB|
+
+## References
+
+https://huggingface.co/nasuka/deberta-v2-base-japanese-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_large_conll2003_inca_v1_latin_fe_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_large_conll2003_inca_v1_latin_fe_v1_en.md
new file mode 100644
index 00000000000000..29d87fc3700de7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_large_conll2003_inca_v1_latin_fe_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v2_large_conll2003_inca_v1_latin_fe_v1 DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: deberta_v2_large_conll2003_inca_v1_latin_fe_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_large_conll2003_inca_v1_latin_fe_v1` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v2_large_conll2003_inca_v1_latin_fe_v1_en_5.5.0_3.0_1725475137952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_large_conll2003_inca_v1_latin_fe_v1_en_5.5.0_3.0_1725475137952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v2_large_conll2003_inca_v1_latin_fe_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v2_large_conll2003_inca_v1_latin_fe_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v2_large_conll2003_inca_v1_latin_fe_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/deberta-v2-large-conll2003-inca-v1-la-fe-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_1107_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_1107_en.md
new file mode 100644
index 00000000000000..f1af2a66d58204
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_1107_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_1107 DeBertaForSequenceClassification from xoyeop
+author: John Snow Labs
+name: deberta_v3_base_1107
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_1107` is a English model originally trained by xoyeop.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_1107_en_5.5.0_3.0_1725468369038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_1107_en_5.5.0_3.0_1725468369038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_1107","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_1107", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_1107|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|640.6 MB|
+
+## References
+
+https://huggingface.co/xoyeop/deberta-v3-base-1107
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_ai4privacy_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_ai4privacy_english_pipeline_en.md
new file mode 100644
index 00000000000000..dd659b1fd94655
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_ai4privacy_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_ai4privacy_english_pipeline pipeline DeBertaForTokenClassification from xXiaobuding
+author: John Snow Labs
+name: deberta_v3_base_ai4privacy_english_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_ai4privacy_english_pipeline` is a English model originally trained by xXiaobuding.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_ai4privacy_english_pipeline_en_5.5.0_3.0_1725473482660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_ai4privacy_english_pipeline_en_5.5.0_3.0_1725473482660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_ai4privacy_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_ai4privacy_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_ai4privacy_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|596.2 MB|
+
+## References
+
+https://huggingface.co/xXiaobuding/deberta-v3-base_ai4privacy_en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_amazon_reviews_multi_bf16_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_amazon_reviews_multi_bf16_en.md
new file mode 100644
index 00000000000000..16bf4bbe5eacee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_amazon_reviews_multi_bf16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_amazon_reviews_multi_bf16 DeBertaForSequenceClassification from thainq107
+author: John Snow Labs
+name: deberta_v3_base_amazon_reviews_multi_bf16
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_amazon_reviews_multi_bf16` is a English model originally trained by thainq107.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_amazon_reviews_multi_bf16_en_5.5.0_3.0_1725462536603.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_amazon_reviews_multi_bf16_en_5.5.0_3.0_1725462536603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_amazon_reviews_multi_bf16","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_amazon_reviews_multi_bf16", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_amazon_reviews_multi_bf16|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|621.2 MB|
+
+## References
+
+https://huggingface.co/thainq107/deberta-v3-base-amazon-reviews-multi-bf16
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_cola_cliang1453_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_cola_cliang1453_en.md
new file mode 100644
index 00000000000000..f37b07e18cf9cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_cola_cliang1453_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_cola_cliang1453 DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_cola_cliang1453
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_cola_cliang1453` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_cola_cliang1453_en_5.5.0_3.0_1725438375790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_cola_cliang1453_en_5.5.0_3.0_1725438375790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_cola_cliang1453","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_cola_cliang1453", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_cola_cliang1453|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|561.6 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_cola_cliang1453_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_cola_cliang1453_pipeline_en.md
new file mode 100644
index 00000000000000..855a52362526b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_cola_cliang1453_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_cola_cliang1453_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_cola_cliang1453_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_cola_cliang1453_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_cola_cliang1453_pipeline_en_5.5.0_3.0_1725438457954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_cola_cliang1453_pipeline_en_5.5.0_3.0_1725438457954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_cola_cliang1453_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_cola_cliang1453_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_cola_cliang1453_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|561.6 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_ner_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_ner_en.md
new file mode 100644
index 00000000000000..b04518fb495a64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_conll2003_ner DeBertaForTokenClassification from ficsort
+author: John Snow Labs
+name: deberta_v3_base_conll2003_ner
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_conll2003_ner` is a English model originally trained by ficsort.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_conll2003_ner_en_5.5.0_3.0_1725472847617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_conll2003_ner_en_5.5.0_3.0_1725472847617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_base_conll2003_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_conll2003_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_conll2003_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|591.3 MB|
+
+## References
+
+https://huggingface.co/ficsort/deberta-v3-base-conll2003-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_ner_pipeline_en.md
new file mode 100644
index 00000000000000..0fb583247caced
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_conll2003_ner_pipeline pipeline DeBertaForTokenClassification from ficsort
+author: John Snow Labs
+name: deberta_v3_base_conll2003_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_conll2003_ner_pipeline` is a English model originally trained by ficsort.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_conll2003_ner_pipeline_en_5.5.0_3.0_1725472908926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_conll2003_ner_pipeline_en_5.5.0_3.0_1725472908926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_conll2003_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_conll2003_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_conll2003_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|591.3 MB|
+
+## References
+
+https://huggingface.co/ficsort/deberta-v3-base-conll2003-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_sayula_popoluca_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_sayula_popoluca_en.md
new file mode 100644
index 00000000000000..f882ff2a10837a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_sayula_popoluca_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_conll2003_sayula_popoluca DeBertaForTokenClassification from ficsort
+author: John Snow Labs
+name: deberta_v3_base_conll2003_sayula_popoluca
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_conll2003_sayula_popoluca` is a English model originally trained by ficsort.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_conll2003_sayula_popoluca_en_5.5.0_3.0_1725473526576.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_conll2003_sayula_popoluca_en_5.5.0_3.0_1725473526576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_base_conll2003_sayula_popoluca","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_base_conll2003_sayula_popoluca", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_conll2003_sayula_popoluca|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|591.4 MB|
+
+## References
+
+https://huggingface.co/ficsort/deberta-v3-base-conll2003-pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_sayula_popoluca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_sayula_popoluca_pipeline_en.md
new file mode 100644
index 00000000000000..0e0569fe9ce318
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_conll2003_sayula_popoluca_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_conll2003_sayula_popoluca_pipeline pipeline DeBertaForTokenClassification from ficsort
+author: John Snow Labs
+name: deberta_v3_base_conll2003_sayula_popoluca_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_conll2003_sayula_popoluca_pipeline` is a English model originally trained by ficsort.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_conll2003_sayula_popoluca_pipeline_en_5.5.0_3.0_1725473588645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_conll2003_sayula_popoluca_pipeline_en_5.5.0_3.0_1725473588645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_conll2003_sayula_popoluca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_conll2003_sayula_popoluca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_conll2003_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|591.4 MB|
+
+## References
+
+https://huggingface.co/ficsort/deberta-v3-base-conll2003-pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline_en.md
new file mode 100644
index 00000000000000..fa42c39239acf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline pipeline DeBertaForTokenClassification from C4Scale
+author: John Snow Labs
+name: deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline` is a English model originally trained by C4Scale.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline_en_5.5.0_3.0_1725471594227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline_en_5.5.0_3.0_1725471594227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_bluegennx_run2_19_5e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|609.3 MB|
+
+## References
+
+https://huggingface.co/C4Scale/deberta-v3-base_finetuned_bluegennx_run2.19_5e
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_bluegennx_run2_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_bluegennx_run2_6_pipeline_en.md
new file mode 100644
index 00000000000000..e0a92dca57a0fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_bluegennx_run2_6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_bluegennx_run2_6_pipeline pipeline DeBertaForTokenClassification from C4Scale
+author: John Snow Labs
+name: deberta_v3_base_finetuned_bluegennx_run2_6_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_bluegennx_run2_6_pipeline` is a English model originally trained by C4Scale.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_bluegennx_run2_6_pipeline_en_5.5.0_3.0_1725475392315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_bluegennx_run2_6_pipeline_en_5.5.0_3.0_1725475392315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_finetuned_bluegennx_run2_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_bluegennx_run2_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_bluegennx_run2_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|607.9 MB|
+
+## References
+
+https://huggingface.co/C4Scale/deberta-v3-base_finetuned_bluegennx_run2.6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_french_pipeline_en.md
new file mode 100644
index 00000000000000..e00990eaf0a1f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_french_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_french_pipeline pipeline DeBertaForSequenceClassification from KhawajaAbaid
+author: John Snow Labs
+name: deberta_v3_base_finetuned_french_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_french_pipeline` is a English model originally trained by KhawajaAbaid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_french_pipeline_en_5.5.0_3.0_1725462553420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_french_pipeline_en_5.5.0_3.0_1725462553420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_finetuned_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|610.2 MB|
+
+## References
+
+https://huggingface.co/KhawajaAbaid/deberta-v3-base-finetuned-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_mcqa_manyet1k_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_mcqa_manyet1k_en.md
new file mode 100644
index 00000000000000..d8aaa5fd66fd2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_finetuned_mcqa_manyet1k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_mcqa_manyet1k DeBertaForSequenceClassification from manyet1k
+author: John Snow Labs
+name: deberta_v3_base_finetuned_mcqa_manyet1k
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_mcqa_manyet1k` is a English model originally trained by manyet1k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_mcqa_manyet1k_en_5.5.0_3.0_1725461829952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_mcqa_manyet1k_en_5.5.0_3.0_1725461829952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_finetuned_mcqa_manyet1k","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_finetuned_mcqa_manyet1k", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_mcqa_manyet1k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|575.1 MB|
+
+## References
+
+https://huggingface.co/manyet1k/deberta-v3-base-finetuned-mcqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_mnli_en.md
new file mode 100644
index 00000000000000..06cc5905ecbf05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_mnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_mnli DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_mnli
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mnli` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_en_5.5.0_3.0_1725439665240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_en_5.5.0_3.0_1725439665240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_mnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_mnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_mnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|641.2 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_mnli_pipeline_en.md
new file mode 100644
index 00000000000000..85e3c6b9cb9aef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_mnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_mnli_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_mnli_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mnli_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_pipeline_en_5.5.0_3.0_1725439715466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_pipeline_en_5.5.0_3.0_1725439715466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_mnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_mnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_mnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|641.2 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_otat_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_otat_en.md
new file mode 100644
index 00000000000000..9b555230506a53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_otat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_otat DeBertaForSequenceClassification from DandinPower
+author: John Snow Labs
+name: deberta_v3_base_otat
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_otat` is a English model originally trained by DandinPower.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_otat_en_5.5.0_3.0_1725439143176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_otat_en_5.5.0_3.0_1725439143176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_otat","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_otat", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_otat|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|611.9 MB|
+
+## References
+
+https://huggingface.co/DandinPower/deberta-v3-base-otat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_otat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_otat_pipeline_en.md
new file mode 100644
index 00000000000000..2d5e127b667b04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_otat_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_otat_pipeline pipeline DeBertaForSequenceClassification from DandinPower
+author: John Snow Labs
+name: deberta_v3_base_otat_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_otat_pipeline` is a English model originally trained by DandinPower.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_otat_pipeline_en_5.5.0_3.0_1725439186098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_otat_pipeline_en_5.5.0_3.0_1725439186098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_otat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_otat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_otat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|611.9 MB|
+
+## References
+
+https://huggingface.co/DandinPower/deberta-v3-base-otat
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_qnli_pipeline_en.md
new file mode 100644
index 00000000000000..a693bf4bb5033a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_qnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_qnli_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_qnli_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_qnli_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qnli_pipeline_en_5.5.0_3.0_1725468424291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_qnli_pipeline_en_5.5.0_3.0_1725468424291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_qnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_qnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_qnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|637.9 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-qnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_sst2_pipeline_en.md
new file mode 100644
index 00000000000000..554ff28d6d2c19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_sst2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_sst2_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_sst2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_sst2_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_sst2_pipeline_en_5.5.0_3.0_1725462947125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_sst2_pipeline_en_5.5.0_3.0_1725462947125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_sst2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_sst2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_sst2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|574.1 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-sst2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_zeroshot_v2_0_28heldout_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_zeroshot_v2_0_28heldout_pipeline_en.md
new file mode 100644
index 00000000000000..f1d577deabf0aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_base_zeroshot_v2_0_28heldout_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_zeroshot_v2_0_28heldout_pipeline pipeline DeBertaForSequenceClassification from MoritzLaurer
+author: John Snow Labs
+name: deberta_v3_base_zeroshot_v2_0_28heldout_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_zeroshot_v2_0_28heldout_pipeline` is a English model originally trained by MoritzLaurer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_zeroshot_v2_0_28heldout_pipeline_en_5.5.0_3.0_1725467830034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_zeroshot_v2_0_28heldout_pipeline_en_5.5.0_3.0_1725467830034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_zeroshot_v2_0_28heldout_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_zeroshot_v2_0_28heldout_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_zeroshot_v2_0_28heldout_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|440.4 MB|
+
+## References
+
+https://huggingface.co/MoritzLaurer/deberta-v3-base-zeroshot-v2.0-28heldout
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ft_financial_news_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ft_financial_news_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..e5ada25034aa70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ft_financial_news_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_ft_financial_news_sentiment_analysis DeBertaForSequenceClassification from mrm8488
+author: John Snow Labs
+name: deberta_v3_ft_financial_news_sentiment_analysis
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_ft_financial_news_sentiment_analysis` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_ft_financial_news_sentiment_analysis_en_5.5.0_3.0_1725462710216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_ft_financial_news_sentiment_analysis_en_5.5.0_3.0_1725462710216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_ft_financial_news_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_ft_financial_news_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_ft_financial_news_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|423.3 MB|
+
+## References
+
+https://huggingface.co/mrm8488/deberta-v3-ft-financial-news-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ft_financial_news_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ft_financial_news_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..7f178a150ae20f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ft_financial_news_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_ft_financial_news_sentiment_analysis_pipeline pipeline DeBertaForSequenceClassification from mrm8488
+author: John Snow Labs
+name: deberta_v3_ft_financial_news_sentiment_analysis_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_ft_financial_news_sentiment_analysis_pipeline` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_ft_financial_news_sentiment_analysis_pipeline_en_5.5.0_3.0_1725462766993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_ft_financial_news_sentiment_analysis_pipeline_en_5.5.0_3.0_1725462766993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_ft_financial_news_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_ft_financial_news_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_ft_financial_news_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|423.3 MB|
+
+## References
+
+https://huggingface.co/mrm8488/deberta-v3-ft-financial-news-sentiment-analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_16_0_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_16_0_en.md
new file mode 100644
index 00000000000000..c75147ae1c6296
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_16_0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_16_0 DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_16_0
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_16_0` is a English model originally trained by SetFit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_0_en_5.5.0_3.0_1725438973912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_0_en_5.5.0_3.0_1725438973912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_16_0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_16_0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_16_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_16_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_16_0_pipeline_en.md
new file mode 100644
index 00000000000000..0db5048f2d5cb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_16_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_16_0_pipeline pipeline DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_16_0_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_16_0_pipeline` is a English model originally trained by SetFit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_0_pipeline_en_5.5.0_3.0_1725439080137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_16_0_pipeline_en_5.5.0_3.0_1725439080137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_16_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_16_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_16_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-16-0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_6_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_6_en.md
new file mode 100644
index 00000000000000..90d2749416a367
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_6 DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_6
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_6` is a English model originally trained by SetFit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_6_en_5.5.0_3.0_1725462657955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_6_en_5.5.0_3.0_1725462657955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_6","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_6", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_6|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_6_pipeline_en.md
new file mode 100644
index 00000000000000..8dee8d3f0bd96c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_6_pipeline pipeline DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_6_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_6_pipeline` is a English model originally trained by SetFit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_6_pipeline_en_5.5.0_3.0_1725462751953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_6_pipeline_en_5.5.0_3.0_1725462751953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_8_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_8_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_8_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_8_en.md
new file mode 100644
index 00000000000000..c869d58021fe8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_8_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_8 DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_8
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_8` is a English model originally trained by SetFit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_8_en_5.5.0_3.0_1725462034082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_8_en_5.5.0_3.0_1725462034082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_8","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_8", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_8|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_8_pipeline_en.md
new file mode 100644
index 00000000000000..b3f8c458a6c1d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large__sst2__train_8_8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_8_pipeline pipeline DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_8_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_8_pipeline` is a English model originally trained by SetFit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_8_pipeline_en_5.5.0_3.0_1725462154206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_8_pipeline_en_5.5.0_3.0_1725462154206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_8_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_8_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-8
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_2epochs_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_2epochs_en.md
new file mode 100644
index 00000000000000..e01c13b7ffeecb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_2epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_ad_opentag_finetuned_ner_2epochs DeBertaForTokenClassification from ABrinkmann
+author: John Snow Labs
+name: deberta_v3_large_ad_opentag_finetuned_ner_2epochs
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_ad_opentag_finetuned_ner_2epochs` is a English model originally trained by ABrinkmann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ad_opentag_finetuned_ner_2epochs_en_5.5.0_3.0_1725474510705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ad_opentag_finetuned_ner_2epochs_en_5.5.0_3.0_1725474510705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_ad_opentag_finetuned_ner_2epochs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_ad_opentag_finetuned_ner_2epochs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_ad_opentag_finetuned_ner_2epochs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ABrinkmann/deberta-v3-large-ad-opentag-finetuned-ner-2epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline_en.md
new file mode 100644
index 00000000000000..69122ddc8ef9bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline pipeline DeBertaForTokenClassification from ABrinkmann
+author: John Snow Labs
+name: deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline` is a English model originally trained by ABrinkmann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline_en_5.5.0_3.0_1725474590993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline_en_5.5.0_3.0_1725474590993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_ad_opentag_finetuned_ner_2epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ABrinkmann/deberta-v3-large-ad-opentag-finetuned-ner-2epochs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..02f8744c9b8bfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_classifier_pipeline pipeline DeBertaForSequenceClassification from KatoHF
+author: John Snow Labs
+name: deberta_v3_large_classifier_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_classifier_pipeline` is a English model originally trained by KatoHF.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_classifier_pipeline_en_5.5.0_3.0_1725464177173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_classifier_pipeline_en_5.5.0_3.0_1725464177173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.1 MB|
+
+## References
+
+https://huggingface.co/KatoHF/deberta-v3-large-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_en.md
new file mode 100644
index 00000000000000..96fe6c8788de08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22 DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22` is a English model originally trained by domenicrosati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_en_5.5.0_3.0_1725469525803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_en_5.5.0_3.0_1725469525803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-finetuned-DAGPap22
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline_en.md
new file mode 100644
index 00000000000000..515c02bd6c2566
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline` is a English model originally trained by domenicrosati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline_en_5.5.0_3.0_1725469600776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline_en_5.5.0_3.0_1725469600776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_dapt_scientific_papers_pubmed_finetuned_dagpap22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-finetuned-DAGPap22
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_fever_pepa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_fever_pepa_pipeline_en.md
new file mode 100644
index 00000000000000..82de86b03b1e60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_fever_pepa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_fever_pepa_pipeline pipeline DeBertaForSequenceClassification from pepa
+author: John Snow Labs
+name: deberta_v3_large_fever_pepa_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_fever_pepa_pipeline` is a English model originally trained by pepa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_fever_pepa_pipeline_en_5.5.0_3.0_1725462464087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_fever_pepa_pipeline_en_5.5.0_3.0_1725462464087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_fever_pepa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_fever_pepa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_fever_pepa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/pepa/deberta-v3-large-fever
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_chandc_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_chandc_en.md
new file mode 100644
index 00000000000000..6362f8c170de23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_chandc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_ner_chandc DeBertaForTokenClassification from chandc
+author: John Snow Labs
+name: deberta_v3_large_finetuned_ner_chandc
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_ner_chandc` is a English model originally trained by chandc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_chandc_en_5.5.0_3.0_1725474619115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_chandc_en_5.5.0_3.0_1725474619115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_finetuned_ner_chandc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_finetuned_ner_chandc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_ner_chandc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/chandc/deberta-v3-large-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_chandc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_chandc_pipeline_en.md
new file mode 100644
index 00000000000000..50fc89f696e7fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_chandc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_ner_chandc_pipeline pipeline DeBertaForTokenClassification from chandc
+author: John Snow Labs
+name: deberta_v3_large_finetuned_ner_chandc_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_ner_chandc_pipeline` is a English model originally trained by chandc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_chandc_pipeline_en_5.5.0_3.0_1725474725200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_chandc_pipeline_en_5.5.0_3.0_1725474725200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_finetuned_ner_chandc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_finetuned_ner_chandc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_ner_chandc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/chandc/deberta-v3-large-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_nli_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_nli_v1_en.md
new file mode 100644
index 00000000000000..a7646aa77a9391
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_nli_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_nli_v1 DeBertaForSequenceClassification from sjrhuschlee
+author: John Snow Labs
+name: deberta_v3_large_nli_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_nli_v1` is a English model originally trained by sjrhuschlee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_nli_v1_en_5.5.0_3.0_1725438648683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_nli_v1_en_5.5.0_3.0_1725438648683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_nli_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_nli_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_nli_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/sjrhuschlee/deberta-v3-large-nli-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_nli_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_nli_v1_pipeline_en.md
new file mode 100644
index 00000000000000..da41c312dfccaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_nli_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_nli_v1_pipeline pipeline DeBertaForSequenceClassification from sjrhuschlee
+author: John Snow Labs
+name: deberta_v3_large_nli_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_nli_v1_pipeline` is a English model originally trained by sjrhuschlee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_nli_v1_pipeline_en_5.5.0_3.0_1725438742504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_nli_v1_pipeline_en_5.5.0_3.0_1725438742504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_nli_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_nli_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_nli_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/sjrhuschlee/deberta-v3-large-nli-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_main_passage_consistency_rater_all_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_main_passage_consistency_rater_all_en.md
new file mode 100644
index 00000000000000..e76ca8070e6947
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_main_passage_consistency_rater_all_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_survey_main_passage_consistency_rater_all DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_main_passage_consistency_rater_all
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_main_passage_consistency_rater_all` is a English model originally trained by domenicrosati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_consistency_rater_all_en_5.5.0_3.0_1725439810481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_consistency_rater_all_en_5.5.0_3.0_1725439810481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_main_passage_consistency_rater_all","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_main_passage_consistency_rater_all", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_main_passage_consistency_rater_all|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-main_passage_consistency-rater-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline_en.md
new file mode 100644
index 00000000000000..90e406bbfa82d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline` is a English model originally trained by domenicrosati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725469515237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725469515237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_main_passage_old_facts_rater_all_gpt4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-main_passage_old_facts-rater-all-gpt4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline_en.md
new file mode 100644
index 00000000000000..47e8f525a9a6ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline` is a English model originally trained by domenicrosati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline_en_5.5.0_3.0_1725440191813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline_en_5.5.0_3.0_1725440191813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_nepal_bhasa_fact_main_passage_rater_gpt4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-new_fact_main_passage-rater-gpt4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ttc_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ttc_en.md
new file mode 100644
index 00000000000000..956a6f6491b32f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ttc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_ttc DeBertaForTokenClassification from tner
+author: John Snow Labs
+name: deberta_v3_large_ttc
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_ttc` is a English model originally trained by tner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ttc_en_5.5.0_3.0_1725471702569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ttc_en_5.5.0_3.0_1725471702569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_ttc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_ttc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_ttc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/tner/deberta-v3-large-ttc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ttc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ttc_pipeline_en.md
new file mode 100644
index 00000000000000..cf75e8a329069c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ttc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_ttc_pipeline pipeline DeBertaForTokenClassification from tner
+author: John Snow Labs
+name: deberta_v3_large_ttc_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_ttc_pipeline` is a English model originally trained by tner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ttc_pipeline_en_5.5.0_3.0_1725471834626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ttc_pipeline_en_5.5.0_3.0_1725471834626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_ttc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_ttc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_ttc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/tner/deberta-v3-large-ttc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_ind_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_ind_en.md
new file mode 100644
index 00000000000000..a70a031e4ee86f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_ind_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_ner_ind DeBertaForTokenClassification from Venkatesh4342
+author: John Snow Labs
+name: deberta_v3_ner_ind
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_ner_ind` is a English model originally trained by Venkatesh4342.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_ner_ind_en_5.5.0_3.0_1725474085431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_ner_ind_en_5.5.0_3.0_1725474085431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_ner_ind","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_ner_ind", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_ner_ind|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Venkatesh4342/deberta-v3-NER-ind
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_ind_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_ind_pipeline_en.md
new file mode 100644
index 00000000000000..8ac84b025f4c3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_ind_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_ner_ind_pipeline pipeline DeBertaForTokenClassification from Venkatesh4342
+author: John Snow Labs
+name: deberta_v3_ner_ind_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_ner_ind_pipeline` is a English model originally trained by Venkatesh4342.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_ner_ind_pipeline_en_5.5.0_3.0_1725474164262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_ner_ind_pipeline_en_5.5.0_3.0_1725474164262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_ner_ind_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_ner_ind_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_ner_ind_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Venkatesh4342/deberta-v3-NER-ind
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_v1_en.md
new file mode 100644
index 00000000000000..2fc75a7b75a2e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_ner_v1 DeBertaForTokenClassification from kabir5297
+author: John Snow Labs
+name: deberta_v3_ner_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_ner_v1` is a English model originally trained by kabir5297.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_ner_v1_en_5.5.0_3.0_1725472003748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_ner_v1_en_5.5.0_3.0_1725472003748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_ner_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_ner_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_ner_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|635.2 MB|
+
+## References
+
+https://huggingface.co/kabir5297/deberta_v3_ner_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_disaster_tweets_part1_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_disaster_tweets_part1_en.md
new file mode 100644
index 00000000000000..391167080e4b13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_disaster_tweets_part1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_small_finetuned_disaster_tweets_part1 DeBertaForSequenceClassification from victorbahlangene
+author: John Snow Labs
+name: deberta_v3_small_finetuned_disaster_tweets_part1
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_disaster_tweets_part1` is a English model originally trained by victorbahlangene.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_disaster_tweets_part1_en_5.5.0_3.0_1725440118333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_disaster_tweets_part1_en_5.5.0_3.0_1725440118333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_disaster_tweets_part1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_disaster_tweets_part1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_finetuned_disaster_tweets_part1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|443.6 MB|
+
+## References
+
+https://huggingface.co/victorbahlangene/deberta-v3-small-finetuned-Disaster-Tweets-Part1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_disaster_tweets_part1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_disaster_tweets_part1_pipeline_en.md
new file mode 100644
index 00000000000000..108a9117a5c7e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_disaster_tweets_part1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_small_finetuned_disaster_tweets_part1_pipeline pipeline DeBertaForSequenceClassification from victorbahlangene
+author: John Snow Labs
+name: deberta_v3_small_finetuned_disaster_tweets_part1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_disaster_tweets_part1_pipeline` is a English model originally trained by victorbahlangene.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_disaster_tweets_part1_pipeline_en_5.5.0_3.0_1725440157602.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_disaster_tweets_part1_pipeline_en_5.5.0_3.0_1725440157602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_small_finetuned_disaster_tweets_part1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_small_finetuned_disaster_tweets_part1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_finetuned_disaster_tweets_part1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|443.6 MB|
+
+## References
+
+https://huggingface.co/victorbahlangene/deberta-v3-small-finetuned-Disaster-Tweets-Part1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_mrpc_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_mrpc_en.md
new file mode 100644
index 00000000000000..d7ecd93cfd0b73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_mrpc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_small_finetuned_mrpc DeBertaForSequenceClassification from mrm8488
+author: John Snow Labs
+name: deberta_v3_small_finetuned_mrpc
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_mrpc` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_mrpc_en_5.5.0_3.0_1725463105268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_mrpc_en_5.5.0_3.0_1725463105268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_mrpc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_mrpc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_finetuned_mrpc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|414.9 MB|
+
+## References
+
+https://huggingface.co/mrm8488/deberta-v3-small-finetuned-mrpc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_mrpc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_mrpc_pipeline_en.md
new file mode 100644
index 00000000000000..ddf0bbc3091631
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_finetuned_mrpc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_small_finetuned_mrpc_pipeline pipeline DeBertaForSequenceClassification from mrm8488
+author: John Snow Labs
+name: deberta_v3_small_finetuned_mrpc_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_mrpc_pipeline` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_mrpc_pipeline_en_5.5.0_3.0_1725463172882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_mrpc_pipeline_en_5.5.0_3.0_1725463172882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_small_finetuned_mrpc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_small_finetuned_mrpc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_finetuned_mrpc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.9 MB|
+
+## References
+
+https://huggingface.co/mrm8488/deberta-v3-small-finetuned-mrpc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_snli_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_snli_en.md
new file mode 100644
index 00000000000000..0e1167d88793f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_snli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_small_snli DeBertaForSequenceClassification from pepa
+author: John Snow Labs
+name: deberta_v3_small_snli
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_snli` is a English model originally trained by pepa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_snli_en_5.5.0_3.0_1725440223851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_snli_en_5.5.0_3.0_1725440223851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_small_snli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_snli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_snli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|460.9 MB|
+
+## References
+
+https://huggingface.co/pepa/deberta-v3-small-snli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_snli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_snli_pipeline_en.md
new file mode 100644
index 00000000000000..586da34615fd77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_small_snli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_small_snli_pipeline pipeline DeBertaForSequenceClassification from pepa
+author: John Snow Labs
+name: deberta_v3_small_snli_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_snli_pipeline` is a English model originally trained by pepa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_snli_pipeline_en_5.5.0_3.0_1725440254049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_snli_pipeline_en_5.5.0_3.0_1725440254049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_small_snli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_small_snli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_snli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|460.9 MB|
+
+## References
+
+https://huggingface.co/pepa/deberta-v3-small-snli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_smallsed_rte_finetuned_rte_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_smallsed_rte_finetuned_rte_en.md
new file mode 100644
index 00000000000000..9d47a2acd49d1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_smallsed_rte_finetuned_rte_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_smallsed_rte_finetuned_rte DeBertaForSequenceClassification from ZaaCo
+author: John Snow Labs
+name: deberta_v3_smallsed_rte_finetuned_rte
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_smallsed_rte_finetuned_rte` is a English model originally trained by ZaaCo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_smallsed_rte_finetuned_rte_en_5.5.0_3.0_1725469066711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_smallsed_rte_finetuned_rte_en_5.5.0_3.0_1725469066711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_smallsed_rte_finetuned_rte","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_smallsed_rte_finetuned_rte", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_smallsed_rte_finetuned_rte|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|417.8 MB|
+
+## References
+
+https://huggingface.co/ZaaCo/deberta-v3-smallsed_rte-finetuned-rte
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_xsmall_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_xsmall_mnli_en.md
new file mode 100644
index 00000000000000..9fb8a16b6b15bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_xsmall_mnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_mnli DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_mnli
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_mnli` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mnli_en_5.5.0_3.0_1725468505426.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mnli_en_5.5.0_3.0_1725468505426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_mnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_mnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_mnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|241.3 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-debertabasepiitrained_en.md b/docs/_posts/ahmedlone127/2024-09-04-debertabasepiitrained_en.md
new file mode 100644
index 00000000000000..73654fe168d1c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-debertabasepiitrained_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English debertabasepiitrained DeBertaForTokenClassification from hardikpatel
+author: John Snow Labs
+name: debertabasepiitrained
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertabasepiitrained` is a English model originally trained by hardikpatel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertabasepiitrained_en_5.5.0_3.0_1725471522268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertabasepiitrained_en_5.5.0_3.0_1725471522268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("debertabasepiitrained","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("debertabasepiitrained", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|debertabasepiitrained|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|621.7 MB|
+
+## References
+
+https://huggingface.co/hardikpatel/debertabasepiitrained
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-debertabasepiitrained_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-debertabasepiitrained_pipeline_en.md
new file mode 100644
index 00000000000000..94c31e830e018c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-debertabasepiitrained_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English debertabasepiitrained_pipeline pipeline DeBertaForTokenClassification from hardikpatel
+author: John Snow Labs
+name: debertabasepiitrained_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertabasepiitrained_pipeline` is a English model originally trained by hardikpatel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertabasepiitrained_pipeline_en_5.5.0_3.0_1725471572306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertabasepiitrained_pipeline_en_5.5.0_3.0_1725471572306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("debertabasepiitrained_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("debertabasepiitrained_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|debertabasepiitrained_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|621.7 MB|
+
+## References
+
+https://huggingface.co/hardikpatel/debertabasepiitrained
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-debiasing_pre_trained_contextualised_embeddings_albert_en.md b/docs/_posts/ahmedlone127/2024-09-04-debiasing_pre_trained_contextualised_embeddings_albert_en.md
new file mode 100644
index 00000000000000..3fc4ef86168545
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-debiasing_pre_trained_contextualised_embeddings_albert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English debiasing_pre_trained_contextualised_embeddings_albert AlbertEmbeddings from Daniel-Saeedi
+author: John Snow Labs
+name: debiasing_pre_trained_contextualised_embeddings_albert
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debiasing_pre_trained_contextualised_embeddings_albert` is a English model originally trained by Daniel-Saeedi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debiasing_pre_trained_contextualised_embeddings_albert_en_5.5.0_3.0_1725457626468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debiasing_pre_trained_contextualised_embeddings_albert_en_5.5.0_3.0_1725457626468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("debiasing_pre_trained_contextualised_embeddings_albert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("debiasing_pre_trained_contextualised_embeddings_albert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|debiasing_pre_trained_contextualised_embeddings_albert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/Daniel-Saeedi/debiasing_pre-trained_contextualised_embeddings_albert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-debiasing_pre_trained_contextualised_embeddings_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-debiasing_pre_trained_contextualised_embeddings_albert_pipeline_en.md
new file mode 100644
index 00000000000000..bc8edf4d5d3dcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-debiasing_pre_trained_contextualised_embeddings_albert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English debiasing_pre_trained_contextualised_embeddings_albert_pipeline pipeline AlbertEmbeddings from Daniel-Saeedi
+author: John Snow Labs
+name: debiasing_pre_trained_contextualised_embeddings_albert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debiasing_pre_trained_contextualised_embeddings_albert_pipeline` is a English model originally trained by Daniel-Saeedi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debiasing_pre_trained_contextualised_embeddings_albert_pipeline_en_5.5.0_3.0_1725457628831.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debiasing_pre_trained_contextualised_embeddings_albert_pipeline_en_5.5.0_3.0_1725457628831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("debiasing_pre_trained_contextualised_embeddings_albert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("debiasing_pre_trained_contextualised_embeddings_albert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|debiasing_pre_trained_contextualised_embeddings_albert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/Daniel-Saeedi/debiasing_pre-trained_contextualised_embeddings_albert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deep_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deep_2_pipeline_en.md
new file mode 100644
index 00000000000000..c4f8a77f9a9686
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deep_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deep_2_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: deep_2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deep_2_pipeline` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deep_2_pipeline_en_5.5.0_3.0_1725453426539.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deep_2_pipeline_en_5.5.0_3.0_1725453426539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deep_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deep_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deep_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Deep_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dictabert_large_ner_he.md b/docs/_posts/ahmedlone127/2024-09-04-dictabert_large_ner_he.md
new file mode 100644
index 00000000000000..c4d168f8e15f6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dictabert_large_ner_he.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hebrew dictabert_large_ner BertForTokenClassification from dicta-il
+author: John Snow Labs
+name: dictabert_large_ner
+date: 2024-09-04
+tags: [he, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: he
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dictabert_large_ner` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dictabert_large_ner_he_5.5.0_3.0_1725477706754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dictabert_large_ner_he_5.5.0_3.0_1725477706754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("dictabert_large_ner","he") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("dictabert_large_ner", "he")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dictabert_large_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|he|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/dicta-il/dictabert-large-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dictabert_large_ner_pipeline_he.md b/docs/_posts/ahmedlone127/2024-09-04-dictabert_large_ner_pipeline_he.md
new file mode 100644
index 00000000000000..87d25e94db5ade
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dictabert_large_ner_pipeline_he.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hebrew dictabert_large_ner_pipeline pipeline BertForTokenClassification from dicta-il
+author: John Snow Labs
+name: dictabert_large_ner_pipeline
+date: 2024-09-04
+tags: [he, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: he
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dictabert_large_ner_pipeline` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dictabert_large_ner_pipeline_he_5.5.0_3.0_1725477792015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dictabert_large_ner_pipeline_he_5.5.0_3.0_1725477792015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dictabert_large_ner_pipeline", lang = "he")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dictabert_large_ner_pipeline", lang = "he")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dictabert_large_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|he|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/dicta-il/dictabert-large-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-disease_identification_sonatafyai_bert_v1_sonatafyai_en.md b/docs/_posts/ahmedlone127/2024-09-04-disease_identification_sonatafyai_bert_v1_sonatafyai_en.md
new file mode 100644
index 00000000000000..fa691a97ff5076
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-disease_identification_sonatafyai_bert_v1_sonatafyai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English disease_identification_sonatafyai_bert_v1_sonatafyai BertForTokenClassification from Sonatafyai
+author: John Snow Labs
+name: disease_identification_sonatafyai_bert_v1_sonatafyai
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disease_identification_sonatafyai_bert_v1_sonatafyai` is a English model originally trained by Sonatafyai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disease_identification_sonatafyai_bert_v1_sonatafyai_en_5.5.0_3.0_1725449843907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disease_identification_sonatafyai_bert_v1_sonatafyai_en_5.5.0_3.0_1725449843907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("disease_identification_sonatafyai_bert_v1_sonatafyai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("disease_identification_sonatafyai_bert_v1_sonatafyai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disease_identification_sonatafyai_bert_v1_sonatafyai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Sonatafyai/Disease_Identification_SonatafyAI_BERT_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline_en.md
new file mode 100644
index 00000000000000..1b8f7eca24a405
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline pipeline BertForTokenClassification from Sonatafyai
+author: John Snow Labs
+name: disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline` is a English model originally trained by Sonatafyai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline_en_5.5.0_3.0_1725449864512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline_en_5.5.0_3.0_1725449864512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disease_identification_sonatafyai_bert_v1_sonatafyai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Sonatafyai/Disease_Identification_SonatafyAI_BERT_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distil_bert_docred_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distil_bert_docred_ner_pipeline_en.md
new file mode 100644
index 00000000000000..d2e4dbc0743366
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distil_bert_docred_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distil_bert_docred_ner_pipeline pipeline DistilBertForTokenClassification from dennishauser
+author: John Snow Labs
+name: distil_bert_docred_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_docred_ner_pipeline` is a English model originally trained by dennishauser.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_docred_ner_pipeline_en_5.5.0_3.0_1725448701264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_docred_ner_pipeline_en_5.5.0_3.0_1725448701264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_docred_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_docred_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_docred_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/dennishauser/distil-bert-docred-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_alex_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_alex_en.md
new file mode 100644
index 00000000000000..de7f7bdd4307e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_alex_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_alex DistilBertForQuestionAnswering from Alexhv
+author: John Snow Labs
+name: distilbert_alex
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_alex` is a English model originally trained by Alexhv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_alex_en_5.5.0_3.0_1725465405289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_alex_en_5.5.0_3.0_1725465405289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_alex","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_alex", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_alex|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Alexhv/distilbert-alex
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_alex_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_alex_pipeline_en.md
new file mode 100644
index 00000000000000..461a205cf15f25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_alex_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_alex_pipeline pipeline DistilBertForQuestionAnswering from Alexhv
+author: John Snow Labs
+name: distilbert_alex_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_alex_pipeline` is a English model originally trained by Alexhv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_alex_pipeline_en_5.5.0_3.0_1725465417043.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_alex_pipeline_en_5.5.0_3.0_1725465417043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_alex_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_alex_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_alex_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Alexhv/distilbert-alex
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_finetuned_conll2003_english_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_finetuned_conll2003_english_ner_pipeline_en.md
new file mode 100644
index 00000000000000..409d29bd5f463c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_finetuned_conll2003_english_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_cased_finetuned_conll2003_english_ner_pipeline pipeline DistilBertForTokenClassification from MrRobson9
+author: John Snow Labs
+name: distilbert_base_cased_finetuned_conll2003_english_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_finetuned_conll2003_english_ner_pipeline` is a English model originally trained by MrRobson9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_finetuned_conll2003_english_ner_pipeline_en_5.5.0_3.0_1725448219102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_finetuned_conll2003_english_ner_pipeline_en_5.5.0_3.0_1725448219102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_cased_finetuned_conll2003_english_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_cased_finetuned_conll2003_english_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_finetuned_conll2003_english_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MrRobson9/distilbert-base-cased-finetuned-conll2003-english-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_finetuned_en.md
new file mode 100644
index 00000000000000..f550ef583f1291
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_cased_finetuned DistilBertEmbeddings from GusNicho
+author: John Snow Labs
+name: distilbert_base_cased_finetuned
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_finetuned` is a English model originally trained by GusNicho.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_finetuned_en_5.5.0_3.0_1725414396536.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_finetuned_en_5.5.0_3.0_1725414396536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_cased_finetuned","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_cased_finetuned","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/GusNicho/distilbert-base-cased-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_pii_english_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_pii_english_en.md
new file mode 100644
index 00000000000000..753c84d7c1762f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_cased_pii_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_cased_pii_english DistilBertForTokenClassification from yonigo
+author: John Snow Labs
+name: distilbert_base_cased_pii_english
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_pii_english` is a English model originally trained by yonigo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_pii_english_en_5.5.0_3.0_1725448439011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_pii_english_en_5.5.0_3.0_1725448439011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_cased_pii_english","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_cased_pii_english", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_pii_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/yonigo/distilbert-base-cased-pii-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_data_wnut_17_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_data_wnut_17_en.md
new file mode 100644
index 00000000000000..b6d85b4180d3c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_data_wnut_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_data_wnut_17 DistilBertForTokenClassification from Pongprecha
+author: John Snow Labs
+name: distilbert_base_data_wnut_17
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_data_wnut_17` is a English model originally trained by Pongprecha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_data_wnut_17_en_5.5.0_3.0_1725476518119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_data_wnut_17_en_5.5.0_3.0_1725476518119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_data_wnut_17","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_data_wnut_17", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_data_wnut_17|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Pongprecha/distilbert_base_data_wnut_17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_english_greek_modern_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_english_greek_modern_cased_pipeline_en.md
new file mode 100644
index 00000000000000..5bada639a6a483
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_english_greek_modern_cased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_english_greek_modern_cased_pipeline pipeline DistilBertEmbeddings from Geotrend
+author: John Snow Labs
+name: distilbert_base_english_greek_modern_cased_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_english_greek_modern_cased_pipeline` is a English model originally trained by Geotrend.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_english_greek_modern_cased_pipeline_en_5.5.0_3.0_1725414412333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_english_greek_modern_cased_pipeline_en_5.5.0_3.0_1725414412333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_english_greek_modern_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_english_greek_modern_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_english_greek_modern_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|248.9 MB|
+
+## References
+
+https://huggingface.co/Geotrend/distilbert-base-en-el-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish_xx.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish_xx.md
new file mode 100644
index 00000000000000..6c3b1f7ec33270
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish DistilBertEmbeddings from lusxvr
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish
+date: 2024-09-04
+tags: [xx, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish` is a Multilingual model originally trained by lusxvr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish_xx_5.5.0_3.0_1725413898245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish_xx_5.5.0_3.0_1725413898245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_english_portuguese_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/lusxvr/distilbert-base-multilingual-cased-finetuned-en_pt_es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_biored_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_biored_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..a660eaf8a05ccd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_biored_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_biored_finetuned_pipeline pipeline DistilBertForTokenClassification from Dagobert42
+author: John Snow Labs
+name: distilbert_base_uncased_biored_finetuned_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_biored_finetuned_pipeline` is a English model originally trained by Dagobert42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_biored_finetuned_pipeline_en_5.5.0_3.0_1725448818593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_biored_finetuned_pipeline_en_5.5.0_3.0_1725448818593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_biored_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_biored_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_biored_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|248.7 MB|
+
+## References
+
+https://huggingface.co/Dagobert42/distilbert-base-uncased-biored-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_custom_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_custom_en.md
new file mode 100644
index 00000000000000..dba05f61c4ffce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_custom_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_custom DistilBertForTokenClassification from BennB
+author: John Snow Labs
+name: distilbert_base_uncased_custom
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_custom` is a English model originally trained by BennB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_custom_en_5.5.0_3.0_1725460578766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_custom_en_5.5.0_3.0_1725460578766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_custom","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_custom", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_custom|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/BennB/distilbert-base-uncased-custom
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_custom_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_custom_pipeline_en.md
new file mode 100644
index 00000000000000..8735aa00e0ab74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_custom_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_custom_pipeline pipeline DistilBertForTokenClassification from BennB
+author: John Snow Labs
+name: distilbert_base_uncased_custom_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_custom_pipeline` is a English model originally trained by BennB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_custom_pipeline_en_5.5.0_3.0_1725460590624.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_custom_pipeline_en_5.5.0_3.0_1725460590624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_custom_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_custom_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_custom_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/BennB/distilbert-base-uncased-custom
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_distilled_squad_finetuned_srh_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_distilled_squad_finetuned_srh_v1_en.md
new file mode 100644
index 00000000000000..9b89675bcf5ec3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_distilled_squad_finetuned_srh_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_squad_finetuned_srh_v1 DistilBertForQuestionAnswering from allistair99
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_squad_finetuned_srh_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_squad_finetuned_srh_v1` is a English model originally trained by allistair99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_squad_finetuned_srh_v1_en_5.5.0_3.0_1725465798300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_squad_finetuned_srh_v1_en_5.5.0_3.0_1725465798300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_distilled_squad_finetuned_srh_v1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_distilled_squad_finetuned_srh_v1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_squad_finetuned_srh_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/allistair99/distilbert-base-uncased-distilled-squad-finetuned-SRH-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline_en.md
new file mode 100644
index 00000000000000..38bcc5e2100559
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline pipeline DistilBertForQuestionAnswering from allistair99
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline` is a English model originally trained by allistair99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline_en_5.5.0_3.0_1725465810611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline_en_5.5.0_3.0_1725465810611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_squad_finetuned_srh_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/allistair99/distilbert-base-uncased-distilled-squad-finetuned-SRH-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_5tagonly_ner_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_5tagonly_ner_en.md
new file mode 100644
index 00000000000000..17e7624664e6a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_5tagonly_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_5tagonly_ner DistilBertForTokenClassification from emilyblah
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_5tagonly_ner
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_5tagonly_ner` is a English model originally trained by emilyblah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_5tagonly_ner_en_5.5.0_3.0_1725448198902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_5tagonly_ner_en_5.5.0_3.0_1725448198902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_5tagonly_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_5tagonly_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_5tagonly_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/emilyblah/distilbert-base-uncased-finetuned-5tagOnly-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_5tagonly_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_5tagonly_ner_pipeline_en.md
new file mode 100644
index 00000000000000..77f5ef6088da2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_5tagonly_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_5tagonly_ner_pipeline pipeline DistilBertForTokenClassification from emilyblah
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_5tagonly_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_5tagonly_ner_pipeline` is a English model originally trained by emilyblah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_5tagonly_ner_pipeline_en_5.5.0_3.0_1725448215144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_5tagonly_ner_pipeline_en_5.5.0_3.0_1725448215144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_5tagonly_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_5tagonly_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_5tagonly_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/emilyblah/distilbert-base-uncased-finetuned-5tagOnly-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ag_news_v4_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ag_news_v4_en.md
new file mode 100644
index 00000000000000..e5d44cb3df4231
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ag_news_v4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ag_news_v4 DistilBertEmbeddings from miggwp
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ag_news_v4
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ag_news_v4` is a English model originally trained by miggwp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_v4_en_5.5.0_3.0_1725418534745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_v4_en_5.5.0_3.0_1725418534745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_ag_news_v4","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_ag_news_v4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ag_news_v4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/miggwp/distilbert-base-uncased-finetuned-ag-news-v4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ag_news_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ag_news_v4_pipeline_en.md
new file mode 100644
index 00000000000000..47e02c8a5fa89b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ag_news_v4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ag_news_v4_pipeline pipeline DistilBertEmbeddings from miggwp
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ag_news_v4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ag_news_v4_pipeline` is a English model originally trained by miggwp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_v4_pipeline_en_5.5.0_3.0_1725418548144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_v4_pipeline_en_5.5.0_3.0_1725418548144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ag_news_v4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ag_news_v4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ag_news_v4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/miggwp/distilbert-base-uncased-finetuned-ag-news-v4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_cola_dev2k_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_cola_dev2k_en.md
new file mode 100644
index 00000000000000..8109fa984ec254
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_cola_dev2k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_dev2k DistilBertForSequenceClassification from dev2k
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_dev2k
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_dev2k` is a English model originally trained by dev2k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_dev2k_en_5.5.0_3.0_1725489809688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_dev2k_en_5.5.0_3.0_1725489809688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_dev2k","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_dev2k", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_dev2k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/dev2k/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_emotion_klempear_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_emotion_klempear_pipeline_en.md
new file mode 100644
index 00000000000000..6710874de5fc82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_emotion_klempear_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_klempear_pipeline pipeline DistilBertForSequenceClassification from KlemPear
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_klempear_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_klempear_pipeline` is a English model originally trained by KlemPear.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_klempear_pipeline_en_5.5.0_3.0_1725489986548.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_klempear_pipeline_en_5.5.0_3.0_1725489986548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_klempear_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_klempear_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_klempear_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KlemPear/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_finer_test_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_finer_test_en.md
new file mode 100644
index 00000000000000..78dd2576fe1ea4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_finer_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_finer_test DistilBertForTokenClassification from bodias
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_finer_test
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_finer_test` is a English model originally trained by bodias.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_finer_test_en_5.5.0_3.0_1725492647900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_finer_test_en_5.5.0_3.0_1725492647900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_finer_test","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_finer_test", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_finer_test|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/bodias/distilbert-base-uncased-finetuned-FiNER_test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline_en.md
new file mode 100644
index 00000000000000..986cfc4e2e3e9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline pipeline DistilBertEmbeddings from delayedkarma
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline` is a English model originally trained by delayedkarma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline_en_5.5.0_3.0_1725414095904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline_en_5.5.0_3.0_1725414095904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_delayedkarma_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/delayedkarma/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_en.md
new file mode 100644
index 00000000000000..ce980a5cb1ed25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho DistilBertEmbeddings from schubertcarvalho
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho` is a English model originally trained by schubertcarvalho.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_en_5.5.0_3.0_1725418469504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_en_5.5.0_3.0_1725418469504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/schubertcarvalho/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline_en.md
new file mode 100644
index 00000000000000..88fc224a76f77f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline pipeline DistilBertEmbeddings from schubertcarvalho
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline` is a English model originally trained by schubertcarvalho.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline_en_5.5.0_3.0_1725418485213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline_en_5.5.0_3.0_1725418485213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_schubertcarvalho_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/schubertcarvalho/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_ce_kishi_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_ce_kishi_en.md
new file mode 100644
index 00000000000000..4a753129b92832
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_ce_kishi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_ce_kishi DistilBertEmbeddings from ce-kishi
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_ce_kishi
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ce_kishi` is a English model originally trained by ce-kishi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ce_kishi_en_5.5.0_3.0_1725418679042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ce_kishi_en_5.5.0_3.0_1725418679042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ce_kishi","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ce_kishi","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_ce_kishi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ce-kishi/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dreamuno_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dreamuno_en.md
new file mode 100644
index 00000000000000..3efd211ad68dbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dreamuno_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dreamuno DistilBertEmbeddings from Dreamuno
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dreamuno
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dreamuno` is a English model originally trained by Dreamuno.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dreamuno_en_5.5.0_3.0_1725414267986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dreamuno_en_5.5.0_3.0_1725414267986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dreamuno","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dreamuno","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dreamuno|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Dreamuno/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline_en.md
new file mode 100644
index 00000000000000..f7f0c09f935192
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline pipeline DistilBertEmbeddings from Dreamuno
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline` is a English model originally trained by Dreamuno.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline_en_5.5.0_3.0_1725414280876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline_en_5.5.0_3.0_1725414280876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dreamuno_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Dreamuno/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dsfdsf2_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dsfdsf2_en.md
new file mode 100644
index 00000000000000..936fc50fced6d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dsfdsf2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dsfdsf2 DistilBertEmbeddings from dsfdsf2
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dsfdsf2
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dsfdsf2` is a English model originally trained by dsfdsf2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dsfdsf2_en_5.5.0_3.0_1725414495716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dsfdsf2_en_5.5.0_3.0_1725414495716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dsfdsf2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dsfdsf2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dsfdsf2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dsfdsf2/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline_en.md
new file mode 100644
index 00000000000000..209c9197bb2bda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline pipeline DistilBertEmbeddings from dsfdsf2
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline` is a English model originally trained by dsfdsf2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline_en_5.5.0_3.0_1725414509181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline_en_5.5.0_3.0_1725414509181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dsfdsf2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dsfdsf2/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline_en.md
new file mode 100644
index 00000000000000..ca094381f4b98c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline pipeline DistilBertEmbeddings from greyfoss
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline` is a English model originally trained by greyfoss.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline_en_5.5.0_3.0_1725413996943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline_en_5.5.0_3.0_1725413996943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_greyfoss_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/greyfoss/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_husseineid_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_husseineid_en.md
new file mode 100644
index 00000000000000..219008357a5b96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_husseineid_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_husseineid DistilBertEmbeddings from HusseinEid
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_husseineid
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_husseineid` is a English model originally trained by HusseinEid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_husseineid_en_5.5.0_3.0_1725413881726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_husseineid_en_5.5.0_3.0_1725413881726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_husseineid","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_husseineid","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_husseineid|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/HusseinEid/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_husseineid_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_husseineid_pipeline_en.md
new file mode 100644
index 00000000000000..bf89c101953637
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_husseineid_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_husseineid_pipeline pipeline DistilBertEmbeddings from HusseinEid
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_husseineid_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_husseineid_pipeline` is a English model originally trained by HusseinEid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_husseineid_pipeline_en_5.5.0_3.0_1725413896680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_husseineid_pipeline_en_5.5.0_3.0_1725413896680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_husseineid_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_husseineid_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_husseineid_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/HusseinEid/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_kialabs_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_kialabs_en.md
new file mode 100644
index 00000000000000..bd45476d3e946c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_kialabs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_kialabs DistilBertEmbeddings from kialabs
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_kialabs
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_kialabs` is a English model originally trained by kialabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kialabs_en_5.5.0_3.0_1725418356238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kialabs_en_5.5.0_3.0_1725418356238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_kialabs","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_kialabs","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_kialabs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kialabs/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_kialabs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_kialabs_pipeline_en.md
new file mode 100644
index 00000000000000..ce7b03d3c01ac4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_kialabs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_kialabs_pipeline pipeline DistilBertEmbeddings from kialabs
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_kialabs_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_kialabs_pipeline` is a English model originally trained by kialabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kialabs_pipeline_en_5.5.0_3.0_1725418369151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kialabs_pipeline_en_5.5.0_3.0_1725418369151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_kialabs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_kialabs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_kialabs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kialabs/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_matthewbk_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_matthewbk_en.md
new file mode 100644
index 00000000000000..e6a3f5db43be3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_matthewbk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_matthewbk DistilBertEmbeddings from matthewbk
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_matthewbk
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_matthewbk` is a English model originally trained by matthewbk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_matthewbk_en_5.5.0_3.0_1725418255254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_matthewbk_en_5.5.0_3.0_1725418255254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_matthewbk","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_matthewbk","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_matthewbk|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/matthewbk/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline_en.md
new file mode 100644
index 00000000000000..8f127b6c4fc383
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline pipeline DistilBertEmbeddings from matthewbk
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline` is a English model originally trained by matthewbk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline_en_5.5.0_3.0_1725418268518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline_en_5.5.0_3.0_1725418268518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_matthewbk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/matthewbk/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_minshengchan_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_minshengchan_en.md
new file mode 100644
index 00000000000000..f224c031390de1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_minshengchan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_minshengchan DistilBertEmbeddings from minshengchan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_minshengchan
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_minshengchan` is a English model originally trained by minshengchan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_minshengchan_en_5.5.0_3.0_1725414296583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_minshengchan_en_5.5.0_3.0_1725414296583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_minshengchan","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_minshengchan","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_minshengchan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/minshengchan/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline_en.md
new file mode 100644
index 00000000000000..9d4750d4bcf284
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline pipeline DistilBertEmbeddings from minshengchan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline` is a English model originally trained by minshengchan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline_en_5.5.0_3.0_1725414309871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline_en_5.5.0_3.0_1725414309871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_minshengchan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/minshengchan/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline_en.md
new file mode 100644
index 00000000000000..30177413bb1ee1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline pipeline DistilBertEmbeddings from phantatbach
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline` is a English model originally trained by phantatbach.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline_en_5.5.0_3.0_1725414198041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline_en_5.5.0_3.0_1725414198041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_phantatbach_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/phantatbach/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_r0in_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_r0in_pipeline_en.md
new file mode 100644
index 00000000000000..63dc34d4da216c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_r0in_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_r0in_pipeline pipeline DistilBertEmbeddings from r0in
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_r0in_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_r0in_pipeline` is a English model originally trained by r0in.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_r0in_pipeline_en_5.5.0_3.0_1725413783751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_r0in_pipeline_en_5.5.0_3.0_1725413783751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_r0in_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_r0in_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_r0in_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/r0in/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_rsffen_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_rsffen_en.md
new file mode 100644
index 00000000000000..03b6620c9acc36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_rsffen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_rsffen DistilBertEmbeddings from RSFfen
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_rsffen
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_rsffen` is a English model originally trained by RSFfen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rsffen_en_5.5.0_3.0_1725418454834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rsffen_en_5.5.0_3.0_1725418454834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_rsffen","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_rsffen","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_rsffen|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/RSFfen/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_rsffen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_rsffen_pipeline_en.md
new file mode 100644
index 00000000000000..565c5b341a5045
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_rsffen_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_rsffen_pipeline pipeline DistilBertEmbeddings from RSFfen
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_rsffen_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_rsffen_pipeline` is a English model originally trained by RSFfen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rsffen_pipeline_en_5.5.0_3.0_1725418468631.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rsffen_pipeline_en_5.5.0_3.0_1725418468631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_rsffen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_rsffen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_rsffen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/RSFfen/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sangwooj_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sangwooj_en.md
new file mode 100644
index 00000000000000..b4f34e2b6eb890
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sangwooj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sangwooj DistilBertEmbeddings from SangwooJ
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sangwooj
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sangwooj` is a English model originally trained by SangwooJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sangwooj_en_5.5.0_3.0_1725418232810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sangwooj_en_5.5.0_3.0_1725418232810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sangwooj","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sangwooj","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sangwooj|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/SangwooJ/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline_en.md
new file mode 100644
index 00000000000000..a103f0894c7e8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline pipeline DistilBertEmbeddings from SangwooJ
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline` is a English model originally trained by SangwooJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline_en_5.5.0_3.0_1725418246139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline_en_5.5.0_3.0_1725418246139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sangwooj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/SangwooJ/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sbulut_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sbulut_pipeline_en.md
new file mode 100644
index 00000000000000..0e84258de73d24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sbulut_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sbulut_pipeline pipeline DistilBertEmbeddings from sbulut
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sbulut_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sbulut_pipeline` is a English model originally trained by sbulut.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sbulut_pipeline_en_5.5.0_3.0_1725414416235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sbulut_pipeline_en_5.5.0_3.0_1725414416235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sbulut_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sbulut_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sbulut_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sbulut/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shahzebnaveed_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shahzebnaveed_en.md
new file mode 100644
index 00000000000000..72a15f56ccf2f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shahzebnaveed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_shahzebnaveed DistilBertEmbeddings from shahzebnaveed
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_shahzebnaveed
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_shahzebnaveed` is a English model originally trained by shahzebnaveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_shahzebnaveed_en_5.5.0_3.0_1725418132291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_shahzebnaveed_en_5.5.0_3.0_1725418132291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_shahzebnaveed","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_shahzebnaveed","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_shahzebnaveed|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/shahzebnaveed/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shradha01_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shradha01_en.md
new file mode 100644
index 00000000000000..d98b358e8a75a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shradha01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_shradha01 DistilBertEmbeddings from shradha01
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_shradha01
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_shradha01` is a English model originally trained by shradha01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_shradha01_en_5.5.0_3.0_1725414372533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_shradha01_en_5.5.0_3.0_1725414372533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_shradha01","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_shradha01","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_shradha01|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/shradha01/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shradha01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shradha01_pipeline_en.md
new file mode 100644
index 00000000000000..395aa72ae24526
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_shradha01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_shradha01_pipeline pipeline DistilBertEmbeddings from shradha01
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_shradha01_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_shradha01_pipeline` is a English model originally trained by shradha01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_shradha01_pipeline_en_5.5.0_3.0_1725414387018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_shradha01_pipeline_en_5.5.0_3.0_1725414387018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_shradha01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_shradha01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_shradha01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/shradha01/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sociedade_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sociedade_en.md
new file mode 100644
index 00000000000000..1263cf656c5f2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sociedade_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sociedade DistilBertEmbeddings from Sociedade
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sociedade
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sociedade` is a English model originally trained by Sociedade.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sociedade_en_5.5.0_3.0_1725418386476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sociedade_en_5.5.0_3.0_1725418386476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sociedade","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sociedade","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sociedade|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Sociedade/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sociedade_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sociedade_pipeline_en.md
new file mode 100644
index 00000000000000..829d51b455c8fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_sociedade_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sociedade_pipeline pipeline DistilBertEmbeddings from Sociedade
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sociedade_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sociedade_pipeline` is a English model originally trained by Sociedade.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sociedade_pipeline_en_5.5.0_3.0_1725418399293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sociedade_pipeline_en_5.5.0_3.0_1725418399293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sociedade_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_sociedade_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sociedade_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Sociedade/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_walterg777_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_walterg777_pipeline_en.md
new file mode 100644
index 00000000000000..6d62511e41f2d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_imdb_walterg777_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_walterg777_pipeline pipeline DistilBertEmbeddings from walterg777
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_walterg777_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_walterg777_pipeline` is a English model originally trained by walterg777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_walterg777_pipeline_en_5.5.0_3.0_1725418774709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_walterg777_pipeline_en_5.5.0_3.0_1725418774709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_walterg777_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_walterg777_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_walterg777_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/walterg777/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_masakhanenews_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_masakhanenews_pipeline_en.md
new file mode 100644
index 00000000000000..a72c4c18f22290
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_masakhanenews_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_masakhanenews_pipeline pipeline DistilBertEmbeddings from Dangurangu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_masakhanenews_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_masakhanenews_pipeline` is a English model originally trained by Dangurangu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_masakhanenews_pipeline_en_5.5.0_3.0_1725413783775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_masakhanenews_pipeline_en_5.5.0_3.0_1725413783775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_masakhanenews_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_masakhanenews_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_masakhanenews_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Dangurangu/distilbert-base-uncased-finetuned-masakhaneNews
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_cerastes_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_cerastes_en.md
new file mode 100644
index 00000000000000..3104337d1ae605
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_cerastes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_cerastes DistilBertForTokenClassification from Cerastes
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_cerastes
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_cerastes` is a English model originally trained by Cerastes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cerastes_en_5.5.0_3.0_1725460867138.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cerastes_en_5.5.0_3.0_1725460867138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_cerastes","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_cerastes", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_cerastes|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Cerastes/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_cerastes_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_cerastes_pipeline_en.md
new file mode 100644
index 00000000000000..0e76c39b5342fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_cerastes_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_cerastes_pipeline pipeline DistilBertForTokenClassification from Cerastes
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_cerastes_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_cerastes_pipeline` is a English model originally trained by Cerastes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cerastes_pipeline_en_5.5.0_3.0_1725460879573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cerastes_pipeline_en_5.5.0_3.0_1725460879573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_cerastes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_cerastes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_cerastes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Cerastes/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_emilyblah_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_emilyblah_pipeline_en.md
new file mode 100644
index 00000000000000..d146eedacad128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_emilyblah_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_emilyblah_pipeline pipeline DistilBertForTokenClassification from emilyblah
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_emilyblah_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_emilyblah_pipeline` is a English model originally trained by emilyblah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_emilyblah_pipeline_en_5.5.0_3.0_1725460571569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_emilyblah_pipeline_en_5.5.0_3.0_1725460571569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_emilyblah_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_emilyblah_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_emilyblah_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/emilyblah/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_finer_139_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_finer_139_en.md
new file mode 100644
index 00000000000000..5f3d0432e395ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_finer_139_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_finer_139 DistilBertForTokenClassification from OlesB
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_finer_139
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_finer_139` is a English model originally trained by OlesB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_finer_139_en_5.5.0_3.0_1725460349290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_finer_139_en_5.5.0_3.0_1725460349290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_finer_139","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_finer_139", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_finer_139|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/OlesB/distilbert-base-uncased-finetuned-ner_finer_139
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_finer_139_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_finer_139_pipeline_en.md
new file mode 100644
index 00000000000000..fcada0ba2b12c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_finer_139_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_finer_139_pipeline pipeline DistilBertForTokenClassification from OlesB
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_finer_139_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_finer_139_pipeline` is a English model originally trained by OlesB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_finer_139_pipeline_en_5.5.0_3.0_1725460363892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_finer_139_pipeline_en_5.5.0_3.0_1725460363892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_finer_139_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_finer_139_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_finer_139_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/OlesB/distilbert-base-uncased-finetuned-ner_finer_139
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_layath_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_layath_pipeline_en.md
new file mode 100644
index 00000000000000..ff007e4f20eddb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_layath_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_layath_pipeline pipeline DistilBertForTokenClassification from layath
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_layath_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_layath_pipeline` is a English model originally trained by layath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_layath_pipeline_en_5.5.0_3.0_1725476182294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_layath_pipeline_en_5.5.0_3.0_1725476182294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_layath_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_layath_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_layath_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/layath/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_misterstino_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_misterstino_pipeline_en.md
new file mode 100644
index 00000000000000..1271c078e57149
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_misterstino_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_misterstino_pipeline pipeline DistilBertForTokenClassification from MisterStino
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_misterstino_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_misterstino_pipeline` is a English model originally trained by MisterStino.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_misterstino_pipeline_en_5.5.0_3.0_1725448219202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_misterstino_pipeline_en_5.5.0_3.0_1725448219202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_misterstino_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_misterstino_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_misterstino_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MisterStino/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_mrk4863_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_mrk4863_en.md
new file mode 100644
index 00000000000000..cc502986acb6a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_mrk4863_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_mrk4863 DistilBertForTokenClassification from MRK4863
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_mrk4863
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_mrk4863` is a English model originally trained by MRK4863.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_mrk4863_en_5.5.0_3.0_1725492437456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_mrk4863_en_5.5.0_3.0_1725492437456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_mrk4863","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_mrk4863", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_mrk4863|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MRK4863/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_mrk4863_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_mrk4863_pipeline_en.md
new file mode 100644
index 00000000000000..ba0802fd17a251
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_mrk4863_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_mrk4863_pipeline pipeline DistilBertForTokenClassification from MRK4863
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_mrk4863_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_mrk4863_pipeline` is a English model originally trained by MRK4863.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_mrk4863_pipeline_en_5.5.0_3.0_1725492457321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_mrk4863_pipeline_en_5.5.0_3.0_1725492457321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_mrk4863_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_mrk4863_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_mrk4863_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MRK4863/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_polo42_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_polo42_en.md
new file mode 100644
index 00000000000000..0454c0a7e2f20d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_polo42_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_polo42 DistilBertForTokenClassification from polo42
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_polo42
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_polo42` is a English model originally trained by polo42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_polo42_en_5.5.0_3.0_1725448412260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_polo42_en_5.5.0_3.0_1725448412260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_polo42","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_polo42", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_polo42|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/polo42/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_soniquentin_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_soniquentin_en.md
new file mode 100644
index 00000000000000..9e23678517207a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_soniquentin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_soniquentin DistilBertForTokenClassification from soniquentin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_soniquentin
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_soniquentin` is a English model originally trained by soniquentin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_soniquentin_en_5.5.0_3.0_1725460999551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_soniquentin_en_5.5.0_3.0_1725460999551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_soniquentin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_soniquentin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_soniquentin|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|377.1 MB|
+
+## References
+
+https://huggingface.co/soniquentin/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_soniquentin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_soniquentin_pipeline_en.md
new file mode 100644
index 00000000000000..aa73a6a4b240fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_soniquentin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_soniquentin_pipeline pipeline DistilBertForTokenClassification from soniquentin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_soniquentin_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_soniquentin_pipeline` is a English model originally trained by soniquentin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_soniquentin_pipeline_en_5.5.0_3.0_1725461019056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_soniquentin_pipeline_en_5.5.0_3.0_1725461019056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_soniquentin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_soniquentin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_soniquentin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|377.1 MB|
+
+## References
+
+https://huggingface.co/soniquentin/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vnear_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vnear_pipeline_en.md
new file mode 100644
index 00000000000000..66de550a22e0bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vnear_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_vnear_pipeline pipeline DistilBertForTokenClassification from VNEar
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_vnear_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_vnear_pipeline` is a English model originally trained by VNEar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_vnear_pipeline_en_5.5.0_3.0_1725448912212.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_vnear_pipeline_en_5.5.0_3.0_1725448912212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_vnear_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_vnear_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_vnear_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/VNEar/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vwslz_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vwslz_en.md
new file mode 100644
index 00000000000000..a7178c485f340b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vwslz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_vwslz DistilBertForTokenClassification from vwslz
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_vwslz
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_vwslz` is a English model originally trained by vwslz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_vwslz_en_5.5.0_3.0_1725476254891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_vwslz_en_5.5.0_3.0_1725476254891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_vwslz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_vwslz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_vwslz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/vwslz/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vwslz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vwslz_pipeline_en.md
new file mode 100644
index 00000000000000..2e45b2d57c091a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_vwslz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_vwslz_pipeline pipeline DistilBertForTokenClassification from vwslz
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_vwslz_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_vwslz_pipeline` is a English model originally trained by vwslz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_vwslz_pipeline_en_5.5.0_3.0_1725476267360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_vwslz_pipeline_en_5.5.0_3.0_1725476267360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_vwslz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_vwslz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_vwslz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/vwslz/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_zy666_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_zy666_en.md
new file mode 100644
index 00000000000000..62c6e2aa830011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_zy666_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_zy666 DistilBertForTokenClassification from zy666
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_zy666
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_zy666` is a English model originally trained by zy666.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_zy666_en_5.5.0_3.0_1725476346447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_zy666_en_5.5.0_3.0_1725476346447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_zy666","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_zy666", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_zy666|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/zy666/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_news_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_news_en.md
new file mode 100644
index 00000000000000..7801106f344ef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_news DistilBertEmbeddings from brownnie
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_news
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_news` is a English model originally trained by brownnie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_news_en_5.5.0_3.0_1725418661166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_news_en_5.5.0_3.0_1725418661166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_news","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_news","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_news|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/brownnie/distilbert-base-uncased-finetuned-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_res_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_res_en.md
new file mode 100644
index 00000000000000..0cc0c1f48a3f2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_res_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_res DistilBertEmbeddings from rohbro
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_res
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_res` is a English model originally trained by rohbro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_res_en_5.5.0_3.0_1725418173060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_res_en_5.5.0_3.0_1725418173060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_res","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_res","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_res|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rohbro/distilbert-base-uncased-finetuned-res
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_res_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_res_pipeline_en.md
new file mode 100644
index 00000000000000..40239b8374ff0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_res_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_res_pipeline pipeline DistilBertEmbeddings from rohbro
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_res_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_res_pipeline` is a English model originally trained by rohbro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_res_pipeline_en_5.5.0_3.0_1725418185905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_res_pipeline_en_5.5.0_3.0_1725418185905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_res_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_res_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_res_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rohbro/distilbert-base-uncased-finetuned-res
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_sayula_popoluca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_sayula_popoluca_pipeline_en.md
new file mode 100644
index 00000000000000..e09e10d96318f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_sayula_popoluca_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_sayula_popoluca_pipeline pipeline DistilBertForTokenClassification from Prince6
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_sayula_popoluca_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_sayula_popoluca_pipeline` is a English model originally trained by Prince6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sayula_popoluca_pipeline_en_5.5.0_3.0_1725460683891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sayula_popoluca_pipeline_en_5.5.0_3.0_1725460683891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_sayula_popoluca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_sayula_popoluca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Prince6/distilbert-base-uncased-finetuned-pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_d5716d28_sonny_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_d5716d28_sonny_en.md
new file mode 100644
index 00000000000000..d87bdc265f161c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_d5716d28_sonny_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_sonny DistilBertEmbeddings from Sonny
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_sonny
+date: 2024-09-04
+tags: [distilbert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_sonny` is a English model originally trained by Sonny.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_sonny_en_5.5.0_3.0_1725465698852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_sonny_en_5.5.0_3.0_1725465698852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_squad_d5716d28_sonny","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = DistilBertEmbeddings 
+    .pretrained("distilbert_base_uncased_finetuned_squad_d5716d28_sonny", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_sonny|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/Sonny/distilbert-base-uncased-finetuned-squad-d5716d28
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline_en.md
new file mode 100644
index 00000000000000..4c0cb64fd6b401
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline pipeline DistilBertForQuestionAnswering from Sonny
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline` is a English model originally trained by Sonny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline_en_5.5.0_3.0_1725465710784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline_en_5.5.0_3.0_1725465710784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_sonny_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Sonny/distilbert-base-uncased-finetuned-squad-d5716d28
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline_en.md
new file mode 100644
index 00000000000000..46cf82bf522191
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline pipeline DistilBertForQuestionAnswering from tanishq1420
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline` is a English model originally trained by tanishq1420.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline_en_5.5.0_3.0_1725465431877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline_en_5.5.0_3.0_1725465431877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_tanishq1420_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/tanishq1420/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_who_does_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_who_does_en.md
new file mode 100644
index 00000000000000..c47e61f7af0963
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_who_does_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_who_does DistilBertForQuestionAnswering from who-does
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_who_does
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_who_does` is a English model originally trained by who-does.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_who_does_en_5.5.0_3.0_1725465783353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_who_does_en_5.5.0_3.0_1725465783353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_who_does","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_who_does", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_who_does|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/who-does/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_who_does_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_who_does_pipeline_en.md
new file mode 100644
index 00000000000000..3e404e40522c57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_who_does_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_who_does_pipeline pipeline DistilBertForQuestionAnswering from who-does
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_who_does_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_who_does_pipeline` is a English model originally trained by who-does.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_who_does_pipeline_en_5.5.0_3.0_1725465795829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_who_does_pipeline_en_5.5.0_3.0_1725465795829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_who_does_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_who_does_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_who_does_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/who-does/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_yashaswi0506_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_yashaswi0506_en.md
new file mode 100644
index 00000000000000..5f0c1f75d318c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_squad_yashaswi0506_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_yashaswi0506 DistilBertForQuestionAnswering from Yashaswi0506
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_yashaswi0506
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_yashaswi0506` is a English model originally trained by Yashaswi0506.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_yashaswi0506_en_5.5.0_3.0_1725465682204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_yashaswi0506_en_5.5.0_3.0_1725465682204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_yashaswi0506","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_yashaswi0506", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_yashaswi0506|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Yashaswi0506/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_streamers_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_streamers_en.md
new file mode 100644
index 00000000000000..7ef9f340f0350a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_streamers_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_streamers DistilBertEmbeddings from muhbdeir
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_streamers
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_streamers` is a English model originally trained by muhbdeir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_streamers_en_5.5.0_3.0_1725414097479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_streamers_en_5.5.0_3.0_1725414097479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_streamers","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_streamers","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_streamers|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/muhbdeir/distilbert-base-uncased-finetuned-streamers
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline_en.md
new file mode 100644
index 00000000000000..5d0bf108cb1ade
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline pipeline DistilBertForSequenceClassification from bhadresh-savani
+author: John Snow Labs
+name: distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline` is a English model originally trained by bhadresh-savani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline_en_5.5.0_3.0_1725490176765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline_en_5.5.0_3.0_1725490176765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_go_emotion_bhadresh_savani_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/bhadresh-savani/distilbert-base-uncased-go-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_mluonium_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_mluonium_en.md
new file mode 100644
index 00000000000000..0ddc017284eaca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_mluonium_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_mluonium DistilBertForTokenClassification from mluonium
+author: John Snow Labs
+name: distilbert_base_uncased_mluonium
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_mluonium` is a English model originally trained by mluonium.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_mluonium_en_5.5.0_3.0_1725460993218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_mluonium_en_5.5.0_3.0_1725460993218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_mluonium","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_mluonium", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_mluonium|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/mluonium/distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_mnli_textattack_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_mnli_textattack_en.md
new file mode 100644
index 00000000000000..d1589b8a9f1f6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_mnli_textattack_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_mnli_textattack DistilBertForSequenceClassification from textattack
+author: John Snow Labs
+name: distilbert_base_uncased_mnli_textattack
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_mnli_textattack` is a English model originally trained by textattack.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_mnli_textattack_en_5.5.0_3.0_1725489511201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_mnli_textattack_en_5.5.0_3.0_1725489511201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_mnli_textattack","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_mnli_textattack", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_mnli_textattack|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/textattack/distilbert-base-uncased-MNLI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_en.md
new file mode 100644
index 00000000000000..ffe85aca9bfd50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_ner_invoicesendername_all_inv_20_12 DistilBertForTokenClassification from Lilya
+author: John Snow Labs
+name: distilbert_base_uncased_ner_invoicesendername_all_inv_20_12
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ner_invoicesendername_all_inv_20_12` is a English model originally trained by Lilya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_en_5.5.0_3.0_1725448454844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_en_5.5.0_3.0_1725448454844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_ner_invoicesendername_all_inv_20_12","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_ner_invoicesendername_all_inv_20_12", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ner_invoicesendername_all_inv_20_12|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Lilya/distilbert-base-uncased-ner-invoiceSenderName_all_inv_20_12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline_en.md
new file mode 100644
index 00000000000000..598b64d510c5b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline pipeline DistilBertForTokenClassification from Lilya
+author: John Snow Labs
+name: distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline` is a English model originally trained by Lilya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline_en_5.5.0_3.0_1725448467354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline_en_5.5.0_3.0_1725448467354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ner_invoicesendername_all_inv_20_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Lilya/distilbert-base-uncased-ner-invoiceSenderName_all_inv_20_12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline_en.md
new file mode 100644
index 00000000000000..2ff1766ea30929
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline pipeline DistilBertForTokenClassification from bozhidara-pesheva
+author: John Snow Labs
+name: distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline` is a English model originally trained by bozhidara-pesheva.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline_en_5.5.0_3.0_1725448515491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline_en_5.5.0_3.0_1725448515491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_norwegian_perturb_bozhidara_pesheva_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/bozhidara-pesheva/distilbert-base-uncased-no-perturb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ww_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ww_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..d5ed9e6969fbf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ww_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_ww_finetuned_imdb DistilBertEmbeddings from keylazy
+author: John Snow Labs
+name: distilbert_base_uncased_ww_finetuned_imdb
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ww_finetuned_imdb` is a English model originally trained by keylazy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ww_finetuned_imdb_en_5.5.0_3.0_1725414457668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ww_finetuned_imdb_en_5.5.0_3.0_1725414457668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_ww_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_ww_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ww_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/keylazy/distilbert-base-uncased-ww-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ww_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ww_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..8b6e18abf76d85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_ww_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_ww_finetuned_imdb_pipeline pipeline DistilBertEmbeddings from keylazy
+author: John Snow Labs
+name: distilbert_base_uncased_ww_finetuned_imdb_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ww_finetuned_imdb_pipeline` is a English model originally trained by keylazy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ww_finetuned_imdb_pipeline_en_5.5.0_3.0_1725414470472.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ww_finetuned_imdb_pipeline_en_5.5.0_3.0_1725414470472.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_ww_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_ww_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ww_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/keylazy/distilbert-base-uncased-ww-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_wwm_finetuned_imdb_accelerate_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_wwm_finetuned_imdb_accelerate_en.md
new file mode 100644
index 00000000000000..c77f6d7853c931
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_wwm_finetuned_imdb_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_wwm_finetuned_imdb_accelerate DistilBertEmbeddings from alex-atelo
+author: John Snow Labs
+name: distilbert_base_uncased_wwm_finetuned_imdb_accelerate
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_wwm_finetuned_imdb_accelerate` is a English model originally trained by alex-atelo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_wwm_finetuned_imdb_accelerate_en_5.5.0_3.0_1725418632259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_wwm_finetuned_imdb_accelerate_en_5.5.0_3.0_1725418632259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_wwm_finetuned_imdb_accelerate","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_wwm_finetuned_imdb_accelerate","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_wwm_finetuned_imdb_accelerate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/alex-atelo/distilbert-base-uncased-wwm-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_emotion_neelams_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_emotion_neelams_en.md
new file mode 100644
index 00000000000000..9901dbb2dbb156
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_emotion_neelams_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_emotion_neelams DistilBertForSequenceClassification from neelams
+author: John Snow Labs
+name: distilbert_emotion_neelams
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_neelams` is a English model originally trained by neelams.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_neelams_en_5.5.0_3.0_1725490342386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_neelams_en_5.5.0_3.0_1725490342386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_emotion_neelams","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_emotion_neelams", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_neelams|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/neelams/distilbert-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_emotion_neelams_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_emotion_neelams_pipeline_en.md
new file mode 100644
index 00000000000000..a5a031d31a6104
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_emotion_neelams_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_emotion_neelams_pipeline pipeline DistilBertForSequenceClassification from neelams
+author: John Snow Labs
+name: distilbert_emotion_neelams_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_neelams_pipeline` is a English model originally trained by neelams.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_neelams_pipeline_en_5.5.0_3.0_1725490353949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_neelams_pipeline_en_5.5.0_3.0_1725490353949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_emotion_neelams_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_emotion_neelams_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_neelams_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/neelams/distilbert-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_finer_4_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_finer_4_v2_en.md
new file mode 100644
index 00000000000000..97a29026ad1c2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_finer_4_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_finer_4_v2 DistilBertForTokenClassification from ShadyML
+author: John Snow Labs
+name: distilbert_finetuned_finer_4_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_finer_4_v2` is a English model originally trained by ShadyML.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_finer_4_v2_en_5.5.0_3.0_1725460903468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_finer_4_v2_en_5.5.0_3.0_1725460903468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_finetuned_finer_4_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_finer_4_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_finer_4_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ShadyML/distilbert-finetuned-finer-4-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_sayula_popoluca_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_sayula_popoluca_en.md
new file mode 100644
index 00000000000000..42967ab67152db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_sayula_popoluca_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_sayula_popoluca DistilBertForTokenClassification from amanpatkar
+author: John Snow Labs
+name: distilbert_finetuned_sayula_popoluca
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_sayula_popoluca` is a English model originally trained by amanpatkar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_sayula_popoluca_en_5.5.0_3.0_1725460780341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_sayula_popoluca_en_5.5.0_3.0_1725460780341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_finetuned_sayula_popoluca","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_sayula_popoluca", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_sayula_popoluca|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/amanpatkar/distilbert-finetuned-pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_squadv2_nampham1106_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_squadv2_nampham1106_en.md
new file mode 100644
index 00000000000000..0d0c58c0018af3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_squadv2_nampham1106_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_finetuned_squadv2_nampham1106 DistilBertForQuestionAnswering from nampham1106
+author: John Snow Labs
+name: distilbert_finetuned_squadv2_nampham1106
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squadv2_nampham1106` is a English model originally trained by nampham1106.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_nampham1106_en_5.5.0_3.0_1725465986411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_nampham1106_en_5.5.0_3.0_1725465986411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squadv2_nampham1106","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squadv2_nampham1106", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squadv2_nampham1106|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/nampham1106/distilbert-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_squadv2_ntn0301_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_squadv2_ntn0301_en.md
new file mode 100644
index 00000000000000..7f07c6d66558bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_finetuned_squadv2_ntn0301_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_finetuned_squadv2_ntn0301 DistilBertForQuestionAnswering from NTN0301
+author: John Snow Labs
+name: distilbert_finetuned_squadv2_ntn0301
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squadv2_ntn0301` is a English model originally trained by NTN0301.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_ntn0301_en_5.5.0_3.0_1725465289217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_ntn0301_en_5.5.0_3.0_1725465289217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squadv2_ntn0301","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squadv2_ntn0301", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squadv2_ntn0301|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/NTN0301/distilbert-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_hera_synthetic_pretrain_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_hera_synthetic_pretrain_en.md
new file mode 100644
index 00000000000000..a6f56750519138
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_hera_synthetic_pretrain_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_hera_synthetic_pretrain DistilBertForTokenClassification from mpajas
+author: John Snow Labs
+name: distilbert_hera_synthetic_pretrain
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_hera_synthetic_pretrain` is a English model originally trained by mpajas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_hera_synthetic_pretrain_en_5.5.0_3.0_1725476382693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_hera_synthetic_pretrain_en_5.5.0_3.0_1725476382693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_hera_synthetic_pretrain","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_hera_synthetic_pretrain", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_hera_synthetic_pretrain|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/mpajas/distilbert-hera-synthetic-pretrain
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_masking_heaps_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_masking_heaps_pipeline_en.md
new file mode 100644
index 00000000000000..330a0a3b100eb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_masking_heaps_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_masking_heaps_pipeline pipeline DistilBertEmbeddings from johannes-garstenauer
+author: John Snow Labs
+name: distilbert_masking_heaps_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_masking_heaps_pipeline` is a English model originally trained by johannes-garstenauer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_masking_heaps_pipeline_en_5.5.0_3.0_1725413905516.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_masking_heaps_pipeline_en_5.5.0_3.0_1725413905516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_masking_heaps_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_masking_heaps_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_masking_heaps_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/johannes-garstenauer/distilbert_masking_heaps
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_multilingual_cased_lft_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_multilingual_cased_lft_pipeline_xx.md
new file mode 100644
index 00000000000000..f86bcea3d41c83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_multilingual_cased_lft_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_multilingual_cased_lft_pipeline pipeline DistilBertForTokenClassification from praysimanjuntak
+author: John Snow Labs
+name: distilbert_multilingual_cased_lft_pipeline
+date: 2024-09-04
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_multilingual_cased_lft_pipeline` is a Multilingual model originally trained by praysimanjuntak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_multilingual_cased_lft_pipeline_xx_5.5.0_3.0_1725461229790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_multilingual_cased_lft_pipeline_xx_5.5.0_3.0_1725461229790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_multilingual_cased_lft_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_multilingual_cased_lft_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_multilingual_cased_lft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/praysimanjuntak/distilbert-multilingual-cased-lft
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_furniture_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_furniture_en.md
new file mode 100644
index 00000000000000..55ad38d80cf128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_furniture_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_furniture DistilBertForTokenClassification from TimoteiB
+author: John Snow Labs
+name: distilbert_ner_furniture
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_furniture` is a English model originally trained by TimoteiB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_furniture_en_5.5.0_3.0_1725476001629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_furniture_en_5.5.0_3.0_1725476001629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_furniture","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_furniture", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_furniture|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/TimoteiB/DistilBERT_NER_furniture
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_furniture_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_furniture_pipeline_en.md
new file mode 100644
index 00000000000000..569663e13e3ed4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_furniture_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_furniture_pipeline pipeline DistilBertForTokenClassification from TimoteiB
+author: John Snow Labs
+name: distilbert_ner_furniture_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_furniture_pipeline` is a English model originally trained by TimoteiB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_furniture_pipeline_en_5.5.0_3.0_1725476014565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_furniture_pipeline_en_5.5.0_3.0_1725476014565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_furniture_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_furniture_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_furniture_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/TimoteiB/DistilBERT_NER_furniture
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_jakka_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_jakka_en.md
new file mode 100644
index 00000000000000..863c95bfce6b51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_jakka_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_jakka DistilBertForTokenClassification from jakka
+author: John Snow Labs
+name: distilbert_ner_jakka
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_jakka` is a English model originally trained by jakka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_jakka_en_5.5.0_3.0_1725448667436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_jakka_en_5.5.0_3.0_1725448667436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_jakka","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_jakka", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_jakka|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jakka/distilbert_ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_jakka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_jakka_pipeline_en.md
new file mode 100644
index 00000000000000..357866a6e0f36b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_ner_jakka_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_jakka_pipeline pipeline DistilBertForTokenClassification from jakka
+author: John Snow Labs
+name: distilbert_ner_jakka_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_jakka_pipeline` is a English model originally trained by jakka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_jakka_pipeline_en_5.5.0_3.0_1725448680416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_jakka_pipeline_en_5.5.0_3.0_1725448680416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_jakka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_jakka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_jakka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jakka/distilbert_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_BERT_ClinicalQA_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_BERT_ClinicalQA_en.md
new file mode 100644
index 00000000000000..cef00915a322df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_BERT_ClinicalQA_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English DistilBertForQuestionAnswering model (from exafluence)
+author: John Snow Labs
+name: distilbert_qa_BERT_ClinicalQA
+date: 2024-09-04
+tags: [en, open_source, distilbert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `BERT-ClinicalQA` is a English model originally trained by `exafluence`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qa_BERT_ClinicalQA_en_5.5.0_3.0_1725465985760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_BERT_ClinicalQA_en_5.5.0_3.0_1725465985760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_qa_BERT_ClinicalQA","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = DistilBertForQuestionAnswering.pretrained("distilbert_qa_BERT_ClinicalQA","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.clinical.distil_bert").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_BERT_ClinicalQA|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/exafluence/BERT-ClinicalQA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_COVID_DistilBERTc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_COVID_DistilBERTc_pipeline_en.md
new file mode 100644
index 00000000000000..5fe4d2ab842204
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_COVID_DistilBERTc_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_qa_COVID_DistilBERTc_pipeline pipeline DistilBertForQuestionAnswering from rahulkuruvilla
+author: John Snow Labs
+name: distilbert_qa_COVID_DistilBERTc_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_qa_COVID_DistilBERTc_pipeline` is a English model originally trained by rahulkuruvilla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qa_COVID_DistilBERTc_pipeline_en_5.5.0_3.0_1725465523344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_COVID_DistilBERTc_pipeline_en_5.5.0_3.0_1725465523344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_qa_COVID_DistilBERTc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_qa_COVID_DistilBERTc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_COVID_DistilBERTc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rahulkuruvilla/COVID-DistilBERTc
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_checkpoint_500_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_checkpoint_500_finetuned_squad_en.md
new file mode 100644
index 00000000000000..7a90ffefe05334
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_checkpoint_500_finetuned_squad_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English DistilBertForQuestionAnswering Cased model (from tabo)
+author: John Snow Labs
+name: distilbert_qa_checkpoint_500_finetuned_squad
+date: 2024-09-04
+tags: [en, open_source, distilbert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `checkpoint-500-finetuned-squad` is a English model originally trained by `tabo`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qa_checkpoint_500_finetuned_squad_en_5.5.0_3.0_1725465617647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_checkpoint_500_finetuned_squad_en_5.5.0_3.0_1725465617647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = DistilBertForQuestionAnswering.pretrained("distilbert_qa_checkpoint_500_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = DistilBertForQuestionAnswering.pretrained("distilbert_qa_checkpoint_500_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.distil_bert").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_checkpoint_500_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/tabo/checkpoint-500-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_distilBertABSA_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_distilBertABSA_en.md
new file mode 100644
index 00000000000000..6e42f584cd93bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_distilBertABSA_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English DistilBertForQuestionAnswering model (from LucasS)
+author: John Snow Labs
+name: distilbert_qa_distilBertABSA
+date: 2024-09-04
+tags: [en, open_source, distilbert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `distilBertABSA` is a English model originally trained by `LucasS`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qa_distilBertABSA_en_5.5.0_3.0_1725465513786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_distilBertABSA_en_5.5.0_3.0_1725465513786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_qa_distilBertABSA","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = DistilBertForQuestionAnswering.pretrained("distilbert_qa_distilBertABSA","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.distil_bert.by_LucasS").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_distilBertABSA|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/LucasS/distilBertABSA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_eurosmart_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_eurosmart_pipeline_en.md
new file mode 100644
index 00000000000000..a4435bc4028339
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_eurosmart_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_qa_eurosmart_pipeline pipeline DistilBertForQuestionAnswering from Eurosmart
+author: John Snow Labs
+name: distilbert_qa_eurosmart_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_qa_eurosmart_pipeline` is a English model originally trained by Eurosmart.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qa_eurosmart_pipeline_en_5.5.0_3.0_1725465888006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_eurosmart_pipeline_en_5.5.0_3.0_1725465888006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_qa_eurosmart_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_qa_eurosmart_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_eurosmart_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Eurosmart/distilbert-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_sdsqna_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_sdsqna_en.md
new file mode 100644
index 00000000000000..229f206a701acb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_sdsqna_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English DistilBertForQuestionAnswering Cased model (from ajaypyatha)
+author: John Snow Labs
+name: distilbert_qa_sdsqna
+date: 2024-09-04
+tags: [en, open_source, distilbert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `sdsqna` is a English model originally trained by `ajaypyatha`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qa_sdsqna_en_5.5.0_3.0_1725465909918.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_sdsqna_en_5.5.0_3.0_1725465909918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = DistilBertForQuestionAnswering.pretrained("distilbert_qa_sdsqna","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = DistilBertForQuestionAnswering.pretrained("distilbert_qa_sdsqna","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.distil_bert.by_ajaypyatha").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_sdsqna|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/ajaypyatha/sdsqna
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_sdsqna_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_sdsqna_pipeline_en.md
new file mode 100644
index 00000000000000..0e4a317ab5c85b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_qa_sdsqna_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_qa_sdsqna_pipeline pipeline DistilBertForQuestionAnswering from ajaypyatha
+author: John Snow Labs
+name: distilbert_qa_sdsqna_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_qa_sdsqna_pipeline` is a English model originally trained by ajaypyatha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qa_sdsqna_pipeline_en_5.5.0_3.0_1725465921710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_sdsqna_pipeline_en_5.5.0_3.0_1725465921710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_qa_sdsqna_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_qa_sdsqna_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_sdsqna_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ajaypyatha/sdsqna
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_en.md
new file mode 100644
index 00000000000000..5639c37d018dec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil DistilBertForSequenceClassification from CouchCat
+author: John Snow Labs
+name: distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil` is a English model originally trained by CouchCat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_en_5.5.0_3.0_1725489788470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_en_5.5.0_3.0_1725489788470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/CouchCat/ma_sa_v7_distil
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline_en.md
new file mode 100644
index 00000000000000..7f799d913618a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline pipeline DistilBertForSequenceClassification from CouchCat
+author: John Snow Labs
+name: distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline` is a English model originally trained by CouchCat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline_en_5.5.0_3.0_1725489800824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline_en_5.5.0_3.0_1725489800824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sequence_classifier_ma_sanskrit_saskta_v7_distil_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/CouchCat/ma_sa_v7_distil
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_tuned_4labels_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_tuned_4labels_en.md
new file mode 100644
index 00000000000000..dee5d4c013b233
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_tuned_4labels_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_tuned_4labels DistilBertForTokenClassification from dayannex
+author: John Snow Labs
+name: distilbert_tuned_4labels
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_tuned_4labels` is a English model originally trained by dayannex.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_tuned_4labels_en_5.5.0_3.0_1725448604931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_tuned_4labels_en_5.5.0_3.0_1725448604931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_tuned_4labels","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_tuned_4labels", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_tuned_4labels|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/dayannex/distilbert-tuned-4labels
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_word2vec_256k_mlm_best_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_word2vec_256k_mlm_best_en.md
new file mode 100644
index 00000000000000..5d42ab53b18639
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_word2vec_256k_mlm_best_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_word2vec_256k_mlm_best DistilBertEmbeddings from vocab-transformers
+author: John Snow Labs
+name: distilbert_word2vec_256k_mlm_best
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_word2vec_256k_mlm_best` is a English model originally trained by vocab-transformers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_word2vec_256k_mlm_best_en_5.5.0_3.0_1725413828962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_word2vec_256k_mlm_best_en_5.5.0_3.0_1725413828962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_word2vec_256k_mlm_best","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_word2vec_256k_mlm_best","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_word2vec_256k_mlm_best|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|902.0 MB|
+
+## References
+
+https://huggingface.co/vocab-transformers/distilbert-word2vec_256k-MLM_best
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilcamembert_base_fr.md b/docs/_posts/ahmedlone127/2024-09-04-distilcamembert_base_fr.md
new file mode 100644
index 00000000000000..4796c8d276feeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilcamembert_base_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French distilcamembert_base CamemBertEmbeddings from cmarkea
+author: John Snow Labs
+name: distilcamembert_base
+date: 2024-09-04
+tags: [fr, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilcamembert_base` is a French model originally trained by cmarkea.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilcamembert_base_fr_5.5.0_3.0_1725442161560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilcamembert_base_fr_5.5.0_3.0_1725442161560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("distilcamembert_base","fr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("distilcamembert_base","fr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilcamembert_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|fr|
+|Size:|253.5 MB|
+
+## References
+
+https://huggingface.co/cmarkea/distilcamembert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distillbert_political_finetune_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distillbert_political_finetune_pipeline_en.md
new file mode 100644
index 00000000000000..7560e1f3556935
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distillbert_political_finetune_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distillbert_political_finetune_pipeline pipeline DistilBertForSequenceClassification from harshal-11
+author: John Snow Labs
+name: distillbert_political_finetune_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_political_finetune_pipeline` is a English model originally trained by harshal-11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_political_finetune_pipeline_en_5.5.0_3.0_1725489808009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_political_finetune_pipeline_en_5.5.0_3.0_1725489808009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distillbert_political_finetune_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distillbert_political_finetune_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_political_finetune_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/harshal-11/DistillBERT-Political-Finetune
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_catalan_v2_pipeline_ca.md b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_catalan_v2_pipeline_ca.md
new file mode 100644
index 00000000000000..29973b6a121cf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_catalan_v2_pipeline_ca.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Catalan, Valencian distilroberta_base_catalan_v2_pipeline pipeline RoBertaEmbeddings from projecte-aina
+author: John Snow Labs
+name: distilroberta_base_catalan_v2_pipeline
+date: 2024-09-04
+tags: [ca, open_source, pipeline, onnx]
+task: Embeddings
+language: ca
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_catalan_v2_pipeline` is a Catalan, Valencian model originally trained by projecte-aina.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_catalan_v2_pipeline_ca_5.5.0_3.0_1725412529024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_catalan_v2_pipeline_ca_5.5.0_3.0_1725412529024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_catalan_v2_pipeline", lang = "ca")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_catalan_v2_pipeline", lang = "ca")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_catalan_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ca|
+|Size:|304.1 MB|
+
+## References
+
+https://huggingface.co/projecte-aina/distilroberta-base-ca-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_cnn_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_cnn_en.md
new file mode 100644
index 00000000000000..84b7e53a4b241b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_cnn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_cnn RoBertaForSequenceClassification from AyoubChLin
+author: John Snow Labs
+name: distilroberta_base_cnn
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_cnn` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_cnn_en_5.5.0_3.0_1725486151506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_cnn_en_5.5.0_3.0_1725486151506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilroberta_base_cnn","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_cnn", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_cnn|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|309.0 MB|
+
+## References
+
+https://huggingface.co/AyoubChLin/distilroberta-base-CNN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_cnn_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_cnn_pipeline_en.md
new file mode 100644
index 00000000000000..c635a24dbd439d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_cnn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_cnn_pipeline pipeline RoBertaForSequenceClassification from AyoubChLin
+author: John Snow Labs
+name: distilroberta_base_cnn_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_cnn_pipeline` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_cnn_pipeline_en_5.5.0_3.0_1725486166171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_cnn_pipeline_en_5.5.0_3.0_1725486166171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_cnn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_cnn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_cnn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.0 MB|
+
+## References
+
+https://huggingface.co/AyoubChLin/distilroberta-base-CNN
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_finetuned_wikitext2_squad_qa_wandb2_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_finetuned_wikitext2_squad_qa_wandb2_en.md
new file mode 100644
index 00000000000000..cafcf22664c3c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_finetuned_wikitext2_squad_qa_wandb2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_wikitext2_squad_qa_wandb2 RoBertaForQuestionAnswering from Madhana
+author: John Snow Labs
+name: distilroberta_base_finetuned_wikitext2_squad_qa_wandb2
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_wikitext2_squad_qa_wandb2` is a English model originally trained by Madhana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_wikitext2_squad_qa_wandb2_en_5.5.0_3.0_1725479509493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_wikitext2_squad_qa_wandb2_en_5.5.0_3.0_1725479509493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("distilroberta_base_finetuned_wikitext2_squad_qa_wandb2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("distilroberta_base_finetuned_wikitext2_squad_qa_wandb2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_wikitext2_squad_qa_wandb2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/Madhana/distilroberta-base-finetuned-wikitext2-SQuAD-qa-WandB2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline_en.md
new file mode 100644
index 00000000000000..667202341d8f3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline pipeline RoBertaForSequenceClassification from Kayvane
+author: John Snow Labs
+name: distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline` is a English model originally trained by Kayvane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline_en_5.5.0_3.0_1725485290553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline_en_5.5.0_3.0_1725485290553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_wandb_week_3_complaints_classifier_512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.1 MB|
+
+## References
+
+https://huggingface.co/Kayvane/distilroberta-base-wandb-week-3-complaints-classifier-512
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_minelee_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_minelee_en.md
new file mode 100644
index 00000000000000..504011965354c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_minelee_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_minelee CamemBertEmbeddings from minelee
+author: John Snow Labs
+name: dummy_minelee
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_minelee` is a English model originally trained by minelee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_minelee_en_5.5.0_3.0_1725444274549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_minelee_en_5.5.0_3.0_1725444274549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_minelee","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_minelee","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_minelee|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/minelee/dummy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_minelee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_minelee_pipeline_en.md
new file mode 100644
index 00000000000000..59345c2b51a486
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_minelee_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_minelee_pipeline pipeline CamemBertEmbeddings from minelee
+author: John Snow Labs
+name: dummy_minelee_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_minelee_pipeline` is a English model originally trained by minelee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_minelee_pipeline_en_5.5.0_3.0_1725444350531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_minelee_pipeline_en_5.5.0_3.0_1725444350531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_minelee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_minelee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_minelee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/minelee/dummy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model2_juliana_zh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model2_juliana_zh_pipeline_en.md
new file mode 100644
index 00000000000000..be492903b71479
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model2_juliana_zh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model2_juliana_zh_pipeline pipeline CamemBertEmbeddings from juliana-zh
+author: John Snow Labs
+name: dummy_model2_juliana_zh_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model2_juliana_zh_pipeline` is a English model originally trained by juliana-zh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model2_juliana_zh_pipeline_en_5.5.0_3.0_1725444797088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model2_juliana_zh_pipeline_en_5.5.0_3.0_1725444797088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model2_juliana_zh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model2_juliana_zh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model2_juliana_zh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/juliana-zh/dummy-model2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model2_skr3178_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model2_skr3178_pipeline_en.md
new file mode 100644
index 00000000000000..6318ed267e3503
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model2_skr3178_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model2_skr3178_pipeline pipeline CamemBertEmbeddings from skr3178
+author: John Snow Labs
+name: dummy_model2_skr3178_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model2_skr3178_pipeline` is a English model originally trained by skr3178.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model2_skr3178_pipeline_en_5.5.0_3.0_1725408608751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model2_skr3178_pipeline_en_5.5.0_3.0_1725408608751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model2_skr3178_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model2_skr3178_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model2_skr3178_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/skr3178/dummy-model2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model8_pipeline_en.md
new file mode 100644
index 00000000000000..35908ca5161466
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model8_pipeline pipeline CamemBertEmbeddings from Turka
+author: John Snow Labs
+name: dummy_model8_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model8_pipeline` is a English model originally trained by Turka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model8_pipeline_en_5.5.0_3.0_1725445018385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model8_pipeline_en_5.5.0_3.0_1725445018385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Turka/dummy-model8
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_jin_cheon_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_jin_cheon_en.md
new file mode 100644
index 00000000000000..3c3d8678c409c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_jin_cheon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_2_jin_cheon CamemBertEmbeddings from jin-cheon
+author: John Snow Labs
+name: dummy_model_2_jin_cheon
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_2_jin_cheon` is a English model originally trained by jin-cheon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_2_jin_cheon_en_5.5.0_3.0_1725409258148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_2_jin_cheon_en_5.5.0_3.0_1725409258148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_2_jin_cheon","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_2_jin_cheon","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_2_jin_cheon|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jin-cheon/dummy-model-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_jin_cheon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_jin_cheon_pipeline_en.md
new file mode 100644
index 00000000000000..0d708571e72f5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_jin_cheon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_2_jin_cheon_pipeline pipeline CamemBertEmbeddings from jin-cheon
+author: John Snow Labs
+name: dummy_model_2_jin_cheon_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_2_jin_cheon_pipeline` is a English model originally trained by jin-cheon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_2_jin_cheon_pipeline_en_5.5.0_3.0_1725409334366.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_2_jin_cheon_pipeline_en_5.5.0_3.0_1725409334366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_2_jin_cheon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_2_jin_cheon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_2_jin_cheon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jin-cheon/dummy-model-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_plan_9_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_plan_9_en.md
new file mode 100644
index 00000000000000..09f61827e18069
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_plan_9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_2_plan_9 CamemBertEmbeddings from Plan-9
+author: John Snow Labs
+name: dummy_model_2_plan_9
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_2_plan_9` is a English model originally trained by Plan-9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_2_plan_9_en_5.5.0_3.0_1725445161444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_2_plan_9_en_5.5.0_3.0_1725445161444.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_2_plan_9","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_2_plan_9","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_2_plan_9|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Plan-9/dummy-model-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_plan_9_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_plan_9_pipeline_en.md
new file mode 100644
index 00000000000000..0ae5d59fe86fc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_2_plan_9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_2_plan_9_pipeline pipeline CamemBertEmbeddings from Plan-9
+author: John Snow Labs
+name: dummy_model_2_plan_9_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_2_plan_9_pipeline` is a English model originally trained by Plan-9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_2_plan_9_pipeline_en_5.5.0_3.0_1725445235841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_2_plan_9_pipeline_en_5.5.0_3.0_1725445235841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_2_plan_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_2_plan_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_2_plan_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Plan-9/dummy-model-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_7_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_7_en.md
new file mode 100644
index 00000000000000..9c9d9274c3d931
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_7 CamemBertEmbeddings from diegoref
+author: John Snow Labs
+name: dummy_model_7
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_7` is a English model originally trained by diegoref.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_7_en_5.5.0_3.0_1725442235022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_7_en_5.5.0_3.0_1725442235022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_7","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_7","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_7|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/diegoref/dummy-model-7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_ainullbabystep_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_ainullbabystep_en.md
new file mode 100644
index 00000000000000..0147c7cdc3606b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_ainullbabystep_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_ainullbabystep CamemBertEmbeddings from AINullBabystep
+author: John Snow Labs
+name: dummy_model_ainullbabystep
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ainullbabystep` is a English model originally trained by AINullBabystep.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ainullbabystep_en_5.5.0_3.0_1725408306443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ainullbabystep_en_5.5.0_3.0_1725408306443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_ainullbabystep","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ainullbabystep","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ainullbabystep|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/AINullBabystep/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_aniruddh10124_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_aniruddh10124_en.md
new file mode 100644
index 00000000000000..a191769e14d934
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_aniruddh10124_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_aniruddh10124 CamemBertEmbeddings from aniruddh10124
+author: John Snow Labs
+name: dummy_model_aniruddh10124
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_aniruddh10124` is a English model originally trained by aniruddh10124.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_aniruddh10124_en_5.5.0_3.0_1725408130501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_aniruddh10124_en_5.5.0_3.0_1725408130501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_aniruddh10124","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_aniruddh10124","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_aniruddh10124|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/aniruddh10124/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_aniruddh10124_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_aniruddh10124_pipeline_en.md
new file mode 100644
index 00000000000000..af38f64e165c67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_aniruddh10124_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_aniruddh10124_pipeline pipeline CamemBertEmbeddings from aniruddh10124
+author: John Snow Labs
+name: dummy_model_aniruddh10124_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_aniruddh10124_pipeline` is a English model originally trained by aniruddh10124.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_aniruddh10124_pipeline_en_5.5.0_3.0_1725408208669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_aniruddh10124_pipeline_en_5.5.0_3.0_1725408208669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_aniruddh10124_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_aniruddh10124_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_aniruddh10124_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/aniruddh10124/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benchan79_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benchan79_en.md
new file mode 100644
index 00000000000000..d51617611f062f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benchan79_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_benchan79 CamemBertEmbeddings from benchan79
+author: John Snow Labs
+name: dummy_model_benchan79
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_benchan79` is a English model originally trained by benchan79.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_benchan79_en_5.5.0_3.0_1725409333081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_benchan79_en_5.5.0_3.0_1725409333081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_benchan79","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_benchan79","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_benchan79|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/benchan79/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benyjaykay_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benyjaykay_en.md
new file mode 100644
index 00000000000000..8f798eeaeb4427
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benyjaykay_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_benyjaykay CamemBertEmbeddings from benyjaykay
+author: John Snow Labs
+name: dummy_model_benyjaykay
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_benyjaykay` is a English model originally trained by benyjaykay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_benyjaykay_en_5.5.0_3.0_1725442620464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_benyjaykay_en_5.5.0_3.0_1725442620464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_benyjaykay","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_benyjaykay","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_benyjaykay|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/benyjaykay/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benyjaykay_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benyjaykay_pipeline_en.md
new file mode 100644
index 00000000000000..2906e7bad48fbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_benyjaykay_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_benyjaykay_pipeline pipeline CamemBertEmbeddings from benyjaykay
+author: John Snow Labs
+name: dummy_model_benyjaykay_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_benyjaykay_pipeline` is a English model originally trained by benyjaykay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_benyjaykay_pipeline_en_5.5.0_3.0_1725442697456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_benyjaykay_pipeline_en_5.5.0_3.0_1725442697456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_benyjaykay_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_benyjaykay_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_benyjaykay_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/benyjaykay/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_binitha_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_binitha_pipeline_en.md
new file mode 100644
index 00000000000000..804ab3246c9a7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_binitha_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_binitha_pipeline pipeline CamemBertEmbeddings from Binitha
+author: John Snow Labs
+name: dummy_model_binitha_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_binitha_pipeline` is a English model originally trained by Binitha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_binitha_pipeline_en_5.5.0_3.0_1725444893629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_binitha_pipeline_en_5.5.0_3.0_1725444893629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_binitha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_binitha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_binitha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Binitha/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_blohsom_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_blohsom_en.md
new file mode 100644
index 00000000000000..1b14f929e632bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_blohsom_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_blohsom CamemBertEmbeddings from Blohsom
+author: John Snow Labs
+name: dummy_model_blohsom
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_blohsom` is a English model originally trained by Blohsom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_blohsom_en_5.5.0_3.0_1725442494023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_blohsom_en_5.5.0_3.0_1725442494023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_blohsom","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_blohsom","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_blohsom|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Blohsom/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_blohsom_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_blohsom_pipeline_en.md
new file mode 100644
index 00000000000000..8c00a310fd078d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_blohsom_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_blohsom_pipeline pipeline CamemBertEmbeddings from Blohsom
+author: John Snow Labs
+name: dummy_model_blohsom_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_blohsom_pipeline` is a English model originally trained by Blohsom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_blohsom_pipeline_en_5.5.0_3.0_1725442570687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_blohsom_pipeline_en_5.5.0_3.0_1725442570687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_blohsom_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_blohsom_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_blohsom_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Blohsom/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_charde_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_charde_en.md
new file mode 100644
index 00000000000000..65131d951be046
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_charde_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_charde CamemBertEmbeddings from charde
+author: John Snow Labs
+name: dummy_model_charde
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_charde` is a English model originally trained by charde.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_charde_en_5.5.0_3.0_1725444427257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_charde_en_5.5.0_3.0_1725444427257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_charde","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_charde","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_charde|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/charde/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_charde_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_charde_pipeline_en.md
new file mode 100644
index 00000000000000..cf80b9772cf709
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_charde_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_charde_pipeline pipeline CamemBertEmbeddings from charde
+author: John Snow Labs
+name: dummy_model_charde_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_charde_pipeline` is a English model originally trained by charde.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_charde_pipeline_en_5.5.0_3.0_1725444504025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_charde_pipeline_en_5.5.0_3.0_1725444504025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_charde_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_charde_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_charde_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/charde/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_devtrent_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_devtrent_en.md
new file mode 100644
index 00000000000000..163a06fc1ed3d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_devtrent_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_devtrent CamemBertEmbeddings from devtrent
+author: John Snow Labs
+name: dummy_model_devtrent
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_devtrent` is a English model originally trained by devtrent.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_devtrent_en_5.5.0_3.0_1725442796812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_devtrent_en_5.5.0_3.0_1725442796812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_devtrent","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_devtrent","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_devtrent|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/devtrent/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_devtrent_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_devtrent_pipeline_en.md
new file mode 100644
index 00000000000000..fbfdce433bb62d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_devtrent_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_devtrent_pipeline pipeline CamemBertEmbeddings from devtrent
+author: John Snow Labs
+name: dummy_model_devtrent_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_devtrent_pipeline` is a English model originally trained by devtrent.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_devtrent_pipeline_en_5.5.0_3.0_1725442873802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_devtrent_pipeline_en_5.5.0_3.0_1725442873802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_devtrent_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_devtrent_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_devtrent_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/devtrent/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_dvd005_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_dvd005_pipeline_en.md
new file mode 100644
index 00000000000000..86efcb997aaf72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_dvd005_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_dvd005_pipeline pipeline CamemBertEmbeddings from DvD005
+author: John Snow Labs
+name: dummy_model_dvd005_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dvd005_pipeline` is a English model originally trained by DvD005.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dvd005_pipeline_en_5.5.0_3.0_1725408578286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dvd005_pipeline_en_5.5.0_3.0_1725408578286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_dvd005_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_dvd005_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dvd005_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/DvD005/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_evannaderi_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_evannaderi_en.md
new file mode 100644
index 00000000000000..f8546a1e24c0da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_evannaderi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_evannaderi CamemBertEmbeddings from evannaderi
+author: John Snow Labs
+name: dummy_model_evannaderi
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_evannaderi` is a English model originally trained by evannaderi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_evannaderi_en_5.5.0_3.0_1725443907449.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_evannaderi_en_5.5.0_3.0_1725443907449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_evannaderi","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_evannaderi","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_evannaderi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/evannaderi/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_evannaderi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_evannaderi_pipeline_en.md
new file mode 100644
index 00000000000000..2577cb1f4b9bf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_evannaderi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_evannaderi_pipeline pipeline CamemBertEmbeddings from evannaderi
+author: John Snow Labs
+name: dummy_model_evannaderi_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_evannaderi_pipeline` is a English model originally trained by evannaderi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_evannaderi_pipeline_en_5.5.0_3.0_1725443984547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_evannaderi_pipeline_en_5.5.0_3.0_1725443984547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_evannaderi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_evannaderi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_evannaderi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/evannaderi/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_ffleming_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_ffleming_en.md
new file mode 100644
index 00000000000000..b5f18eba3ad96e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_ffleming_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_ffleming CamemBertEmbeddings from ffleming
+author: John Snow Labs
+name: dummy_model_ffleming
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ffleming` is a English model originally trained by ffleming.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ffleming_en_5.5.0_3.0_1725442250439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ffleming_en_5.5.0_3.0_1725442250439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_ffleming","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ffleming","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ffleming|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ffleming/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gmgowtham_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gmgowtham_pipeline_en.md
new file mode 100644
index 00000000000000..24cb38a92e01e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gmgowtham_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_gmgowtham_pipeline pipeline CamemBertEmbeddings from GMGowtham
+author: John Snow Labs
+name: dummy_model_gmgowtham_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_gmgowtham_pipeline` is a English model originally trained by GMGowtham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_gmgowtham_pipeline_en_5.5.0_3.0_1725443459442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_gmgowtham_pipeline_en_5.5.0_3.0_1725443459442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_gmgowtham_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_gmgowtham_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_gmgowtham_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/GMGowtham/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gvozdev_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gvozdev_en.md
new file mode 100644
index 00000000000000..3aae01afcff4ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gvozdev_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_gvozdev CamemBertEmbeddings from gvozdev
+author: John Snow Labs
+name: dummy_model_gvozdev
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_gvozdev` is a English model originally trained by gvozdev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_gvozdev_en_5.5.0_3.0_1725443255923.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_gvozdev_en_5.5.0_3.0_1725443255923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_gvozdev","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_gvozdev","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_gvozdev|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/gvozdev/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gvozdev_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gvozdev_pipeline_en.md
new file mode 100644
index 00000000000000..d595903a662001
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_gvozdev_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_gvozdev_pipeline pipeline CamemBertEmbeddings from gvozdev
+author: John Snow Labs
+name: dummy_model_gvozdev_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_gvozdev_pipeline` is a English model originally trained by gvozdev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_gvozdev_pipeline_en_5.5.0_3.0_1725443331319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_gvozdev_pipeline_en_5.5.0_3.0_1725443331319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_gvozdev_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_gvozdev_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_gvozdev_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/gvozdev/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_iamj1han_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_iamj1han_pipeline_en.md
new file mode 100644
index 00000000000000..d8ce87c184b8da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_iamj1han_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_iamj1han_pipeline pipeline CamemBertEmbeddings from iamj1han
+author: John Snow Labs
+name: dummy_model_iamj1han_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_iamj1han_pipeline` is a English model originally trained by iamj1han.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_iamj1han_pipeline_en_5.5.0_3.0_1725408036889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_iamj1han_pipeline_en_5.5.0_3.0_1725408036889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_iamj1han_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_iamj1han_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_iamj1han_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/iamj1han/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jgrabovac_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jgrabovac_en.md
new file mode 100644
index 00000000000000..ca1403502d9e62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jgrabovac_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jgrabovac CamemBertEmbeddings from jgrabovac
+author: John Snow Labs
+name: dummy_model_jgrabovac
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jgrabovac` is a English model originally trained by jgrabovac.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jgrabovac_en_5.5.0_3.0_1725445044623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jgrabovac_en_5.5.0_3.0_1725445044623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jgrabovac","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jgrabovac","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jgrabovac|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jgrabovac/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jgrabovac_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jgrabovac_pipeline_en.md
new file mode 100644
index 00000000000000..5e8464c7578454
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jgrabovac_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jgrabovac_pipeline pipeline CamemBertEmbeddings from jgrabovac
+author: John Snow Labs
+name: dummy_model_jgrabovac_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jgrabovac_pipeline` is a English model originally trained by jgrabovac.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jgrabovac_pipeline_en_5.5.0_3.0_1725445119846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jgrabovac_pipeline_en_5.5.0_3.0_1725445119846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jgrabovac_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jgrabovac_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jgrabovac_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jgrabovac/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jonathansum_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jonathansum_pipeline_en.md
new file mode 100644
index 00000000000000..39a87534b0d05f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_jonathansum_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jonathansum_pipeline pipeline CamemBertEmbeddings from JonathanSum
+author: John Snow Labs
+name: dummy_model_jonathansum_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jonathansum_pipeline` is a English model originally trained by JonathanSum.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jonathansum_pipeline_en_5.5.0_3.0_1725443228616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jonathansum_pipeline_en_5.5.0_3.0_1725443228616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jonathansum_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jonathansum_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jonathansum_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/JonathanSum/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaso_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaso_en.md
new file mode 100644
index 00000000000000..dd88d177383214
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaso_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_kaso CamemBertEmbeddings from kaso
+author: John Snow Labs
+name: dummy_model_kaso
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kaso` is a English model originally trained by kaso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kaso_en_5.5.0_3.0_1725408180600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kaso_en_5.5.0_3.0_1725408180600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_kaso","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_kaso","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kaso|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/kaso/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaso_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaso_pipeline_en.md
new file mode 100644
index 00000000000000..19ab4a8ee29e71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaso_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_kaso_pipeline pipeline CamemBertEmbeddings from kaso
+author: John Snow Labs
+name: dummy_model_kaso_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kaso_pipeline` is a English model originally trained by kaso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kaso_pipeline_en_5.5.0_3.0_1725408258462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kaso_pipeline_en_5.5.0_3.0_1725408258462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_kaso_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_kaso_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kaso_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/kaso/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaushikacharya_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaushikacharya_en.md
new file mode 100644
index 00000000000000..16677e664efdcf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaushikacharya_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_kaushikacharya CamemBertEmbeddings from kaushikacharya
+author: John Snow Labs
+name: dummy_model_kaushikacharya
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kaushikacharya` is a English model originally trained by kaushikacharya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kaushikacharya_en_5.5.0_3.0_1725444190052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kaushikacharya_en_5.5.0_3.0_1725444190052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_kaushikacharya","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_kaushikacharya","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kaushikacharya|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/kaushikacharya/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaushikacharya_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaushikacharya_pipeline_en.md
new file mode 100644
index 00000000000000..02c3881d9b4b67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kaushikacharya_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_kaushikacharya_pipeline pipeline CamemBertEmbeddings from kaushikacharya
+author: John Snow Labs
+name: dummy_model_kaushikacharya_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kaushikacharya_pipeline` is a English model originally trained by kaushikacharya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kaushikacharya_pipeline_en_5.5.0_3.0_1725444266266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kaushikacharya_pipeline_en_5.5.0_3.0_1725444266266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_kaushikacharya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_kaushikacharya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kaushikacharya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/kaushikacharya/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kmpartner_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kmpartner_en.md
new file mode 100644
index 00000000000000..6b45c51eb2b94c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_kmpartner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_kmpartner CamemBertEmbeddings from kmpartner
+author: John Snow Labs
+name: dummy_model_kmpartner
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kmpartner` is a English model originally trained by kmpartner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kmpartner_en_5.5.0_3.0_1725408781971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kmpartner_en_5.5.0_3.0_1725408781971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_kmpartner","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_kmpartner","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kmpartner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/kmpartner/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lanyiu_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lanyiu_en.md
new file mode 100644
index 00000000000000..9034770e69f33b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lanyiu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_lanyiu CamemBertEmbeddings from LanYiU
+author: John Snow Labs
+name: dummy_model_lanyiu
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lanyiu` is a English model originally trained by LanYiU.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lanyiu_en_5.5.0_3.0_1725445135088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lanyiu_en_5.5.0_3.0_1725445135088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_lanyiu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_lanyiu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lanyiu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/LanYiU/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lanyiu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lanyiu_pipeline_en.md
new file mode 100644
index 00000000000000..b00cadfdcd0684
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lanyiu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_lanyiu_pipeline pipeline CamemBertEmbeddings from LanYiU
+author: John Snow Labs
+name: dummy_model_lanyiu_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lanyiu_pipeline` is a English model originally trained by LanYiU.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lanyiu_pipeline_en_5.5.0_3.0_1725445209555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lanyiu_pipeline_en_5.5.0_3.0_1725445209555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_lanyiu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_lanyiu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lanyiu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/LanYiU/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lifan_z_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lifan_z_en.md
new file mode 100644
index 00000000000000..ad7688c031f056
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lifan_z_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_lifan_z CamemBertEmbeddings from Lifan-Z
+author: John Snow Labs
+name: dummy_model_lifan_z
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lifan_z` is a English model originally trained by Lifan-Z.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lifan_z_en_5.5.0_3.0_1725443044292.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lifan_z_en_5.5.0_3.0_1725443044292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_lifan_z","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_lifan_z","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lifan_z|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Lifan-Z/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lifan_z_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lifan_z_pipeline_en.md
new file mode 100644
index 00000000000000..902075eb370604
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_lifan_z_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_lifan_z_pipeline pipeline CamemBertEmbeddings from Lifan-Z
+author: John Snow Labs
+name: dummy_model_lifan_z_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lifan_z_pipeline` is a English model originally trained by Lifan-Z.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lifan_z_pipeline_en_5.5.0_3.0_1725443120943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lifan_z_pipeline_en_5.5.0_3.0_1725443120943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_lifan_z_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_lifan_z_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lifan_z_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Lifan-Z/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_maxcarduner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_maxcarduner_pipeline_en.md
new file mode 100644
index 00000000000000..18b1998977bde2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_maxcarduner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_maxcarduner_pipeline pipeline CamemBertEmbeddings from maxcarduner
+author: John Snow Labs
+name: dummy_model_maxcarduner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_maxcarduner_pipeline` is a English model originally trained by maxcarduner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_maxcarduner_pipeline_en_5.5.0_3.0_1725444804874.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_maxcarduner_pipeline_en_5.5.0_3.0_1725444804874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_maxcarduner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_maxcarduner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_maxcarduner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/maxcarduner/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_nonoch_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_nonoch_en.md
new file mode 100644
index 00000000000000..1f5cc6275b176d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_nonoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_nonoch CamemBertEmbeddings from nonoch
+author: John Snow Labs
+name: dummy_model_nonoch
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_nonoch` is a English model originally trained by nonoch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_nonoch_en_5.5.0_3.0_1725444492014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_nonoch_en_5.5.0_3.0_1725444492014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_nonoch","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_nonoch","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_nonoch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nonoch/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_nonoch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_nonoch_pipeline_en.md
new file mode 100644
index 00000000000000..2fac273688c278
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_nonoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_nonoch_pipeline pipeline CamemBertEmbeddings from nonoch
+author: John Snow Labs
+name: dummy_model_nonoch_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_nonoch_pipeline` is a English model originally trained by nonoch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_nonoch_pipeline_en_5.5.0_3.0_1725444568842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_nonoch_pipeline_en_5.5.0_3.0_1725444568842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_nonoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_nonoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_nonoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nonoch/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_pallavi176_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_pallavi176_pipeline_en.md
new file mode 100644
index 00000000000000..ecd56bf8448088
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_pallavi176_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_pallavi176_pipeline pipeline CamemBertEmbeddings from pallavi176
+author: John Snow Labs
+name: dummy_model_pallavi176_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pallavi176_pipeline` is a English model originally trained by pallavi176.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pallavi176_pipeline_en_5.5.0_3.0_1725408724173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pallavi176_pipeline_en_5.5.0_3.0_1725408724173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_pallavi176_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_pallavi176_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_pallavi176_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/pallavi176/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_qmmms_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_qmmms_en.md
new file mode 100644
index 00000000000000..eb56e8c15baf6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_qmmms_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_qmmms CamemBertEmbeddings from QMMMS
+author: John Snow Labs
+name: dummy_model_qmmms
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_qmmms` is a English model originally trained by QMMMS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_qmmms_en_5.5.0_3.0_1725444145121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_qmmms_en_5.5.0_3.0_1725444145121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_qmmms","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_qmmms","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_qmmms|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/QMMMS/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_qmmms_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_qmmms_pipeline_en.md
new file mode 100644
index 00000000000000..e3375bf91631d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_qmmms_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_qmmms_pipeline pipeline CamemBertEmbeddings from QMMMS
+author: John Snow Labs
+name: dummy_model_qmmms_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_qmmms_pipeline` is a English model originally trained by QMMMS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_qmmms_pipeline_en_5.5.0_3.0_1725444221831.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_qmmms_pipeline_en_5.5.0_3.0_1725444221831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_qmmms_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_qmmms_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_qmmms_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/QMMMS/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_raghav0802_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_raghav0802_pipeline_en.md
new file mode 100644
index 00000000000000..1ba1eb300b0382
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_raghav0802_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_raghav0802_pipeline pipeline CamemBertEmbeddings from Raghav0802
+author: John Snow Labs
+name: dummy_model_raghav0802_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_raghav0802_pipeline` is a English model originally trained by Raghav0802.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_raghav0802_pipeline_en_5.5.0_3.0_1725442870228.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_raghav0802_pipeline_en_5.5.0_3.0_1725442870228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_raghav0802_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_raghav0802_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_raghav0802_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Raghav0802/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rahulraj2k16_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rahulraj2k16_en.md
new file mode 100644
index 00000000000000..e9209b4a0e4b77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rahulraj2k16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_rahulraj2k16 CamemBertEmbeddings from rahulraj2k16
+author: John Snow Labs
+name: dummy_model_rahulraj2k16
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rahulraj2k16` is a English model originally trained by rahulraj2k16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_rahulraj2k16_en_5.5.0_3.0_1725444405233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rahulraj2k16_en_5.5.0_3.0_1725444405233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_rahulraj2k16","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_rahulraj2k16","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_rahulraj2k16|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/rahulraj2k16/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rahulraj2k16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rahulraj2k16_pipeline_en.md
new file mode 100644
index 00000000000000..f90e0a7cfc12f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rahulraj2k16_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_rahulraj2k16_pipeline pipeline CamemBertEmbeddings from rahulraj2k16
+author: John Snow Labs
+name: dummy_model_rahulraj2k16_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rahulraj2k16_pipeline` is a English model originally trained by rahulraj2k16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_rahulraj2k16_pipeline_en_5.5.0_3.0_1725444481170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rahulraj2k16_pipeline_en_5.5.0_3.0_1725444481170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_rahulraj2k16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_rahulraj2k16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_rahulraj2k16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/rahulraj2k16/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_raphgg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_raphgg_pipeline_en.md
new file mode 100644
index 00000000000000..5e9e9eccf79ff8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_raphgg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_raphgg_pipeline pipeline CamemBertEmbeddings from raphgg
+author: John Snow Labs
+name: dummy_model_raphgg_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_raphgg_pipeline` is a English model originally trained by raphgg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_raphgg_pipeline_en_5.5.0_3.0_1725408854928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_raphgg_pipeline_en_5.5.0_3.0_1725408854928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_raphgg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_raphgg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_raphgg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/raphgg/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_riccardogvn_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_riccardogvn_en.md
new file mode 100644
index 00000000000000..ab09822ee1b679
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_riccardogvn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_riccardogvn CamemBertEmbeddings from RiccardoGvn
+author: John Snow Labs
+name: dummy_model_riccardogvn
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_riccardogvn` is a English model originally trained by RiccardoGvn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_riccardogvn_en_5.5.0_3.0_1725444620784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_riccardogvn_en_5.5.0_3.0_1725444620784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_riccardogvn","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_riccardogvn","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_riccardogvn|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/RiccardoGvn/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_riccardogvn_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_riccardogvn_pipeline_en.md
new file mode 100644
index 00000000000000..40e54df03aeb05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_riccardogvn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_riccardogvn_pipeline pipeline CamemBertEmbeddings from RiccardoGvn
+author: John Snow Labs
+name: dummy_model_riccardogvn_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_riccardogvn_pipeline` is a English model originally trained by RiccardoGvn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_riccardogvn_pipeline_en_5.5.0_3.0_1725444697114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_riccardogvn_pipeline_en_5.5.0_3.0_1725444697114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_riccardogvn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_riccardogvn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_riccardogvn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/RiccardoGvn/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rocksat_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rocksat_en.md
new file mode 100644
index 00000000000000..804d44d6eb3775
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rocksat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_rocksat CamemBertEmbeddings from rocksat
+author: John Snow Labs
+name: dummy_model_rocksat
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rocksat` is a English model originally trained by rocksat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_rocksat_en_5.5.0_3.0_1725443908047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rocksat_en_5.5.0_3.0_1725443908047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_rocksat","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_rocksat","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_rocksat|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/rocksat/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_samra1211_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_samra1211_en.md
new file mode 100644
index 00000000000000..dd9a33621079a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_samra1211_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_samra1211 CamemBertEmbeddings from Samra1211
+author: John Snow Labs
+name: dummy_model_samra1211
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_samra1211` is a English model originally trained by Samra1211.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_samra1211_en_5.5.0_3.0_1725444255687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_samra1211_en_5.5.0_3.0_1725444255687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_samra1211","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_samra1211","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_samra1211|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Samra1211/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_samra1211_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_samra1211_pipeline_en.md
new file mode 100644
index 00000000000000..c7be3627edebd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_samra1211_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_samra1211_pipeline pipeline CamemBertEmbeddings from Samra1211
+author: John Snow Labs
+name: dummy_model_samra1211_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_samra1211_pipeline` is a English model originally trained by Samra1211.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_samra1211_pipeline_en_5.5.0_3.0_1725444332009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_samra1211_pipeline_en_5.5.0_3.0_1725444332009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_samra1211_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_samra1211_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_samra1211_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Samra1211/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sebu_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sebu_en.md
new file mode 100644
index 00000000000000..e16a0d3561d90d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sebu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_sebu CamemBertEmbeddings from Sebu
+author: John Snow Labs
+name: dummy_model_sebu
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sebu` is a English model originally trained by Sebu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sebu_en_5.5.0_3.0_1725442976390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sebu_en_5.5.0_3.0_1725442976390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_sebu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sebu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sebu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Sebu/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sebu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sebu_pipeline_en.md
new file mode 100644
index 00000000000000..89b3c1c17dcc6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sebu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_sebu_pipeline pipeline CamemBertEmbeddings from Sebu
+author: John Snow Labs
+name: dummy_model_sebu_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sebu_pipeline` is a English model originally trained by Sebu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sebu_pipeline_en_5.5.0_3.0_1725443053922.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sebu_pipeline_en_5.5.0_3.0_1725443053922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_sebu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_sebu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sebu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Sebu/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_srashti07_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_srashti07_en.md
new file mode 100644
index 00000000000000..c12af94b84b534
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_srashti07_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_srashti07 CamemBertEmbeddings from srashti07
+author: John Snow Labs
+name: dummy_model_srashti07
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_srashti07` is a English model originally trained by srashti07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_srashti07_en_5.5.0_3.0_1725442502355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_srashti07_en_5.5.0_3.0_1725442502355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_srashti07","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_srashti07","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_srashti07|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/srashti07/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_srashti07_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_srashti07_pipeline_en.md
new file mode 100644
index 00000000000000..4c6443d60db1e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_srashti07_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_srashti07_pipeline pipeline CamemBertEmbeddings from srashti07
+author: John Snow Labs
+name: dummy_model_srashti07_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_srashti07_pipeline` is a English model originally trained by srashti07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_srashti07_pipeline_en_5.5.0_3.0_1725442578981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_srashti07_pipeline_en_5.5.0_3.0_1725442578981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_srashti07_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_srashti07_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_srashti07_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/srashti07/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suhanishamma_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suhanishamma_en.md
new file mode 100644
index 00000000000000..4ed0d8d964ac17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suhanishamma_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_suhanishamma CamemBertEmbeddings from suhanishamma
+author: John Snow Labs
+name: dummy_model_suhanishamma
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_suhanishamma` is a English model originally trained by suhanishamma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_suhanishamma_en_5.5.0_3.0_1725408358619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_suhanishamma_en_5.5.0_3.0_1725408358619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_suhanishamma","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_suhanishamma","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_suhanishamma|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/suhanishamma/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suhanishamma_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suhanishamma_pipeline_en.md
new file mode 100644
index 00000000000000..d2b34bdf985a05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suhanishamma_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_suhanishamma_pipeline pipeline CamemBertEmbeddings from suhanishamma
+author: John Snow Labs
+name: dummy_model_suhanishamma_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_suhanishamma_pipeline` is a English model originally trained by suhanishamma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_suhanishamma_pipeline_en_5.5.0_3.0_1725408436946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_suhanishamma_pipeline_en_5.5.0_3.0_1725408436946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_suhanishamma_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_suhanishamma_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_suhanishamma_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/suhanishamma/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suieugeneris_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suieugeneris_pipeline_en.md
new file mode 100644
index 00000000000000..b4dc77dd7dab6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_suieugeneris_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_suieugeneris_pipeline pipeline CamemBertEmbeddings from suieugeneris
+author: John Snow Labs
+name: dummy_model_suieugeneris_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_suieugeneris_pipeline` is a English model originally trained by suieugeneris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_suieugeneris_pipeline_en_5.5.0_3.0_1725408864800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_suieugeneris_pipeline_en_5.5.0_3.0_1725408864800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_suieugeneris_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_suieugeneris_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_suieugeneris_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/suieugeneris/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sunilpinnamaneni_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sunilpinnamaneni_en.md
new file mode 100644
index 00000000000000..067cc16c7af5ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_sunilpinnamaneni_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_sunilpinnamaneni CamemBertEmbeddings from sunilpinnamaneni
+author: John Snow Labs
+name: dummy_model_sunilpinnamaneni
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sunilpinnamaneni` is a English model originally trained by sunilpinnamaneni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sunilpinnamaneni_en_5.5.0_3.0_1725442943096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sunilpinnamaneni_en_5.5.0_3.0_1725442943096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_sunilpinnamaneni","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sunilpinnamaneni","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sunilpinnamaneni|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sunilpinnamaneni/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_thucdangvan020999_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_thucdangvan020999_en.md
new file mode 100644
index 00000000000000..d281eb41f67fb3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_thucdangvan020999_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_thucdangvan020999 CamemBertEmbeddings from thucdangvan020999
+author: John Snow Labs
+name: dummy_model_thucdangvan020999
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_thucdangvan020999` is a English model originally trained by thucdangvan020999.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_thucdangvan020999_en_5.5.0_3.0_1725444730980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_thucdangvan020999_en_5.5.0_3.0_1725444730980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_thucdangvan020999","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_thucdangvan020999","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_thucdangvan020999|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/thucdangvan020999/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_thucdangvan020999_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_thucdangvan020999_pipeline_en.md
new file mode 100644
index 00000000000000..f14d8123366bdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_thucdangvan020999_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_thucdangvan020999_pipeline pipeline CamemBertEmbeddings from thucdangvan020999
+author: John Snow Labs
+name: dummy_model_thucdangvan020999_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_thucdangvan020999_pipeline` is a English model originally trained by thucdangvan020999.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_thucdangvan020999_pipeline_en_5.5.0_3.0_1725444807596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_thucdangvan020999_pipeline_en_5.5.0_3.0_1725444807596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_thucdangvan020999_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_thucdangvan020999_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_thucdangvan020999_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/thucdangvan020999/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_tofunumber1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_tofunumber1_pipeline_en.md
new file mode 100644
index 00000000000000..10ebf0696cc40d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_tofunumber1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_tofunumber1_pipeline pipeline CamemBertEmbeddings from TofuNumber1
+author: John Snow Labs
+name: dummy_model_tofunumber1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_tofunumber1_pipeline` is a English model originally trained by TofuNumber1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_tofunumber1_pipeline_en_5.5.0_3.0_1725408042703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_tofunumber1_pipeline_en_5.5.0_3.0_1725408042703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_tofunumber1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_tofunumber1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_tofunumber1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/TofuNumber1/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_tpanda09_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_tpanda09_en.md
new file mode 100644
index 00000000000000..ec801f25cedf4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_tpanda09_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_tpanda09 CamemBertEmbeddings from tpanda09
+author: John Snow Labs
+name: dummy_model_tpanda09
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_tpanda09` is a English model originally trained by tpanda09.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_tpanda09_en_5.5.0_3.0_1725443907696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_tpanda09_en_5.5.0_3.0_1725443907696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_tpanda09","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_tpanda09","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_tpanda09|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/tpanda09/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_vickysirwani_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_vickysirwani_pipeline_en.md
new file mode 100644
index 00000000000000..e234d6f50b2cd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_vickysirwani_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_vickysirwani_pipeline pipeline CamemBertEmbeddings from vickysirwani
+author: John Snow Labs
+name: dummy_model_vickysirwani_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_vickysirwani_pipeline` is a English model originally trained by vickysirwani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_vickysirwani_pipeline_en_5.5.0_3.0_1725409227571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_vickysirwani_pipeline_en_5.5.0_3.0_1725409227571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_vickysirwani_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_vickysirwani_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_vickysirwani_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/vickysirwani/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_xuda77_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_xuda77_en.md
new file mode 100644
index 00000000000000..7fadfd2b20beb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_xuda77_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_xuda77 CamemBertEmbeddings from xuda77
+author: John Snow Labs
+name: dummy_model_xuda77
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_xuda77` is a English model originally trained by xuda77.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_xuda77_en_5.5.0_3.0_1725408253040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_xuda77_en_5.5.0_3.0_1725408253040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_xuda77","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_xuda77","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_xuda77|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/xuda77/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_yuta0x89_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_yuta0x89_en.md
new file mode 100644
index 00000000000000..517fb252445df6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_yuta0x89_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_yuta0x89 CamemBertEmbeddings from yuta0x89
+author: John Snow Labs
+name: dummy_model_yuta0x89
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_yuta0x89` is a English model originally trained by yuta0x89.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_yuta0x89_en_5.5.0_3.0_1725441967811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_yuta0x89_en_5.5.0_3.0_1725441967811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_yuta0x89","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_yuta0x89","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_yuta0x89|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/yuta0x89/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_yuta0x89_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_yuta0x89_pipeline_en.md
new file mode 100644
index 00000000000000..9561d586e9baa4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_yuta0x89_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_yuta0x89_pipeline pipeline CamemBertEmbeddings from yuta0x89
+author: John Snow Labs
+name: dummy_model_yuta0x89_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_yuta0x89_pipeline` is a English model originally trained by yuta0x89.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_yuta0x89_pipeline_en_5.5.0_3.0_1725442044401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_yuta0x89_pipeline_en_5.5.0_3.0_1725442044401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_yuta0x89_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_yuta0x89_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_yuta0x89_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/yuta0x89/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-emotion_text_classifier_on_dd_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-emotion_text_classifier_on_dd_v1_en.md
new file mode 100644
index 00000000000000..92126b2d8bc02e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-emotion_text_classifier_on_dd_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emotion_text_classifier_on_dd_v1 RoBertaForSequenceClassification from Shotaro30678
+author: John Snow Labs
+name: emotion_text_classifier_on_dd_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_text_classifier_on_dd_v1` is a English model originally trained by Shotaro30678.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_text_classifier_on_dd_v1_en_5.5.0_3.0_1725486105333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_text_classifier_on_dd_v1_en_5.5.0_3.0_1725486105333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("emotion_text_classifier_on_dd_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("emotion_text_classifier_on_dd_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_text_classifier_on_dd_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.9 MB|
+
+## References
+
+https://huggingface.co/Shotaro30678/emotion_text_classifier_on_dd_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-environmentalbert_base_en.md b/docs/_posts/ahmedlone127/2024-09-04-environmentalbert_base_en.md
new file mode 100644
index 00000000000000..0870be6cf694cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-environmentalbert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English environmentalbert_base RoBertaEmbeddings from ESGBERT
+author: John Snow Labs
+name: environmentalbert_base
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`environmentalbert_base` is a English model originally trained by ESGBERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/environmentalbert_base_en_5.5.0_3.0_1725412648667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/environmentalbert_base_en_5.5.0_3.0_1725412648667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("environmentalbert_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("environmentalbert_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|environmentalbert_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.7 MB|
+
+## References
+
+https://huggingface.co/ESGBERT/EnvironmentalBERT-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-erlangshen_unimc_albert_235m_english_en.md b/docs/_posts/ahmedlone127/2024-09-04-erlangshen_unimc_albert_235m_english_en.md
new file mode 100644
index 00000000000000..f02a5f7d28d329
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-erlangshen_unimc_albert_235m_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English erlangshen_unimc_albert_235m_english AlbertEmbeddings from IDEA-CCNL
+author: John Snow Labs
+name: erlangshen_unimc_albert_235m_english
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`erlangshen_unimc_albert_235m_english` is a English model originally trained by IDEA-CCNL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/erlangshen_unimc_albert_235m_english_en_5.5.0_3.0_1725435153233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/erlangshen_unimc_albert_235m_english_en_5.5.0_3.0_1725435153233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("erlangshen_unimc_albert_235m_english","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("erlangshen_unimc_albert_235m_english","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|erlangshen_unimc_albert_235m_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|771.0 MB|
+
+## References
+
+https://huggingface.co/IDEA-CCNL/Erlangshen-UniMC-Albert-235M-English
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-erlangshen_unimc_albert_235m_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-erlangshen_unimc_albert_235m_english_pipeline_en.md
new file mode 100644
index 00000000000000..79c79c2d1e4fe1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-erlangshen_unimc_albert_235m_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English erlangshen_unimc_albert_235m_english_pipeline pipeline AlbertEmbeddings from IDEA-CCNL
+author: John Snow Labs
+name: erlangshen_unimc_albert_235m_english_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`erlangshen_unimc_albert_235m_english_pipeline` is a English model originally trained by IDEA-CCNL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/erlangshen_unimc_albert_235m_english_pipeline_en_5.5.0_3.0_1725435191937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/erlangshen_unimc_albert_235m_english_pipeline_en_5.5.0_3.0_1725435191937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("erlangshen_unimc_albert_235m_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("erlangshen_unimc_albert_235m_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|erlangshen_unimc_albert_235m_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|771.0 MB|
+
+## References
+
+https://huggingface.co/IDEA-CCNL/Erlangshen-UniMC-Albert-235M-English
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-esg_sentiment_prediction_en.md b/docs/_posts/ahmedlone127/2024-09-04-esg_sentiment_prediction_en.md
new file mode 100644
index 00000000000000..79c149bdc8022a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-esg_sentiment_prediction_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esg_sentiment_prediction CamemBertForSequenceClassification from Katkatkuu
+author: John Snow Labs
+name: esg_sentiment_prediction
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esg_sentiment_prediction` is a English model originally trained by Katkatkuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esg_sentiment_prediction_en_5.5.0_3.0_1725480361832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esg_sentiment_prediction_en_5.5.0_3.0_1725480361832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("esg_sentiment_prediction","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("esg_sentiment_prediction", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esg_sentiment_prediction|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.3 MB|
+
+## References
+
+https://huggingface.co/Katkatkuu/ESG_Sentiment_Prediction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-est_roberta_pipeline_et.md b/docs/_posts/ahmedlone127/2024-09-04-est_roberta_pipeline_et.md
new file mode 100644
index 00000000000000..514ba7ad09824a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-est_roberta_pipeline_et.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Estonian est_roberta_pipeline pipeline CamemBertEmbeddings from EMBEDDIA
+author: John Snow Labs
+name: est_roberta_pipeline
+date: 2024-09-04
+tags: [et, open_source, pipeline, onnx]
+task: Embeddings
+language: et
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`est_roberta_pipeline` is a Estonian model originally trained by EMBEDDIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/est_roberta_pipeline_et_5.5.0_3.0_1725442410460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/est_roberta_pipeline_et_5.5.0_3.0_1725442410460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("est_roberta_pipeline", lang = "et")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("est_roberta_pipeline", lang = "et")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|est_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|et|
+|Size:|277.9 MB|
+
+## References
+
+https://huggingface.co/EMBEDDIA/est-roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-facets_gpt_77_en.md b/docs/_posts/ahmedlone127/2024-09-04-facets_gpt_77_en.md
new file mode 100644
index 00000000000000..0fb0117782edbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-facets_gpt_77_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English facets_gpt_77 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_gpt_77
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facets_gpt_77` is a English model originally trained by ingeol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facets_gpt_77_en_5.5.0_3.0_1725470006328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_gpt_77_en_5.5.0_3.0_1725470006328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("facets_gpt_77","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("facets_gpt_77","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_gpt_77|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_gpt_77
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-facets_gpt_expanswer_35_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-facets_gpt_expanswer_35_pipeline_en.md
new file mode 100644
index 00000000000000..5659dc7430e05e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-facets_gpt_expanswer_35_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English facets_gpt_expanswer_35_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_gpt_expanswer_35_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facets_gpt_expanswer_35_pipeline` is a English model originally trained by ingeol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facets_gpt_expanswer_35_pipeline_en_5.5.0_3.0_1725470934263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_gpt_expanswer_35_pipeline_en_5.5.0_3.0_1725470934263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("facets_gpt_expanswer_35_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("facets_gpt_expanswer_35_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_gpt_expanswer_35_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_gpt_expanswer_35
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fairlex_cail_minilm_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-04-fairlex_cail_minilm_pipeline_zh.md
new file mode 100644
index 00000000000000..8db5ce63af142f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fairlex_cail_minilm_pipeline_zh.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Chinese fairlex_cail_minilm_pipeline pipeline XlmRoBertaEmbeddings from coastalcph
+author: John Snow Labs
+name: fairlex_cail_minilm_pipeline
+date: 2024-09-04
+tags: [zh, open_source, pipeline, onnx]
+task: Embeddings
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fairlex_cail_minilm_pipeline` is a Chinese model originally trained by coastalcph.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fairlex_cail_minilm_pipeline_zh_5.5.0_3.0_1725416960919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fairlex_cail_minilm_pipeline_zh_5.5.0_3.0_1725416960919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fairlex_cail_minilm_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fairlex_cail_minilm_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fairlex_cail_minilm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|403.0 MB|
+
+## References
+
+https://huggingface.co/coastalcph/fairlex-cail-minilm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fairlex_cail_minilm_zh.md b/docs/_posts/ahmedlone127/2024-09-04-fairlex_cail_minilm_zh.md
new file mode 100644
index 00000000000000..129d1d53e4dd62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fairlex_cail_minilm_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese fairlex_cail_minilm XlmRoBertaEmbeddings from coastalcph
+author: John Snow Labs
+name: fairlex_cail_minilm
+date: 2024-09-04
+tags: [zh, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fairlex_cail_minilm` is a Chinese model originally trained by coastalcph.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fairlex_cail_minilm_zh_5.5.0_3.0_1725416939644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fairlex_cail_minilm_zh_5.5.0_3.0_1725416939644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("fairlex_cail_minilm","zh") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("fairlex_cail_minilm","zh") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fairlex_cail_minilm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|zh|
+|Size:|402.9 MB|
+
+## References
+
+https://huggingface.co/coastalcph/fairlex-cail-minilm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fart_chemberta_pubchem10m_en.md b/docs/_posts/ahmedlone127/2024-09-04-fart_chemberta_pubchem10m_en.md
new file mode 100644
index 00000000000000..3480e4030accf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fart_chemberta_pubchem10m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fart_chemberta_pubchem10m RoBertaForSequenceClassification from FartLabs
+author: John Snow Labs
+name: fart_chemberta_pubchem10m
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fart_chemberta_pubchem10m` is a English model originally trained by FartLabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fart_chemberta_pubchem10m_en_5.5.0_3.0_1725453234823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fart_chemberta_pubchem10m_en_5.5.0_3.0_1725453234823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("fart_chemberta_pubchem10m","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("fart_chemberta_pubchem10m", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fart_chemberta_pubchem10m|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|313.2 MB|
+
+## References
+
+https://huggingface.co/FartLabs/FART_Chemberta_PubChem10M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fart_chemberta_pubchem10m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-fart_chemberta_pubchem10m_pipeline_en.md
new file mode 100644
index 00000000000000..473abe59d4edd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fart_chemberta_pubchem10m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fart_chemberta_pubchem10m_pipeline pipeline RoBertaForSequenceClassification from FartLabs
+author: John Snow Labs
+name: fart_chemberta_pubchem10m_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fart_chemberta_pubchem10m_pipeline` is a English model originally trained by FartLabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fart_chemberta_pubchem10m_pipeline_en_5.5.0_3.0_1725453249811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fart_chemberta_pubchem10m_pipeline_en_5.5.0_3.0_1725453249811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fart_chemberta_pubchem10m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fart_chemberta_pubchem10m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fart_chemberta_pubchem10m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|313.2 MB|
+
+## References
+
+https://huggingface.co/FartLabs/FART_Chemberta_PubChem10M
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-feelings_a6000_0_00001_en.md b/docs/_posts/ahmedlone127/2024-09-04-feelings_a6000_0_00001_en.md
new file mode 100644
index 00000000000000..b215855463f1ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-feelings_a6000_0_00001_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English feelings_a6000_0_00001 RoBertaForSequenceClassification from rose-e-wang
+author: John Snow Labs
+name: feelings_a6000_0_00001
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feelings_a6000_0_00001` is a English model originally trained by rose-e-wang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feelings_a6000_0_00001_en_5.5.0_3.0_1725452751210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feelings_a6000_0_00001_en_5.5.0_3.0_1725452751210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("feelings_a6000_0_00001","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("feelings_a6000_0_00001", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|feelings_a6000_0_00001|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/rose-e-wang/feelings_a6000_0.00001
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-feelings_a6000_0_00001_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-feelings_a6000_0_00001_pipeline_en.md
new file mode 100644
index 00000000000000..ffea405e6f54d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-feelings_a6000_0_00001_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English feelings_a6000_0_00001_pipeline pipeline RoBertaForSequenceClassification from rose-e-wang
+author: John Snow Labs
+name: feelings_a6000_0_00001_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feelings_a6000_0_00001_pipeline` is a English model originally trained by rose-e-wang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feelings_a6000_0_00001_pipeline_en_5.5.0_3.0_1725452837104.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feelings_a6000_0_00001_pipeline_en_5.5.0_3.0_1725452837104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("feelings_a6000_0_00001_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("feelings_a6000_0_00001_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|feelings_a6000_0_00001_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/rose-e-wang/feelings_a6000_0.00001
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_clip_en.md b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_clip_en.md
new file mode 100644
index 00000000000000..8421515fa704fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_clip_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English fine_tuned_clip CLIPForZeroShotClassification from saiabhishek-itta
+author: John Snow Labs
+name: fine_tuned_clip
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_clip` is a English model originally trained by saiabhishek-itta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_clip_en_5.5.0_3.0_1725456363962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_clip_en_5.5.0_3.0_1725456363962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("fine_tuned_clip","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("fine_tuned_clip","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_clip|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/saiabhishek-itta/fine-tuned-clip
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_clip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_clip_pipeline_en.md
new file mode 100644
index 00000000000000..0206bc74e19042
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_clip_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_clip_pipeline pipeline CLIPForZeroShotClassification from saiabhishek-itta
+author: John Snow Labs
+name: fine_tuned_clip_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_clip_pipeline` is a English model originally trained by saiabhishek-itta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_clip_pipeline_en_5.5.0_3.0_1725456441048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_clip_pipeline_en_5.5.0_3.0_1725456441048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_clip_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_clip_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_clip_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/saiabhishek-itta/fine-tuned-clip
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_distilbert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_distilbert_base_uncased_en.md
new file mode 100644
index 00000000000000..1b3f57e55c2adf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_distilbert_base_uncased_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English fine_tuned_distilbert_base_uncased DistilBertForSequenceClassification from bright1
+author: John Snow Labs
+name: fine_tuned_distilbert_base_uncased
+date: 2024-09-04
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_distilbert_base_uncased` is a English model originally trained by bright1.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_base_uncased_en_5.5.0_3.0_1725466542281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_base_uncased_en_5.5.0_3.0_1725466542281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = DistilBertForSequenceClassification.pretrained("fine_tuned_distilbert_base_uncased","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("fine_tuned_distilbert_base_uncased","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_distilbert_base_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|255.8 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/bright1/fine-tuned-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_distilbert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_distilbert_base_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..6fd20847c481c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_distilbert_base_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_distilbert_base_uncased_pipeline pipeline CamemBertForSequenceClassification from hichamH
+author: John Snow Labs
+name: fine_tuned_distilbert_base_uncased_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_distilbert_base_uncased_pipeline` is a English model originally trained by hichamH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_base_uncased_pipeline_en_5.5.0_3.0_1725466554054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_base_uncased_pipeline_en_5.5.0_3.0_1725466554054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_distilbert_base_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_distilbert_base_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_distilbert_base_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|255.8 MB|
+
+## References
+
+https://huggingface.co/hichamH/fine-tuned-distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_mdeberta_category_by_notes_synthetic_en.md b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_mdeberta_category_by_notes_synthetic_en.md
new file mode 100644
index 00000000000000..8c07ee6661a96b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_mdeberta_category_by_notes_synthetic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_mdeberta_category_by_notes_synthetic DeBertaForSequenceClassification from adhityaprimandhika
+author: John Snow Labs
+name: fine_tuned_mdeberta_category_by_notes_synthetic
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_mdeberta_category_by_notes_synthetic` is a English model originally trained by adhityaprimandhika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_mdeberta_category_by_notes_synthetic_en_5.5.0_3.0_1725461850450.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_mdeberta_category_by_notes_synthetic_en_5.5.0_3.0_1725461850450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("fine_tuned_mdeberta_category_by_notes_synthetic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("fine_tuned_mdeberta_category_by_notes_synthetic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_mdeberta_category_by_notes_synthetic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|805.5 MB|
+
+## References
+
+https://huggingface.co/adhityaprimandhika/fine-tuned-mdeberta-category-by-notes-synthetic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_mdeberta_category_by_notes_synthetic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_mdeberta_category_by_notes_synthetic_pipeline_en.md
new file mode 100644
index 00000000000000..7ebd43feb2c2d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_mdeberta_category_by_notes_synthetic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_mdeberta_category_by_notes_synthetic_pipeline pipeline DeBertaForSequenceClassification from adhityaprimandhika
+author: John Snow Labs
+name: fine_tuned_mdeberta_category_by_notes_synthetic_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_mdeberta_category_by_notes_synthetic_pipeline` is a English model originally trained by adhityaprimandhika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_mdeberta_category_by_notes_synthetic_pipeline_en_5.5.0_3.0_1725461965455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_mdeberta_category_by_notes_synthetic_pipeline_en_5.5.0_3.0_1725461965455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_mdeberta_category_by_notes_synthetic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_mdeberta_category_by_notes_synthetic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_mdeberta_category_by_notes_synthetic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|805.5 MB|
+
+## References
+
+https://huggingface.co/adhityaprimandhika/fine-tuned-mdeberta-category-by-notes-synthetic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_model_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_model_1_en.md
new file mode 100644
index 00000000000000..2f3fb6d8a788b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fine_tuned_model_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_model_1 AlbertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: fine_tuned_model_1
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_model_1` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_model_1_en_5.5.0_3.0_1725464889509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_model_1_en_5.5.0_3.0_1725464889509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("fine_tuned_model_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("fine_tuned_model_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_model_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/fine_tuned_model_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-finer_distillbert_en.md b/docs/_posts/ahmedlone127/2024-09-04-finer_distillbert_en.md
new file mode 100644
index 00000000000000..f17e4aee762170
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-finer_distillbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finer_distillbert DistilBertForTokenClassification from HariLuru
+author: John Snow Labs
+name: finer_distillbert
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finer_distillbert` is a English model originally trained by HariLuru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finer_distillbert_en_5.5.0_3.0_1725448813033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finer_distillbert_en_5.5.0_3.0_1725448813033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("finer_distillbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("finer_distillbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finer_distillbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/HariLuru/finer_distillbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-finer_distillbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-finer_distillbert_pipeline_en.md
new file mode 100644
index 00000000000000..9510b53aafa906
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-finer_distillbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finer_distillbert_pipeline pipeline DistilBertForTokenClassification from HariLuru
+author: John Snow Labs
+name: finer_distillbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finer_distillbert_pipeline` is a English model originally trained by HariLuru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finer_distillbert_pipeline_en_5.5.0_3.0_1725448825533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finer_distillbert_pipeline_en_5.5.0_3.0_1725448825533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finer_distillbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finer_distillbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finer_distillbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/HariLuru/finer_distillbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-finetuned_ai4bharat_en.md b/docs/_posts/ahmedlone127/2024-09-04-finetuned_ai4bharat_en.md
new file mode 100644
index 00000000000000..57292dc1c9e667
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-finetuned_ai4bharat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_ai4bharat AlbertEmbeddings from anujsahani01
+author: John Snow Labs
+name: finetuned_ai4bharat
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ai4bharat` is a English model originally trained by anujsahani01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ai4bharat_en_5.5.0_3.0_1725435553618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ai4bharat_en_5.5.0_3.0_1725435553618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("finetuned_ai4bharat","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("finetuned_ai4bharat","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_ai4bharat|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|125.5 MB|
+
+## References
+
+https://huggingface.co/anujsahani01/finetuned_AI4Bharat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-finetuned_ai4bharat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-finetuned_ai4bharat_pipeline_en.md
new file mode 100644
index 00000000000000..074ccef791dc27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-finetuned_ai4bharat_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_ai4bharat_pipeline pipeline AlbertEmbeddings from anujsahani01
+author: John Snow Labs
+name: finetuned_ai4bharat_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ai4bharat_pipeline` is a English model originally trained by anujsahani01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ai4bharat_pipeline_en_5.5.0_3.0_1725435559940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ai4bharat_pipeline_en_5.5.0_3.0_1725435559940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_ai4bharat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_ai4bharat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_ai4bharat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|125.5 MB|
+
+## References
+
+https://huggingface.co/anujsahani01/finetuned_AI4Bharat
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline_en.md
new file mode 100644
index 00000000000000..0c3341fe349fd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline pipeline DistilBertEmbeddings from hanyuany14
+author: John Snow Labs
+name: finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline` is a English model originally trained by hanyuany14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline_en_5.5.0_3.0_1725413783843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline_en_5.5.0_3.0_1725413783843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_dscs24_mitre_distilbert_base_uncased_fill_mask_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/hanyuany14/finetuned-DSCS24-mitre-distilbert-base-uncased-fill-mask
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-finetuned_sail2017_indic_bert_en.md b/docs/_posts/ahmedlone127/2024-09-04-finetuned_sail2017_indic_bert_en.md
new file mode 100644
index 00000000000000..afd1a3cc1721d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-finetuned_sail2017_indic_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_sail2017_indic_bert AlbertForSequenceClassification from aditeyabaral
+author: John Snow Labs
+name: finetuned_sail2017_indic_bert
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sail2017_indic_bert` is a English model originally trained by aditeyabaral.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sail2017_indic_bert_en_5.5.0_3.0_1725488276560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sail2017_indic_bert_en_5.5.0_3.0_1725488276560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("finetuned_sail2017_indic_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("finetuned_sail2017_indic_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_sail2017_indic_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/aditeyabaral/finetuned-sail2017-indic-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-finetunedclip_en.md b/docs/_posts/ahmedlone127/2024-09-04-finetunedclip_en.md
new file mode 100644
index 00000000000000..cc3df4e0a34e62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-finetunedclip_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English finetunedclip CLIPForZeroShotClassification from homiehari
+author: John Snow Labs
+name: finetunedclip
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetunedclip` is a English model originally trained by homiehari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetunedclip_en_5.5.0_3.0_1725456471106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetunedclip_en_5.5.0_3.0_1725456471106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("finetunedclip","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("finetunedclip","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetunedclip|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|567.3 MB|
+
+## References
+
+https://huggingface.co/homiehari/finetunedCLIP
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-finetuning_sentiment_model_3000_samples_carlodallaquercia_en.md b/docs/_posts/ahmedlone127/2024-09-04-finetuning_sentiment_model_3000_samples_carlodallaquercia_en.md
new file mode 100644
index 00000000000000..620f0de31582b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-finetuning_sentiment_model_3000_samples_carlodallaquercia_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_carlodallaquercia DistilBertForSequenceClassification from carlodallaquercia
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_carlodallaquercia
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_carlodallaquercia` is a English model originally trained by carlodallaquercia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_carlodallaquercia_en_5.5.0_3.0_1725490082362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_carlodallaquercia_en_5.5.0_3.0_1725490082362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_carlodallaquercia","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_carlodallaquercia", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_carlodallaquercia|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/carlodallaquercia/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fnctech_en.md b/docs/_posts/ahmedlone127/2024-09-04-fnctech_en.md
new file mode 100644
index 00000000000000..a4ec1798dad7ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fnctech_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fnctech MPNetEmbeddings from bchan007
+author: John Snow Labs
+name: fnctech
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fnctech` is a English model originally trained by bchan007.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fnctech_en_5.5.0_3.0_1725470489608.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fnctech_en_5.5.0_3.0_1725470489608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("fnctech","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("fnctech","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fnctech|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/bchan007/fnctech
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fralbert_base_cased_fr.md b/docs/_posts/ahmedlone127/2024-09-04-fralbert_base_cased_fr.md
new file mode 100644
index 00000000000000..c86d8aa054c697
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fralbert_base_cased_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French fralbert_base_cased AlbertEmbeddings from cservan
+author: John Snow Labs
+name: fralbert_base_cased
+date: 2024-09-04
+tags: [fr, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fralbert_base_cased` is a French model originally trained by cservan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fralbert_base_cased_fr_5.5.0_3.0_1725435230520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fralbert_base_cased_fr_5.5.0_3.0_1725435230520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("fralbert_base_cased","fr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("fralbert_base_cased","fr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fralbert_base_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|fr|
+|Size:|42.8 MB|
+
+## References
+
+https://huggingface.co/cservan/fralbert-base-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-fralbert_base_cased_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-04-fralbert_base_cased_pipeline_fr.md
new file mode 100644
index 00000000000000..e488975ac607d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-fralbert_base_cased_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French fralbert_base_cased_pipeline pipeline AlbertEmbeddings from cservan
+author: John Snow Labs
+name: fralbert_base_cased_pipeline
+date: 2024-09-04
+tags: [fr, open_source, pipeline, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fralbert_base_cased_pipeline` is a French model originally trained by cservan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fralbert_base_cased_pipeline_fr_5.5.0_3.0_1725435232972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fralbert_base_cased_pipeline_fr_5.5.0_3.0_1725435232972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fralbert_base_cased_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fralbert_base_cased_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fralbert_base_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|42.8 MB|
+
+## References
+
+https://huggingface.co/cservan/fralbert-base-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-furina_with_transliteration_minangkabau_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-furina_with_transliteration_minangkabau_pipeline_en.md
new file mode 100644
index 00000000000000..018f91b60e6c26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-furina_with_transliteration_minangkabau_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English furina_with_transliteration_minangkabau_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: furina_with_transliteration_minangkabau_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`furina_with_transliteration_minangkabau_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/furina_with_transliteration_minangkabau_pipeline_en_5.5.0_3.0_1725417857455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/furina_with_transliteration_minangkabau_pipeline_en_5.5.0_3.0_1725417857455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("furina_with_transliteration_minangkabau_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("furina_with_transliteration_minangkabau_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|furina_with_transliteration_minangkabau_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/furina-with-transliteration-min
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-gdpr_anonymiseingsmodel_ganm_en.md b/docs/_posts/ahmedlone127/2024-09-04-gdpr_anonymiseingsmodel_ganm_en.md
new file mode 100644
index 00000000000000..dbf719974589ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-gdpr_anonymiseingsmodel_ganm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gdpr_anonymiseingsmodel_ganm BertForTokenClassification from AI-aktindsigt
+author: John Snow Labs
+name: gdpr_anonymiseingsmodel_ganm
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gdpr_anonymiseingsmodel_ganm` is a English model originally trained by AI-aktindsigt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gdpr_anonymiseingsmodel_ganm_en_5.5.0_3.0_1725477941347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gdpr_anonymiseingsmodel_ganm_en_5.5.0_3.0_1725477941347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("gdpr_anonymiseingsmodel_ganm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("gdpr_anonymiseingsmodel_ganm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gdpr_anonymiseingsmodel_ganm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|666.0 MB|
+
+## References
+
+https://huggingface.co/AI-aktindsigt/gdpr_anonymiseingsmodel_ganm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-geolm_base_toponym_recognition_en.md b/docs/_posts/ahmedlone127/2024-09-04-geolm_base_toponym_recognition_en.md
new file mode 100644
index 00000000000000..4c435d915e4043
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-geolm_base_toponym_recognition_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English geolm_base_toponym_recognition BertForTokenClassification from zekun-li
+author: John Snow Labs
+name: geolm_base_toponym_recognition
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`geolm_base_toponym_recognition` is a English model originally trained by zekun-li.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/geolm_base_toponym_recognition_en_5.5.0_3.0_1725449974577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/geolm_base_toponym_recognition_en_5.5.0_3.0_1725449974577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("geolm_base_toponym_recognition","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("geolm_base_toponym_recognition", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|geolm_base_toponym_recognition|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/zekun-li/geolm-base-toponym-recognition
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-gptops_finetuned_mpnet_gpu_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-gptops_finetuned_mpnet_gpu_v1_en.md
new file mode 100644
index 00000000000000..0592484dfdf1af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-gptops_finetuned_mpnet_gpu_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gptops_finetuned_mpnet_gpu_v1 MPNetEmbeddings from sembeddings
+author: John Snow Labs
+name: gptops_finetuned_mpnet_gpu_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gptops_finetuned_mpnet_gpu_v1` is a English model originally trained by sembeddings.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gptops_finetuned_mpnet_gpu_v1_en_5.5.0_3.0_1725470236148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gptops_finetuned_mpnet_gpu_v1_en_5.5.0_3.0_1725470236148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("gptops_finetuned_mpnet_gpu_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("gptops_finetuned_mpnet_gpu_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gptops_finetuned_mpnet_gpu_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/sembeddings/gptops_finetuned_mpnet_gpu_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-gptops_finetuned_mpnet_gpu_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-gptops_finetuned_mpnet_gpu_v1_pipeline_en.md
new file mode 100644
index 00000000000000..9b85f5b6893a64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-gptops_finetuned_mpnet_gpu_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gptops_finetuned_mpnet_gpu_v1_pipeline pipeline MPNetEmbeddings from sembeddings
+author: John Snow Labs
+name: gptops_finetuned_mpnet_gpu_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gptops_finetuned_mpnet_gpu_v1_pipeline` is a English model originally trained by sembeddings.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gptops_finetuned_mpnet_gpu_v1_pipeline_en_5.5.0_3.0_1725470258144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gptops_finetuned_mpnet_gpu_v1_pipeline_en_5.5.0_3.0_1725470258144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gptops_finetuned_mpnet_gpu_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gptops_finetuned_mpnet_gpu_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gptops_finetuned_mpnet_gpu_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/sembeddings/gptops_finetuned_mpnet_gpu_v1
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-gqa_roberta_german_legal_squad_2000_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-04-gqa_roberta_german_legal_squad_2000_pipeline_de.md
new file mode 100644
index 00000000000000..5837a2c60992db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-gqa_roberta_german_legal_squad_2000_pipeline_de.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: German gqa_roberta_german_legal_squad_2000_pipeline pipeline RoBertaForQuestionAnswering from farid1088
+author: John Snow Labs
+name: gqa_roberta_german_legal_squad_2000_pipeline
+date: 2024-09-04
+tags: [de, open_source, pipeline, onnx]
+task: Question Answering
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gqa_roberta_german_legal_squad_2000_pipeline` is a German model originally trained by farid1088.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gqa_roberta_german_legal_squad_2000_pipeline_de_5.5.0_3.0_1725479764866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gqa_roberta_german_legal_squad_2000_pipeline_de_5.5.0_3.0_1725479764866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gqa_roberta_german_legal_squad_2000_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gqa_roberta_german_legal_squad_2000_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gqa_roberta_german_legal_squad_2000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|465.8 MB|
+
+## References
+
+https://huggingface.co/farid1088/GQA_RoBERTa_German_legal_SQuAD_2000
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline_en.md
new file mode 100644
index 00000000000000..0c1679c317db3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline pipeline DeBertaForSequenceClassification from SiddharthaM
+author: John Snow Labs
+name: hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline` is a English model originally trained by SiddharthaM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline_en_5.5.0_3.0_1725463404640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline_en_5.5.0_3.0_1725463404640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hasoc19_microsoft_mdeberta_v3_base_sentiment_nepal_bhasa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|815.4 MB|
+
+## References
+
+https://huggingface.co/SiddharthaM/hasoc19-microsoft-mdeberta-v3-base-sentiment-new
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-hiyoshi_street_clip_en.md b/docs/_posts/ahmedlone127/2024-09-04-hiyoshi_street_clip_en.md
new file mode 100644
index 00000000000000..5ccfa694622373
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-hiyoshi_street_clip_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English hiyoshi_street_clip CLIPForZeroShotClassification from fummicc1
+author: John Snow Labs
+name: hiyoshi_street_clip
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hiyoshi_street_clip` is a English model originally trained by fummicc1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hiyoshi_street_clip_en_5.5.0_3.0_1725490764506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hiyoshi_street_clip_en_5.5.0_3.0_1725490764506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("hiyoshi_street_clip","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("hiyoshi_street_clip","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hiyoshi_street_clip|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/fummicc1/hiyoshi-street-clip
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-hiyoshi_street_clip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-hiyoshi_street_clip_pipeline_en.md
new file mode 100644
index 00000000000000..f90175894ad791
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-hiyoshi_street_clip_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hiyoshi_street_clip_pipeline pipeline CLIPForZeroShotClassification from fummicc1
+author: John Snow Labs
+name: hiyoshi_street_clip_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hiyoshi_street_clip_pipeline` is a English model originally trained by fummicc1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hiyoshi_street_clip_pipeline_en_5.5.0_3.0_1725490840619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hiyoshi_street_clip_pipeline_en_5.5.0_3.0_1725490840619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hiyoshi_street_clip_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hiyoshi_street_clip_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hiyoshi_street_clip_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/fummicc1/hiyoshi-street-clip
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-hw01_hamsty_en.md b/docs/_posts/ahmedlone127/2024-09-04-hw01_hamsty_en.md
new file mode 100644
index 00000000000000..71d84216037097
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-hw01_hamsty_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hw01_hamsty DistilBertForSequenceClassification from hamsty
+author: John Snow Labs
+name: hw01_hamsty
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw01_hamsty` is a English model originally trained by hamsty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw01_hamsty_en_5.5.0_3.0_1725490174002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw01_hamsty_en_5.5.0_3.0_1725490174002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("hw01_hamsty","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("hw01_hamsty", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw01_hamsty|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hamsty/HW01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-hw_intent_atis_en.md b/docs/_posts/ahmedlone127/2024-09-04-hw_intent_atis_en.md
new file mode 100644
index 00000000000000..881fac26973aa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-hw_intent_atis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hw_intent_atis RoBertaForSequenceClassification from RaushanTurganbay
+author: John Snow Labs
+name: hw_intent_atis
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw_intent_atis` is a English model originally trained by RaushanTurganbay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw_intent_atis_en_5.5.0_3.0_1725484995127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw_intent_atis_en_5.5.0_3.0_1725484995127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("hw_intent_atis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("hw_intent_atis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw_intent_atis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|422.6 MB|
+
+## References
+
+https://huggingface.co/RaushanTurganbay/hw-intent-atis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-icebert_large_is.md b/docs/_posts/ahmedlone127/2024-09-04-icebert_large_is.md
new file mode 100644
index 00000000000000..2b90553ac0dddd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-icebert_large_is.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Icelandic icebert_large RoBertaEmbeddings from mideind
+author: John Snow Labs
+name: icebert_large
+date: 2024-09-04
+tags: [is, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: is
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`icebert_large` is a Icelandic model originally trained by mideind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/icebert_large_is_5.5.0_3.0_1725413087413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/icebert_large_is_5.5.0_3.0_1725413087413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("icebert_large","is") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("icebert_large","is") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|icebert_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|is|
+|Size:|844.2 MB|
+
+## References
+
+https://huggingface.co/mideind/IceBERT-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-icebert_large_pipeline_is.md b/docs/_posts/ahmedlone127/2024-09-04-icebert_large_pipeline_is.md
new file mode 100644
index 00000000000000..313cca20c90f7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-icebert_large_pipeline_is.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Icelandic icebert_large_pipeline pipeline RoBertaEmbeddings from mideind
+author: John Snow Labs
+name: icebert_large_pipeline
+date: 2024-09-04
+tags: [is, open_source, pipeline, onnx]
+task: Embeddings
+language: is
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`icebert_large_pipeline` is a Icelandic model originally trained by mideind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/icebert_large_pipeline_is_5.5.0_3.0_1725413341044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/icebert_large_pipeline_is_5.5.0_3.0_1725413341044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("icebert_large_pipeline", lang = "is")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("icebert_large_pipeline", lang = "is")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|icebert_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|is|
+|Size:|844.3 MB|
+
+## References
+
+https://huggingface.co/mideind/IceBERT-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-icelandic_title_setfit_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-icelandic_title_setfit_pipeline_en.md
new file mode 100644
index 00000000000000..efbf8e96806273
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-icelandic_title_setfit_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English icelandic_title_setfit_pipeline pipeline MPNetEmbeddings from AlekseyKorshuk
+author: John Snow Labs
+name: icelandic_title_setfit_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`icelandic_title_setfit_pipeline` is a English model originally trained by AlekseyKorshuk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/icelandic_title_setfit_pipeline_en_5.5.0_3.0_1725470417482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/icelandic_title_setfit_pipeline_en_5.5.0_3.0_1725470417482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("icelandic_title_setfit_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("icelandic_title_setfit_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|icelandic_title_setfit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/AlekseyKorshuk/is-title-setfit
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-imdb_review_sentiement_en.md b/docs/_posts/ahmedlone127/2024-09-04-imdb_review_sentiement_en.md
new file mode 100644
index 00000000000000..07c4e38bfbe4a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-imdb_review_sentiement_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imdb_review_sentiement DistilBertForSequenceClassification from santiadavani
+author: John Snow Labs
+name: imdb_review_sentiement
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_review_sentiement` is a English model originally trained by santiadavani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_review_sentiement_en_5.5.0_3.0_1725490016233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_review_sentiement_en_5.5.0_3.0_1725490016233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("imdb_review_sentiement","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdb_review_sentiement", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdb_review_sentiement|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/santiadavani/imdb_review_sentiement
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-indic_bert_finetuned_trac_ds_en.md b/docs/_posts/ahmedlone127/2024-09-04-indic_bert_finetuned_trac_ds_en.md
new file mode 100644
index 00000000000000..30fb1ed34aab60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-indic_bert_finetuned_trac_ds_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_finetuned_trac_ds AlbertForSequenceClassification from IIIT-L
+author: John Snow Labs
+name: indic_bert_finetuned_trac_ds
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_finetuned_trac_ds` is a English model originally trained by IIIT-L.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_trac_ds_en_5.5.0_3.0_1725488507805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_trac_ds_en_5.5.0_3.0_1725488507805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_finetuned_trac_ds","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_finetuned_trac_ds", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_finetuned_trac_ds|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/IIIT-L/indic-bert-finetuned-TRAC-DS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-indicbert_hindi_urdu_en.md b/docs/_posts/ahmedlone127/2024-09-04-indicbert_hindi_urdu_en.md
new file mode 100644
index 00000000000000..fbb7d2f4bac7b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-indicbert_hindi_urdu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indicbert_hindi_urdu AlbertForTokenClassification from anwesham
+author: John Snow Labs
+name: indicbert_hindi_urdu
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, albert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indicbert_hindi_urdu` is a English model originally trained by anwesham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indicbert_hindi_urdu_en_5.5.0_3.0_1725486913841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indicbert_hindi_urdu_en_5.5.0_3.0_1725486913841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = AlbertForTokenClassification.pretrained("indicbert_hindi_urdu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = AlbertForTokenClassification.pretrained("indicbert_hindi_urdu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indicbert_hindi_urdu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|125.6 MB|
+
+## References
+
+https://huggingface.co/anwesham/indicbert_hi_ur
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-indicbert_urdu_en.md b/docs/_posts/ahmedlone127/2024-09-04-indicbert_urdu_en.md
new file mode 100644
index 00000000000000..535f8df4cb6180
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-indicbert_urdu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indicbert_urdu AlbertForTokenClassification from anwesham
+author: John Snow Labs
+name: indicbert_urdu
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, albert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indicbert_urdu` is a English model originally trained by anwesham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indicbert_urdu_en_5.5.0_3.0_1725486622169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indicbert_urdu_en_5.5.0_3.0_1725486622169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = AlbertForTokenClassification.pretrained("indicbert_urdu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = AlbertForTokenClassification.pretrained("indicbert_urdu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indicbert_urdu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|125.6 MB|
+
+## References
+
+https://huggingface.co/anwesham/indicbert_ur
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-indojave_codemixed_roberta_base_id.md b/docs/_posts/ahmedlone127/2024-09-04-indojave_codemixed_roberta_base_id.md
new file mode 100644
index 00000000000000..2b622a82543edf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-indojave_codemixed_roberta_base_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian indojave_codemixed_roberta_base RoBertaEmbeddings from fathan
+author: John Snow Labs
+name: indojave_codemixed_roberta_base
+date: 2024-09-04
+tags: [id, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indojave_codemixed_roberta_base` is a Indonesian model originally trained by fathan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indojave_codemixed_roberta_base_id_5.5.0_3.0_1725412533212.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indojave_codemixed_roberta_base_id_5.5.0_3.0_1725412533212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("indojave_codemixed_roberta_base","id") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("indojave_codemixed_roberta_base","id") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indojave_codemixed_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|id|
+|Size:|471.0 MB|
+
+## References
+
+https://huggingface.co/fathan/indojave-codemixed-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-indonesian_punctuation_en.md b/docs/_posts/ahmedlone127/2024-09-04-indonesian_punctuation_en.md
new file mode 100644
index 00000000000000..c585843d4d3451
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-indonesian_punctuation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indonesian_punctuation AlbertForTokenClassification from Wikidepia
+author: John Snow Labs
+name: indonesian_punctuation
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, albert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_punctuation` is a English model originally trained by Wikidepia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_punctuation_en_5.5.0_3.0_1725486983862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_punctuation_en_5.5.0_3.0_1725486983862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = AlbertForTokenClassification.pretrained("indonesian_punctuation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = AlbertForTokenClassification.pretrained("indonesian_punctuation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_punctuation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|21.3 MB|
+
+## References
+
+https://huggingface.co/Wikidepia/indonesian-punctuation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-iotnation_companyname_extraction_qa_model_1_2_roberta_en.md b/docs/_posts/ahmedlone127/2024-09-04-iotnation_companyname_extraction_qa_model_1_2_roberta_en.md
new file mode 100644
index 00000000000000..2f4609589304d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-iotnation_companyname_extraction_qa_model_1_2_roberta_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English iotnation_companyname_extraction_qa_model_1_2_roberta RoBertaForQuestionAnswering from chriskim2273
+author: John Snow Labs
+name: iotnation_companyname_extraction_qa_model_1_2_roberta
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iotnation_companyname_extraction_qa_model_1_2_roberta` is a English model originally trained by chriskim2273.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iotnation_companyname_extraction_qa_model_1_2_roberta_en_5.5.0_3.0_1725484085175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iotnation_companyname_extraction_qa_model_1_2_roberta_en_5.5.0_3.0_1725484085175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("iotnation_companyname_extraction_qa_model_1_2_roberta","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("iotnation_companyname_extraction_qa_model_1_2_roberta", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iotnation_companyname_extraction_qa_model_1_2_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.7 MB|
+
+## References
+
+https://huggingface.co/chriskim2273/IOTNation_CompanyName_Extraction_QA_Model_1.2_Roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-isy503_sentiment_analysis2_aliatik66_en.md b/docs/_posts/ahmedlone127/2024-09-04-isy503_sentiment_analysis2_aliatik66_en.md
new file mode 100644
index 00000000000000..174aa08c1f41fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-isy503_sentiment_analysis2_aliatik66_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English isy503_sentiment_analysis2_aliatik66 DistilBertForSequenceClassification from aliatik66
+author: John Snow Labs
+name: isy503_sentiment_analysis2_aliatik66
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`isy503_sentiment_analysis2_aliatik66` is a English model originally trained by aliatik66.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/isy503_sentiment_analysis2_aliatik66_en_5.5.0_3.0_1725490022308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/isy503_sentiment_analysis2_aliatik66_en_5.5.0_3.0_1725490022308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("isy503_sentiment_analysis2_aliatik66","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("isy503_sentiment_analysis2_aliatik66", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|isy503_sentiment_analysis2_aliatik66|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aliatik66/ISY503-sentiment_analysis2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-isy503_sentiment_analysis2_aliatik66_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-isy503_sentiment_analysis2_aliatik66_pipeline_en.md
new file mode 100644
index 00000000000000..016e651937e93f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-isy503_sentiment_analysis2_aliatik66_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English isy503_sentiment_analysis2_aliatik66_pipeline pipeline DistilBertForSequenceClassification from aliatik66
+author: John Snow Labs
+name: isy503_sentiment_analysis2_aliatik66_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`isy503_sentiment_analysis2_aliatik66_pipeline` is a English model originally trained by aliatik66.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/isy503_sentiment_analysis2_aliatik66_pipeline_en_5.5.0_3.0_1725490034527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/isy503_sentiment_analysis2_aliatik66_pipeline_en_5.5.0_3.0_1725490034527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("isy503_sentiment_analysis2_aliatik66_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("isy503_sentiment_analysis2_aliatik66_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|isy503_sentiment_analysis2_aliatik66_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aliatik66/ISY503-sentiment_analysis2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-kalematech_arabic_stt_asr_based_on_whisper_small_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-kalematech_arabic_stt_asr_based_on_whisper_small_pipeline_ar.md
new file mode 100644
index 00000000000000..38f0d5fb1ec837
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-kalematech_arabic_stt_asr_based_on_whisper_small_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic kalematech_arabic_stt_asr_based_on_whisper_small_pipeline pipeline WhisperForCTC from Salama1429
+author: John Snow Labs
+name: kalematech_arabic_stt_asr_based_on_whisper_small_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kalematech_arabic_stt_asr_based_on_whisper_small_pipeline` is a Arabic model originally trained by Salama1429.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kalematech_arabic_stt_asr_based_on_whisper_small_pipeline_ar_5.5.0_3.0_1725429350966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kalematech_arabic_stt_asr_based_on_whisper_small_pipeline_ar_5.5.0_3.0_1725429350966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kalematech_arabic_stt_asr_based_on_whisper_small_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kalematech_arabic_stt_asr_based_on_whisper_small_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kalematech_arabic_stt_asr_based_on_whisper_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-kamal_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-04-kamal_camembert_en.md
new file mode 100644
index 00000000000000..393d356c272e96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-kamal_camembert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kamal_camembert CamemBertEmbeddings from nskamal
+author: John Snow Labs
+name: kamal_camembert
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kamal_camembert` is a English model originally trained by nskamal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kamal_camembert_en_5.5.0_3.0_1725408783081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kamal_camembert_en_5.5.0_3.0_1725408783081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("kamal_camembert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("kamal_camembert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kamal_camembert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nskamal/kamal_camembert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-kamal_camembert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-kamal_camembert_pipeline_en.md
new file mode 100644
index 00000000000000..c0174c84102f95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-kamal_camembert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kamal_camembert_pipeline pipeline CamemBertEmbeddings from nskamal
+author: John Snow Labs
+name: kamal_camembert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kamal_camembert_pipeline` is a English model originally trained by nskamal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kamal_camembert_pipeline_en_5.5.0_3.0_1725408864022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kamal_camembert_pipeline_en_5.5.0_3.0_1725408864022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kamal_camembert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kamal_camembert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kamal_camembert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nskamal/kamal_camembert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-kanberto_kn.md b/docs/_posts/ahmedlone127/2024-09-04-kanberto_kn.md
new file mode 100644
index 00000000000000..664ad18cba9926
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-kanberto_kn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Kannada kanberto RoBertaEmbeddings from Naveen-k
+author: John Snow Labs
+name: kanberto
+date: 2024-09-04
+tags: [kn, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: kn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kanberto` is a Kannada model originally trained by Naveen-k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kanberto_kn_5.5.0_3.0_1725412308197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kanberto_kn_5.5.0_3.0_1725412308197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("kanberto","kn") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("kanberto","kn") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kanberto|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|kn|
+|Size:|311.8 MB|
+
+## References
+
+https://huggingface.co/Naveen-k/KanBERTo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-kaviel_threat_text_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-kaviel_threat_text_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..4df43d70ce67ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-kaviel_threat_text_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kaviel_threat_text_classifier_pipeline pipeline RoBertaForSequenceClassification from HiddenKise
+author: John Snow Labs
+name: kaviel_threat_text_classifier_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kaviel_threat_text_classifier_pipeline` is a English model originally trained by HiddenKise.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kaviel_threat_text_classifier_pipeline_en_5.5.0_3.0_1725485930371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kaviel_threat_text_classifier_pipeline_en_5.5.0_3.0_1725485930371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kaviel_threat_text_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kaviel_threat_text_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kaviel_threat_text_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|416.1 MB|
+
+## References
+
+https://huggingface.co/HiddenKise/Kaviel-threat-text-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..feebc2c2cb60de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline pipeline DistilBertForTokenClassification from jaggernaut007
+author: John Snow Labs
+name: keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline` is a English model originally trained by jaggernaut007.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline_en_5.5.0_3.0_1725492573941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline_en_5.5.0_3.0_1725492573941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keyphrase_extraction_distilbert_inspec_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.7 MB|
+
+## References
+
+https://huggingface.co/jaggernaut007/keyphrase-extraction-distilbert-inspec-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-kor_naver_ner_name_v2_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-kor_naver_ner_name_v2_1_pipeline_en.md
new file mode 100644
index 00000000000000..a69ef84435544d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-kor_naver_ner_name_v2_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kor_naver_ner_name_v2_1_pipeline pipeline BertForTokenClassification from joon09
+author: John Snow Labs
+name: kor_naver_ner_name_v2_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kor_naver_ner_name_v2_1_pipeline` is a English model originally trained by joon09.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kor_naver_ner_name_v2_1_pipeline_en_5.5.0_3.0_1725449625842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kor_naver_ner_name_v2_1_pipeline_en_5.5.0_3.0_1725449625842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kor_naver_ner_name_v2_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kor_naver_ner_name_v2_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kor_naver_ner_name_v2_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|441.3 MB|
+
+## References
+
+https://huggingface.co/joon09/kor-naver-ner-name-v2.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-legal_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-legal_roberta_large_pipeline_en.md
new file mode 100644
index 00000000000000..94a44849e723a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-legal_roberta_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English legal_roberta_large_pipeline pipeline RoBertaEmbeddings from lexlms
+author: John Snow Labs
+name: legal_roberta_large_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_roberta_large_pipeline` is a English model originally trained by lexlms.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_roberta_large_pipeline_en_5.5.0_3.0_1725412397286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_roberta_large_pipeline_en_5.5.0_3.0_1725412397286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legal_roberta_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legal_roberta_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_roberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/lexlms/legal-roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-legal_xlm_roberta_large_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-04-legal_xlm_roberta_large_pipeline_xx.md
new file mode 100644
index 00000000000000..f24ebbb053e1f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-legal_xlm_roberta_large_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual legal_xlm_roberta_large_pipeline pipeline RoBertaEmbeddings from joelniklaus
+author: John Snow Labs
+name: legal_xlm_roberta_large_pipeline
+date: 2024-09-04
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_xlm_roberta_large_pipeline` is a Multilingual model originally trained by joelniklaus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_xlm_roberta_large_pipeline_xx_5.5.0_3.0_1725413327209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_xlm_roberta_large_pipeline_xx_5.5.0_3.0_1725413327209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legal_xlm_roberta_large_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legal_xlm_roberta_large_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_xlm_roberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/joelniklaus/legal-xlm-roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-legal_xlm_roberta_large_xx.md b/docs/_posts/ahmedlone127/2024-09-04-legal_xlm_roberta_large_xx.md
new file mode 100644
index 00000000000000..bb1efdbd41e4e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-legal_xlm_roberta_large_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual legal_xlm_roberta_large RoBertaEmbeddings from joelniklaus
+author: John Snow Labs
+name: legal_xlm_roberta_large
+date: 2024-09-04
+tags: [xx, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_xlm_roberta_large` is a Multilingual model originally trained by joelniklaus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_xlm_roberta_large_xx_5.5.0_3.0_1725413246394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_xlm_roberta_large_xx_5.5.0_3.0_1725413246394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("legal_xlm_roberta_large","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("legal_xlm_roberta_large","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_xlm_roberta_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|xx|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/joelniklaus/legal-xlm-roberta-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-lenu_dutch_en.md b/docs/_posts/ahmedlone127/2024-09-04-lenu_dutch_en.md
new file mode 100644
index 00000000000000..abc7f405852770
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-lenu_dutch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lenu_dutch BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_dutch
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_dutch` is a English model originally trained by Sociovestix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_dutch_en_5.5.0_3.0_1725432675888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_dutch_en_5.5.0_3.0_1725432675888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("lenu_dutch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_dutch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_dutch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_NL
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-lenu_northern_sami_en.md b/docs/_posts/ahmedlone127/2024-09-04-lenu_northern_sami_en.md
new file mode 100644
index 00000000000000..cb507020394f25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-lenu_northern_sami_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lenu_northern_sami BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_northern_sami
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_northern_sami` is a English model originally trained by Sociovestix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_northern_sami_en_5.5.0_3.0_1725433097252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_northern_sami_en_5.5.0_3.0_1725433097252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("lenu_northern_sami","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_northern_sami", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_northern_sami|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_SE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-lenu_northern_sami_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-lenu_northern_sami_pipeline_en.md
new file mode 100644
index 00000000000000..651001e0a3767a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-lenu_northern_sami_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lenu_northern_sami_pipeline pipeline BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_northern_sami_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_northern_sami_pipeline` is a English model originally trained by Sociovestix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lenu_northern_sami_pipeline_en_5.5.0_3.0_1725433129838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_northern_sami_pipeline_en_5.5.0_3.0_1725433129838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lenu_northern_sami_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lenu_northern_sami_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_northern_sami_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_SE
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-llm_bert_model_based_skills_extraction_from_jobdescription_en.md b/docs/_posts/ahmedlone127/2024-09-04-llm_bert_model_based_skills_extraction_from_jobdescription_en.md
new file mode 100644
index 00000000000000..4bcb22bd640883
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-llm_bert_model_based_skills_extraction_from_jobdescription_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English llm_bert_model_based_skills_extraction_from_jobdescription DistilBertForTokenClassification from GalalEwida
+author: John Snow Labs
+name: llm_bert_model_based_skills_extraction_from_jobdescription
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_bert_model_based_skills_extraction_from_jobdescription` is a English model originally trained by GalalEwida.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_bert_model_based_skills_extraction_from_jobdescription_en_5.5.0_3.0_1725448541637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_bert_model_based_skills_extraction_from_jobdescription_en_5.5.0_3.0_1725448541637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("llm_bert_model_based_skills_extraction_from_jobdescription","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("llm_bert_model_based_skills_extraction_from_jobdescription", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llm_bert_model_based_skills_extraction_from_jobdescription|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/GalalEwida/LLM-BERT-Model-Based-Skills-Extraction-from-jobdescription
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-llm_bert_model_based_skills_extraction_from_jobdescription_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-llm_bert_model_based_skills_extraction_from_jobdescription_pipeline_en.md
new file mode 100644
index 00000000000000..b5dfec85ad2a23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-llm_bert_model_based_skills_extraction_from_jobdescription_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English llm_bert_model_based_skills_extraction_from_jobdescription_pipeline pipeline DistilBertForTokenClassification from GalalEwida
+author: John Snow Labs
+name: llm_bert_model_based_skills_extraction_from_jobdescription_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_bert_model_based_skills_extraction_from_jobdescription_pipeline` is a English model originally trained by GalalEwida.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_bert_model_based_skills_extraction_from_jobdescription_pipeline_en_5.5.0_3.0_1725448553625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_bert_model_based_skills_extraction_from_jobdescription_pipeline_en_5.5.0_3.0_1725448553625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("llm_bert_model_based_skills_extraction_from_jobdescription_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("llm_bert_model_based_skills_extraction_from_jobdescription_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llm_bert_model_based_skills_extraction_from_jobdescription_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/GalalEwida/LLM-BERT-Model-Based-Skills-Extraction-from-jobdescription
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-magbert_lm_en.md b/docs/_posts/ahmedlone127/2024-09-04-magbert_lm_en.md
new file mode 100644
index 00000000000000..7e77238b887e52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-magbert_lm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English magbert_lm CamemBertEmbeddings from TypicaAI
+author: John Snow Labs
+name: magbert_lm
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`magbert_lm` is a English model originally trained by TypicaAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/magbert_lm_en_5.5.0_3.0_1725442062270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/magbert_lm_en_5.5.0_3.0_1725442062270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("magbert_lm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("magbert_lm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|magbert_lm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|412.5 MB|
+
+## References
+
+https://huggingface.co/TypicaAI/magbert-lm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-maltese_coref_english_french_coref_exp_en.md b/docs/_posts/ahmedlone127/2024-09-04-maltese_coref_english_french_coref_exp_en.md
new file mode 100644
index 00000000000000..5c2e865d0f6c32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-maltese_coref_english_french_coref_exp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_coref_english_french_coref_exp MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_french_coref_exp
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_french_coref_exp` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_coref_exp_en_5.5.0_3.0_1725494380685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_coref_exp_en_5.5.0_3.0_1725494380685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_coref_english_french_coref_exp","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_coref_english_french_coref_exp","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_french_coref_exp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_fr_coref_exp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline_en.md
new file mode 100644
index 00000000000000..3b2d2e5b68754a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline pipeline MarianTransformer from Lingrui1
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline` is a English model originally trained by Lingrui1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline_en_5.5.0_3.0_1725493784199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline_en_5.5.0_3.0_1725493784199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_lingrui1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/Lingrui1/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098_en.md b/docs/_posts/ahmedlone127/2024-09-04-marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098_en.md
new file mode 100644
index 00000000000000..c395ce6bcf3b1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098 MarianTransformer from sooh098
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098` is a English model originally trained by sooh098.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098_en_5.5.0_3.0_1725493908365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098_en_5.5.0_3.0_1725493908365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_sooh098|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.2 MB|
+
+## References
+
+https://huggingface.co/sooh098/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-masking_heaps_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-masking_heaps_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..d0bf7780dd1d70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-masking_heaps_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English masking_heaps_distilbert_pipeline pipeline DistilBertEmbeddings from johannes-garstenauer
+author: John Snow Labs
+name: masking_heaps_distilbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`masking_heaps_distilbert_pipeline` is a English model originally trained by johannes-garstenauer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/masking_heaps_distilbert_pipeline_en_5.5.0_3.0_1725418294791.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/masking_heaps_distilbert_pipeline_en_5.5.0_3.0_1725418294791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("masking_heaps_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("masking_heaps_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|masking_heaps_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/johannes-garstenauer/masking-heaps-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_base_metaphor_detection_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_base_metaphor_detection_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..0736562ff8645c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_base_metaphor_detection_spanish_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish mdeberta_base_metaphor_detection_spanish_pipeline pipeline DeBertaForTokenClassification from HiTZ
+author: John Snow Labs
+name: mdeberta_base_metaphor_detection_spanish_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_metaphor_detection_spanish_pipeline` is a Castilian, Spanish model originally trained by HiTZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_base_metaphor_detection_spanish_pipeline_es_5.5.0_3.0_1725472502484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_metaphor_detection_spanish_pipeline_es_5.5.0_3.0_1725472502484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_base_metaphor_detection_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_base_metaphor_detection_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_base_metaphor_detection_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|846.8 MB|
+
+## References
+
+https://huggingface.co/HiTZ/mdeberta-base-metaphor-detection-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_base_v3_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_base_v3_4_pipeline_en.md
new file mode 100644
index 00000000000000..188e2918a3a4b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_base_v3_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_base_v3_4_pipeline pipeline DeBertaForSequenceClassification from alyazharr
+author: John Snow Labs
+name: mdeberta_base_v3_4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_v3_4_pipeline` is a English model originally trained by alyazharr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_base_v3_4_pipeline_en_5.5.0_3.0_1725438613615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_v3_4_pipeline_en_5.5.0_3.0_1725438613615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_base_v3_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_base_v3_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_base_v3_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|831.7 MB|
+
+## References
+
+https://huggingface.co/alyazharr/mdeberta_base_v3_4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v2_base_prompt_injections_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v2_base_prompt_injections_en.md
new file mode 100644
index 00000000000000..fba3509b1952cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v2_base_prompt_injections_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v2_base_prompt_injections DeBertaForSequenceClassification from Fan1018
+author: John Snow Labs
+name: mdeberta_v2_base_prompt_injections
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v2_base_prompt_injections` is a English model originally trained by Fan1018.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v2_base_prompt_injections_en_5.5.0_3.0_1725439247816.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v2_base_prompt_injections_en_5.5.0_3.0_1725439247816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v2_base_prompt_injections","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v2_base_prompt_injections", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v2_base_prompt_injections|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|786.2 MB|
+
+## References
+
+https://huggingface.co/Fan1018/mdeberta-v2-base-prompt-injections
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v2_base_prompt_injections_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v2_base_prompt_injections_pipeline_en.md
new file mode 100644
index 00000000000000..961c13530c04bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v2_base_prompt_injections_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v2_base_prompt_injections_pipeline pipeline DeBertaForSequenceClassification from Fan1018
+author: John Snow Labs
+name: mdeberta_v2_base_prompt_injections_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v2_base_prompt_injections_pipeline` is a English model originally trained by Fan1018.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v2_base_prompt_injections_pipeline_en_5.5.0_3.0_1725439399925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v2_base_prompt_injections_pipeline_en_5.5.0_3.0_1725439399925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v2_base_prompt_injections_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v2_base_prompt_injections_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v2_base_prompt_injections_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|786.3 MB|
+
+## References
+
+https://huggingface.co/Fan1018/mdeberta-v2-base-prompt-injections
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_ctebmsp_es.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_ctebmsp_es.md
new file mode 100644
index 00000000000000..a7f17a4649bd1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_ctebmsp_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish mdeberta_v3_base_ctebmsp DeBertaForTokenClassification from IIC
+author: John Snow Labs
+name: mdeberta_v3_base_ctebmsp
+date: 2024-09-04
+tags: [es, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_ctebmsp` is a Castilian, Spanish model originally trained by IIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_ctebmsp_es_5.5.0_3.0_1725472658340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_ctebmsp_es_5.5.0_3.0_1725472658340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_ctebmsp","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_ctebmsp", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_ctebmsp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|795.3 MB|
+
+## References
+
+https://huggingface.co/IIC/mdeberta-v3-base-ctebmsp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_ctebmsp_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_ctebmsp_pipeline_es.md
new file mode 100644
index 00000000000000..468f54ab7dddff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_ctebmsp_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish mdeberta_v3_base_ctebmsp_pipeline pipeline DeBertaForTokenClassification from IIC
+author: John Snow Labs
+name: mdeberta_v3_base_ctebmsp_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_ctebmsp_pipeline` is a Castilian, Spanish model originally trained by IIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_ctebmsp_pipeline_es_5.5.0_3.0_1725472805387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_ctebmsp_pipeline_es_5.5.0_3.0_1725472805387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_ctebmsp_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_ctebmsp_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_ctebmsp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|795.3 MB|
+
+## References
+
+https://huggingface.co/IIC/mdeberta-v3-base-ctebmsp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_finetuded_porttagger_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_finetuded_porttagger_en.md
new file mode 100644
index 00000000000000..ab1529fe1ae155
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_finetuded_porttagger_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_finetuded_porttagger DeBertaForTokenClassification from Emanuel
+author: John Snow Labs
+name: mdeberta_v3_base_finetuded_porttagger
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_finetuded_porttagger` is a English model originally trained by Emanuel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuded_porttagger_en_5.5.0_3.0_1725472010527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuded_porttagger_en_5.5.0_3.0_1725472010527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_finetuded_porttagger","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_finetuded_porttagger", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_finetuded_porttagger|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|830.4 MB|
+
+## References
+
+https://huggingface.co/Emanuel/mdeberta-v3-base-finetuded-porttagger
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_harem_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_harem_en.md
new file mode 100644
index 00000000000000..363f07813e555e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_harem_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_harem DeBertaForTokenClassification from ruanchaves
+author: John Snow Labs
+name: mdeberta_v3_base_harem
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_harem` is a English model originally trained by ruanchaves.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_harem_en_5.5.0_3.0_1725475357957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_harem_en_5.5.0_3.0_1725475357957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_harem","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_harem", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_harem|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|832.6 MB|
+
+## References
+
+https://huggingface.co/ruanchaves/mdeberta-v3-base-harem
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_harem_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_harem_pipeline_en.md
new file mode 100644
index 00000000000000..0593c2f1c52501
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_harem_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_harem_pipeline pipeline DeBertaForTokenClassification from ruanchaves
+author: John Snow Labs
+name: mdeberta_v3_base_harem_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_harem_pipeline` is a English model originally trained by ruanchaves.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_harem_pipeline_en_5.5.0_3.0_1725475424465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_harem_pipeline_en_5.5.0_3.0_1725475424465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_harem_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_harem_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_harem_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|832.6 MB|
+
+## References
+
+https://huggingface.co/ruanchaves/mdeberta-v3-base-harem
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_mrpc_10_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_mrpc_10_en.md
new file mode 100644
index 00000000000000..f48c3eaff609d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_mrpc_10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_mrpc_10 DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_mrpc_10
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_mrpc_10` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mrpc_10_en_5.5.0_3.0_1725439068827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mrpc_10_en_5.5.0_3.0_1725439068827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_mrpc_10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_mrpc_10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_mrpc_10|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|789.2 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-mrpc-10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_mrpc_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_mrpc_10_pipeline_en.md
new file mode 100644
index 00000000000000..6faf61966c7790
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_mrpc_10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_mrpc_10_pipeline pipeline DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_mrpc_10_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_mrpc_10_pipeline` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mrpc_10_pipeline_en_5.5.0_3.0_1725439218115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mrpc_10_pipeline_en_5.5.0_3.0_1725439218115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_mrpc_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_mrpc_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_mrpc_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|789.2 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-mrpc-10
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_aihub_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_aihub_en.md
new file mode 100644
index 00000000000000..1f294ef9e4f738
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_aihub_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_open_ner_aihub DeBertaForTokenClassification from datasciathlete
+author: John Snow Labs
+name: mdeberta_v3_base_open_ner_aihub
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_open_ner_aihub` is a English model originally trained by datasciathlete.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_aihub_en_5.5.0_3.0_1725472364809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_aihub_en_5.5.0_3.0_1725472364809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_open_ner_aihub","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_open_ner_aihub", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_open_ner_aihub|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|948.4 MB|
+
+## References
+
+https://huggingface.co/datasciathlete/mdeberta-v3-base-open-ner-aihub
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_aihub_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_aihub_pipeline_en.md
new file mode 100644
index 00000000000000..63a86ac72b49b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_aihub_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_open_ner_aihub_pipeline pipeline DeBertaForTokenClassification from datasciathlete
+author: John Snow Labs
+name: mdeberta_v3_base_open_ner_aihub_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_open_ner_aihub_pipeline` is a English model originally trained by datasciathlete.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_aihub_pipeline_en_5.5.0_3.0_1725472421189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_aihub_pipeline_en_5.5.0_3.0_1725472421189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_open_ner_aihub_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_open_ner_aihub_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_open_ner_aihub_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|948.4 MB|
+
+## References
+
+https://huggingface.co/datasciathlete/mdeberta-v3-base-open-ner-aihub
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_pipeline_en.md
new file mode 100644
index 00000000000000..e927fe7b3c2846
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_open_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_open_ner_pipeline pipeline DeBertaForTokenClassification from yongsun-yoon
+author: John Snow Labs
+name: mdeberta_v3_base_open_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_open_ner_pipeline` is a English model originally trained by yongsun-yoon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_pipeline_en_5.5.0_3.0_1725473734763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_open_ner_pipeline_en_5.5.0_3.0_1725473734763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_open_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_open_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_open_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|910.8 MB|
+
+## References
+
+https://huggingface.co/yongsun-yoon/mdeberta-v3-base-open-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_sst2_100_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_sst2_100_en.md
new file mode 100644
index 00000000000000..c87cfc095f91b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_sst2_100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_sst2_100 DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_sst2_100
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_sst2_100` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sst2_100_en_5.5.0_3.0_1725440685074.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sst2_100_en_5.5.0_3.0_1725440685074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_sst2_100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_sst2_100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_sst2_100|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|785.6 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-sst2-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_vnrte_100_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_vnrte_100_en.md
new file mode 100644
index 00000000000000..cf34af9d57b19a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_vnrte_100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_vnrte_100 DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_vnrte_100
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_vnrte_100` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_vnrte_100_en_5.5.0_3.0_1725469264957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_vnrte_100_en_5.5.0_3.0_1725469264957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_vnrte_100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_vnrte_100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_vnrte_100|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|794.8 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-vnrte-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_ver_6_task_1a_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_ver_6_task_1a_en.md
new file mode 100644
index 00000000000000..d974cce2e36e8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_ver_6_task_1a_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_ver_6_task_1a DeBertaForSequenceClassification from sheduele
+author: John Snow Labs
+name: mdeberta_ver_6_task_1a
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_ver_6_task_1a` is a English model originally trained by sheduele.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_ver_6_task_1a_en_5.5.0_3.0_1725438414526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_ver_6_task_1a_en_5.5.0_3.0_1725438414526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_ver_6_task_1a","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_ver_6_task_1a", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_ver_6_task_1a|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|865.6 MB|
+
+## References
+
+https://huggingface.co/sheduele/mdeberta_ver_6_task_1A
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_ver_6_task_1a_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_ver_6_task_1a_pipeline_en.md
new file mode 100644
index 00000000000000..d958b63139d71a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_ver_6_task_1a_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_ver_6_task_1a_pipeline pipeline DeBertaForSequenceClassification from sheduele
+author: John Snow Labs
+name: mdeberta_ver_6_task_1a_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_ver_6_task_1a_pipeline` is a English model originally trained by sheduele.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_ver_6_task_1a_pipeline_en_5.5.0_3.0_1725438513534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_ver_6_task_1a_pipeline_en_5.5.0_3.0_1725438513534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_ver_6_task_1a_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_ver_6_task_1a_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_ver_6_task_1a_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|865.6 MB|
+
+## References
+
+https://huggingface.co/sheduele/mdeberta_ver_6_task_1A
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-meaningbert_en.md b/docs/_posts/ahmedlone127/2024-09-04-meaningbert_en.md
new file mode 100644
index 00000000000000..7c4defc4d47d88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-meaningbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English meaningbert BertForSequenceClassification from davebulaval
+author: John Snow Labs
+name: meaningbert
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meaningbert` is a English model originally trained by davebulaval.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meaningbert_en_5.5.0_3.0_1725433519232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meaningbert_en_5.5.0_3.0_1725433519232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("meaningbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("meaningbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|meaningbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/davebulaval/MeaningBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-meaningbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-meaningbert_pipeline_en.md
new file mode 100644
index 00000000000000..a9749de3d803b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-meaningbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English meaningbert_pipeline pipeline BertForSequenceClassification from davebulaval
+author: John Snow Labs
+name: meaningbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meaningbert_pipeline` is a English model originally trained by davebulaval.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meaningbert_pipeline_en_5.5.0_3.0_1725433539131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meaningbert_pipeline_en_5.5.0_3.0_1725433539131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("meaningbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("meaningbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|meaningbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/davebulaval/MeaningBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-medicalbert_en.md b/docs/_posts/ahmedlone127/2024-09-04-medicalbert_en.md
new file mode 100644
index 00000000000000..094bf0474c071e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-medicalbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English medicalbert DistilBertForTokenClassification from roupenminassian
+author: John Snow Labs
+name: medicalbert
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medicalbert` is a English model originally trained by roupenminassian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medicalbert_en_5.5.0_3.0_1725448777790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medicalbert_en_5.5.0_3.0_1725448777790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("medicalbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("medicalbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medicalbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/roupenminassian/medicalBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-medicalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-medicalbert_pipeline_en.md
new file mode 100644
index 00000000000000..ad73a8f487e29b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-medicalbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English medicalbert_pipeline pipeline DistilBertForTokenClassification from roupenminassian
+author: John Snow Labs
+name: medicalbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medicalbert_pipeline` is a English model originally trained by roupenminassian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medicalbert_pipeline_en_5.5.0_3.0_1725448790754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medicalbert_pipeline_en_5.5.0_3.0_1725448790754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medicalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medicalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medicalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/roupenminassian/medicalBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-memo_bert_sanskrit_saskta_en.md b/docs/_posts/ahmedlone127/2024-09-04-memo_bert_sanskrit_saskta_en.md
new file mode 100644
index 00000000000000..0aa5752abadaee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-memo_bert_sanskrit_saskta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English memo_bert_sanskrit_saskta XlmRoBertaForSequenceClassification from MiMe-MeMo
+author: John Snow Labs
+name: memo_bert_sanskrit_saskta
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_bert_sanskrit_saskta` is a English model originally trained by MiMe-MeMo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_bert_sanskrit_saskta_en_5.5.0_3.0_1725411277921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_bert_sanskrit_saskta_en_5.5.0_3.0_1725411277921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("memo_bert_sanskrit_saskta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("memo_bert_sanskrit_saskta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_bert_sanskrit_saskta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/MiMe-MeMo/MeMo-BERT-SA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-memo_bert_sanskrit_saskta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-memo_bert_sanskrit_saskta_pipeline_en.md
new file mode 100644
index 00000000000000..7876fc792b4465
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-memo_bert_sanskrit_saskta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English memo_bert_sanskrit_saskta_pipeline pipeline XlmRoBertaForSequenceClassification from MiMe-MeMo
+author: John Snow Labs
+name: memo_bert_sanskrit_saskta_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_bert_sanskrit_saskta_pipeline` is a English model originally trained by MiMe-MeMo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_bert_sanskrit_saskta_pipeline_en_5.5.0_3.0_1725411315691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_bert_sanskrit_saskta_pipeline_en_5.5.0_3.0_1725411315691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("memo_bert_sanskrit_saskta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("memo_bert_sanskrit_saskta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_bert_sanskrit_saskta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/MiMe-MeMo/MeMo-BERT-SA
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_cls_sst2_gladiator_en.md b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_cls_sst2_gladiator_en.md
new file mode 100644
index 00000000000000..7fd617af44121e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_cls_sst2_gladiator_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_cls_sst2_gladiator DeBertaForSequenceClassification from Gladiator
+author: John Snow Labs
+name: microsoft_deberta_v3_large_cls_sst2_gladiator
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_cls_sst2_gladiator` is a English model originally trained by Gladiator.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_cls_sst2_gladiator_en_5.5.0_3.0_1725462247851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_cls_sst2_gladiator_en_5.5.0_3.0_1725462247851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("microsoft_deberta_v3_large_cls_sst2_gladiator","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("microsoft_deberta_v3_large_cls_sst2_gladiator", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_cls_sst2_gladiator|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Gladiator/microsoft-deberta-v3-large_cls_sst2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_en.md b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_en.md
new file mode 100644
index 00000000000000..66ec393a81a8c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_en_5.5.0_3.0_1725475467629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_en_5.5.0_3.0_1725475467629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-breast-without-castellon-castellon-10-docs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline_en.md
new file mode 100644
index 00000000000000..24524d90155f40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline pipeline DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline_en_5.5.0_3.0_1725475548402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline_en_5.5.0_3.0_1725475548402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_conll2003_breast_without_castellon_castellon_10_docs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-breast-without-castellon-castellon-10-docs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_general_model_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_general_model_v1_en.md
new file mode 100644
index 00000000000000..8b0f244c324450
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_general_model_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_conll2003_general_model_v1 DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_conll2003_general_model_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_general_model_v1` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_general_model_v1_en_5.5.0_3.0_1725472157929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_general_model_v1_en_5.5.0_3.0_1725472157929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_general_model_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_general_model_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_conll2003_general_model_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-general-model-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_en.md b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_en.md
new file mode 100644
index 00000000000000..6d04c040892bb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3 DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_en_5.5.0_3.0_1725471919520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_en_5.5.0_3.0_1725471919520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-la-fe-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline_en.md
new file mode 100644
index 00000000000000..befa6b27d4d76e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline pipeline DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline` is a English model originally trained by Yanis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline_en_5.5.0_3.0_1725471998755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline_en_5.5.0_3.0_1725471998755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_conll2003_latin_fe_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/microsoft-deberta-v3-large_ner_conll2003-la-fe-v3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_wikiann_en.md b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_wikiann_en.md
new file mode 100644
index 00000000000000..5f9e9d19fb8ab8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_wikiann_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_wikiann DeBertaForTokenClassification from Gladiator
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_wikiann
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_wikiann` is a English model originally trained by Gladiator.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_wikiann_en_5.5.0_3.0_1725473916309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_wikiann_en_5.5.0_3.0_1725473916309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_wikiann","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("microsoft_deberta_v3_large_ner_wikiann", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_wikiann|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Gladiator/microsoft-deberta-v3-large_ner_wikiann
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_wikiann_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_wikiann_pipeline_en.md
new file mode 100644
index 00000000000000..f10c1a75e16e3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-microsoft_deberta_v3_large_ner_wikiann_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_ner_wikiann_pipeline pipeline DeBertaForTokenClassification from Gladiator
+author: John Snow Labs
+name: microsoft_deberta_v3_large_ner_wikiann_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_ner_wikiann_pipeline` is a English model originally trained by Gladiator.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_wikiann_pipeline_en_5.5.0_3.0_1725474002485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_ner_wikiann_pipeline_en_5.5.0_3.0_1725474002485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("microsoft_deberta_v3_large_ner_wikiann_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_ner_wikiann_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_ner_wikiann_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Gladiator/microsoft-deberta-v3-large_ner_wikiann
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mindact_candidategeneration_deberta_v3_base_en.md b/docs/_posts/ahmedlone127/2024-09-04-mindact_candidategeneration_deberta_v3_base_en.md
new file mode 100644
index 00000000000000..dbe776134a2cb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mindact_candidategeneration_deberta_v3_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mindact_candidategeneration_deberta_v3_base DeBertaForSequenceClassification from osunlp
+author: John Snow Labs
+name: mindact_candidategeneration_deberta_v3_base
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mindact_candidategeneration_deberta_v3_base` is a English model originally trained by osunlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mindact_candidategeneration_deberta_v3_base_en_5.5.0_3.0_1725439338863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mindact_candidategeneration_deberta_v3_base_en_5.5.0_3.0_1725439338863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mindact_candidategeneration_deberta_v3_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mindact_candidategeneration_deberta_v3_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mindact_candidategeneration_deberta_v3_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|626.4 MB|
+
+## References
+
+https://huggingface.co/osunlp/MindAct_CandidateGeneration_deberta-v3-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mindact_candidategeneration_deberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mindact_candidategeneration_deberta_v3_base_pipeline_en.md
new file mode 100644
index 00000000000000..db1b43c5a48665
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mindact_candidategeneration_deberta_v3_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mindact_candidategeneration_deberta_v3_base_pipeline pipeline DeBertaForSequenceClassification from osunlp
+author: John Snow Labs
+name: mindact_candidategeneration_deberta_v3_base_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mindact_candidategeneration_deberta_v3_base_pipeline` is a English model originally trained by osunlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mindact_candidategeneration_deberta_v3_base_pipeline_en_5.5.0_3.0_1725439384425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mindact_candidategeneration_deberta_v3_base_pipeline_en_5.5.0_3.0_1725439384425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mindact_candidategeneration_deberta_v3_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mindact_candidategeneration_deberta_v3_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mindact_candidategeneration_deberta_v3_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|626.4 MB|
+
+## References
+
+https://huggingface.co/osunlp/MindAct_CandidateGeneration_deberta-v3-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mix4_japanese_english_fugumt_en.md b/docs/_posts/ahmedlone127/2024-09-04-mix4_japanese_english_fugumt_en.md
new file mode 100644
index 00000000000000..3534c3dc7d5c4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mix4_japanese_english_fugumt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mix4_japanese_english_fugumt MarianTransformer from twieland
+author: John Snow Labs
+name: mix4_japanese_english_fugumt
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix4_japanese_english_fugumt` is a English model originally trained by twieland.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mix4_japanese_english_fugumt_en_5.5.0_3.0_1725494007319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix4_japanese_english_fugumt_en_5.5.0_3.0_1725494007319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("mix4_japanese_english_fugumt","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("mix4_japanese_english_fugumt","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mix4_japanese_english_fugumt|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|352.4 MB|
+
+## References
+
+https://huggingface.co/twieland/MIX4_ja-en_fugumt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mlm_spanish_roberta_base_es.md b/docs/_posts/ahmedlone127/2024-09-04-mlm_spanish_roberta_base_es.md
new file mode 100644
index 00000000000000..15842883609df6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mlm_spanish_roberta_base_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish mlm_spanish_roberta_base RoBertaEmbeddings from MMG
+author: John Snow Labs
+name: mlm_spanish_roberta_base
+date: 2024-09-04
+tags: [es, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_spanish_roberta_base` is a Castilian, Spanish model originally trained by MMG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_spanish_roberta_base_es_5.5.0_3.0_1725412183606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_spanish_roberta_base_es_5.5.0_3.0_1725412183606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("mlm_spanish_roberta_base","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("mlm_spanish_roberta_base","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_spanish_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|es|
+|Size:|470.9 MB|
+
+## References
+
+https://huggingface.co/MMG/mlm-spanish-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mlm_spanish_roberta_base_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-mlm_spanish_roberta_base_pipeline_es.md
new file mode 100644
index 00000000000000..f86aa62c9cbc1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mlm_spanish_roberta_base_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish mlm_spanish_roberta_base_pipeline pipeline RoBertaEmbeddings from MMG
+author: John Snow Labs
+name: mlm_spanish_roberta_base_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_spanish_roberta_base_pipeline` is a Castilian, Spanish model originally trained by MMG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_spanish_roberta_base_pipeline_es_5.5.0_3.0_1725412211265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_spanish_roberta_base_pipeline_es_5.5.0_3.0_1725412211265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mlm_spanish_roberta_base_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mlm_spanish_roberta_base_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_spanish_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|470.9 MB|
+
+## References
+
+https://huggingface.co/MMG/mlm-spanish-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mmx_classifier_microblog_env02_en.md b/docs/_posts/ahmedlone127/2024-09-04-mmx_classifier_microblog_env02_en.md
new file mode 100644
index 00000000000000..a323547dd60671
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mmx_classifier_microblog_env02_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mmx_classifier_microblog_env02 RoBertaForSequenceClassification from dmr76
+author: John Snow Labs
+name: mmx_classifier_microblog_env02
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mmx_classifier_microblog_env02` is a English model originally trained by dmr76.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mmx_classifier_microblog_env02_en_5.5.0_3.0_1725453107427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mmx_classifier_microblog_env02_en_5.5.0_3.0_1725453107427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("mmx_classifier_microblog_env02","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("mmx_classifier_microblog_env02", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mmx_classifier_microblog_env02|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/dmr76/mmx_classifier_microblog_ENv02
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mmx_classifier_microblog_env02_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mmx_classifier_microblog_env02_pipeline_en.md
new file mode 100644
index 00000000000000..b72b0728a19d1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mmx_classifier_microblog_env02_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mmx_classifier_microblog_env02_pipeline pipeline RoBertaForSequenceClassification from dmr76
+author: John Snow Labs
+name: mmx_classifier_microblog_env02_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mmx_classifier_microblog_env02_pipeline` is a English model originally trained by dmr76.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mmx_classifier_microblog_env02_pipeline_en_5.5.0_3.0_1725453172588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mmx_classifier_microblog_env02_pipeline_en_5.5.0_3.0_1725453172588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mmx_classifier_microblog_env02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mmx_classifier_microblog_env02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mmx_classifier_microblog_env02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/dmr76/mmx_classifier_microblog_ENv02
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mnli_microsoft_deberta_v3_large_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-04-mnli_microsoft_deberta_v3_large_seed_2_en.md
new file mode 100644
index 00000000000000..7eef25f073ef0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mnli_microsoft_deberta_v3_large_seed_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mnli_microsoft_deberta_v3_large_seed_2 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: mnli_microsoft_deberta_v3_large_seed_2
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mnli_microsoft_deberta_v3_large_seed_2` is a English model originally trained by utahnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mnli_microsoft_deberta_v3_large_seed_2_en_5.5.0_3.0_1725467936438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mnli_microsoft_deberta_v3_large_seed_2_en_5.5.0_3.0_1725467936438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mnli_microsoft_deberta_v3_large_seed_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mnli_microsoft_deberta_v3_large_seed_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mnli_microsoft_deberta_v3_large_seed_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/mnli_microsoft_deberta-v3-large_seed-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mobilebert_finetuned_sayula_popoluca_en.md b/docs/_posts/ahmedlone127/2024-09-04-mobilebert_finetuned_sayula_popoluca_en.md
new file mode 100644
index 00000000000000..498877ed7a7b48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mobilebert_finetuned_sayula_popoluca_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mobilebert_finetuned_sayula_popoluca BertForTokenClassification from mrm8488
+author: John Snow Labs
+name: mobilebert_finetuned_sayula_popoluca
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_finetuned_sayula_popoluca` is a English model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_finetuned_sayula_popoluca_en_5.5.0_3.0_1725449867529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_finetuned_sayula_popoluca_en_5.5.0_3.0_1725449867529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("mobilebert_finetuned_sayula_popoluca","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("mobilebert_finetuned_sayula_popoluca", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mobilebert_finetuned_sayula_popoluca|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|92.6 MB|
+
+## References
+
+https://huggingface.co/mrm8488/mobilebert-finetuned-pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-model_21200_en.md b/docs/_posts/ahmedlone127/2024-09-04-model_21200_en.md
new file mode 100644
index 00000000000000..2525afed644e6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-model_21200_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_21200 XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: model_21200
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_21200` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_21200_en_5.5.0_3.0_1725417223106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_21200_en_5.5.0_3.0_1725417223106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("model_21200","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("model_21200","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_21200|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/model_21200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-model_21200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-model_21200_pipeline_en.md
new file mode 100644
index 00000000000000..e6bdcf46cc4ba2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-model_21200_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_21200_pipeline pipeline XlmRoBertaEmbeddings from yemen2016
+author: John Snow Labs
+name: model_21200_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_21200_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_21200_pipeline_en_5.5.0_3.0_1725417281844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_21200_pipeline_en_5.5.0_3.0_1725417281844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_21200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_21200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_21200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/model_21200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-monobert_legal_french_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-04-monobert_legal_french_pipeline_fr.md
new file mode 100644
index 00000000000000..e98ced63b65efe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-monobert_legal_french_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French monobert_legal_french_pipeline pipeline CamemBertForSequenceClassification from maastrichtlawtech
+author: John Snow Labs
+name: monobert_legal_french_pipeline
+date: 2024-09-04
+tags: [fr, open_source, pipeline, onnx]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`monobert_legal_french_pipeline` is a French model originally trained by maastrichtlawtech.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/monobert_legal_french_pipeline_fr_5.5.0_3.0_1725466675822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/monobert_legal_french_pipeline_fr_5.5.0_3.0_1725466675822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("monobert_legal_french_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("monobert_legal_french_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|monobert_legal_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|415.0 MB|
+
+## References
+
+https://huggingface.co/maastrichtlawtech/monobert-legal-french
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mother_tongue_model_v3_pipeline_sn.md b/docs/_posts/ahmedlone127/2024-09-04-mother_tongue_model_v3_pipeline_sn.md
new file mode 100644
index 00000000000000..ae1c3427399cca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mother_tongue_model_v3_pipeline_sn.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Shona mother_tongue_model_v3_pipeline pipeline WhisperForCTC from MothersTongue
+author: John Snow Labs
+name: mother_tongue_model_v3_pipeline
+date: 2024-09-04
+tags: [sn, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: sn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mother_tongue_model_v3_pipeline` is a Shona model originally trained by MothersTongue.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mother_tongue_model_v3_pipeline_sn_5.5.0_3.0_1725430208767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mother_tongue_model_v3_pipeline_sn_5.5.0_3.0_1725430208767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mother_tongue_model_v3_pipeline", lang = "sn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mother_tongue_model_v3_pipeline", lang = "sn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mother_tongue_model_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sn|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/MothersTongue/mother_tongue_model_v3
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mpnet_stackexchange_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-mpnet_stackexchange_v1_en.md
new file mode 100644
index 00000000000000..9f9e4dc5c1ce7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mpnet_stackexchange_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_stackexchange_v1 MPNetEmbeddings from flax-sentence-embeddings
+author: John Snow Labs
+name: mpnet_stackexchange_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_stackexchange_v1` is a English model originally trained by flax-sentence-embeddings.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_stackexchange_v1_en_5.5.0_3.0_1725470917717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_stackexchange_v1_en_5.5.0_3.0_1725470917717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_stackexchange_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_stackexchange_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_stackexchange_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.6 MB|
+
+## References
+
+https://huggingface.co/flax-sentence-embeddings/mpnet_stackexchange_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_squad_indonesian_ir_en.md b/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_squad_indonesian_ir_en.md
new file mode 100644
index 00000000000000..28b11f1670f808
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_squad_indonesian_ir_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_qaqg_finetuned_squad_indonesian_ir T5Transformer from hawalurahman
+author: John Snow Labs
+name: mt5_base_qaqg_finetuned_squad_indonesian_ir
+date: 2024-09-04
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_qaqg_finetuned_squad_indonesian_ir` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_qaqg_finetuned_squad_indonesian_ir_en_5.5.0_3.0_1725459894953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_qaqg_finetuned_squad_indonesian_ir_en_5.5.0_3.0_1725459894953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_qaqg_finetuned_squad_indonesian_ir","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_qaqg_finetuned_squad_indonesian_ir", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_qaqg_finetuned_squad_indonesian_ir|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/hawalurahman/mt5-base-qaqg-finetuned-SQuAD-id-ir
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline_en.md
new file mode 100644
index 00000000000000..72f639c9d6094d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline_en_5.5.0_3.0_1725460058795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline_en_5.5.0_3.0_1725460058795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_qaqg_finetuned_squad_indonesian_ir_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/hawalurahman/mt5-base-qaqg-finetuned-SQuAD-id-ir
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline_en.md
new file mode 100644
index 00000000000000..91305fa3720214
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline_en_5.5.0_3.0_1725460179004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline_en_5.5.0_3.0_1725460179004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_qaqg_finetuned_tydiqa_indonesian_ir_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/hawalurahman/mt5-base-qaqg-finetuned-TydiQA-id-ir
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence_en.md b/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence_en.md
new file mode 100644
index 00000000000000..d2fa75c33e895f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence T5Transformer from hawalurahman
+author: John Snow Labs
+name: mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence
+date: 2024-09-04
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence_en_5.5.0_3.0_1725459552705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence_en_5.5.0_3.0_1725459552705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_qaqg_finetuned_tydiqa_indonesian_sentence|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/hawalurahman/mt5-base-qaqg-finetuned-TydiQA-id-sentence
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-multilingual_e5_base_censor_v0_2_xx.md b/docs/_posts/ahmedlone127/2024-09-04-multilingual_e5_base_censor_v0_2_xx.md
new file mode 100644
index 00000000000000..ec1885a5ce9f9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-multilingual_e5_base_censor_v0_2_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_e5_base_censor_v0_2 XlmRoBertaForSequenceClassification from Data-Lab
+author: John Snow Labs
+name: multilingual_e5_base_censor_v0_2
+date: 2024-09-04
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_e5_base_censor_v0_2` is a Multilingual model originally trained by Data-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_e5_base_censor_v0_2_xx_5.5.0_3.0_1725410959464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_e5_base_censor_v0_2_xx_5.5.0_3.0_1725410959464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("multilingual_e5_base_censor_v0_2","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("multilingual_e5_base_censor_v0_2", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_e5_base_censor_v0_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|800.0 MB|
+
+## References
+
+https://huggingface.co/Data-Lab/multilingual-e5-base_censor_v0.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-nasa_smd_ibm_distil_v0_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-nasa_smd_ibm_distil_v0_1_en.md
new file mode 100644
index 00000000000000..fcdbadaf9c8acb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-nasa_smd_ibm_distil_v0_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nasa_smd_ibm_distil_v0_1 RoBertaEmbeddings from nasa-impact
+author: John Snow Labs
+name: nasa_smd_ibm_distil_v0_1
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nasa_smd_ibm_distil_v0_1` is a English model originally trained by nasa-impact.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_distil_v0_1_en_5.5.0_3.0_1725412410297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_distil_v0_1_en_5.5.0_3.0_1725412410297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("nasa_smd_ibm_distil_v0_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("nasa_smd_ibm_distil_v0_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nasa_smd_ibm_distil_v0_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|114.1 MB|
+
+## References
+
+https://huggingface.co/nasa-impact/nasa-smd-ibm-distil-v0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-nasa_smd_ibm_distil_v0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-nasa_smd_ibm_distil_v0_1_pipeline_en.md
new file mode 100644
index 00000000000000..3cac56abeaee0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-nasa_smd_ibm_distil_v0_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nasa_smd_ibm_distil_v0_1_pipeline pipeline RoBertaEmbeddings from nasa-impact
+author: John Snow Labs
+name: nasa_smd_ibm_distil_v0_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nasa_smd_ibm_distil_v0_1_pipeline` is a English model originally trained by nasa-impact.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_distil_v0_1_pipeline_en_5.5.0_3.0_1725412416590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_distil_v0_1_pipeline_en_5.5.0_3.0_1725412416590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nasa_smd_ibm_distil_v0_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nasa_smd_ibm_distil_v0_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nasa_smd_ibm_distil_v0_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|114.2 MB|
+
+## References
+
+https://huggingface.co/nasa-impact/nasa-smd-ibm-distil-v0.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-nepal_bhasa_trained_slovak_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-nepal_bhasa_trained_slovak_pipeline_en.md
new file mode 100644
index 00000000000000..d32a756d874cf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-nepal_bhasa_trained_slovak_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nepal_bhasa_trained_slovak_pipeline pipeline DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: nepal_bhasa_trained_slovak_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_trained_slovak_pipeline` is a English model originally trained by annamariagnat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_slovak_pipeline_en_5.5.0_3.0_1725460930493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_slovak_pipeline_en_5.5.0_3.0_1725460930493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nepal_bhasa_trained_slovak_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nepal_bhasa_trained_slovak_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_trained_slovak_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/NEW_trained_slovak
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_bert_large_cased_portuguese_contratos_tceal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_bert_large_cased_portuguese_contratos_tceal_pipeline_en.md
new file mode 100644
index 00000000000000..1e60ee9b4b2c65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_bert_large_cased_portuguese_contratos_tceal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_bert_large_cased_portuguese_contratos_tceal_pipeline pipeline BertForTokenClassification from begnini
+author: John Snow Labs
+name: ner_bert_large_cased_portuguese_contratos_tceal_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_bert_large_cased_portuguese_contratos_tceal_pipeline` is a English model originally trained by begnini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_bert_large_cased_portuguese_contratos_tceal_pipeline_en_5.5.0_3.0_1725450033883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_bert_large_cased_portuguese_contratos_tceal_pipeline_en_5.5.0_3.0_1725450033883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_bert_large_cased_portuguese_contratos_tceal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_bert_large_cased_portuguese_contratos_tceal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_bert_large_cased_portuguese_contratos_tceal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/begnini/ner-bert-large-cased-pt-contratos_tceal
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_bertje_tagdetekst_nl.md b/docs/_posts/ahmedlone127/2024-09-04-ner_bertje_tagdetekst_nl.md
new file mode 100644
index 00000000000000..860a40b089e687
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_bertje_tagdetekst_nl.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Dutch, Flemish ner_bertje_tagdetekst BertForTokenClassification from surferfelix
+author: John Snow Labs
+name: ner_bertje_tagdetekst
+date: 2024-09-04
+tags: [nl, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_bertje_tagdetekst` is a Dutch, Flemish model originally trained by surferfelix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_bertje_tagdetekst_nl_5.5.0_3.0_1725477824903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_bertje_tagdetekst_nl_5.5.0_3.0_1725477824903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_bertje_tagdetekst","nl") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_bertje_tagdetekst", "nl")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_bertje_tagdetekst|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|nl|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/surferfelix/ner-bertje-tagdetekst
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_bertje_tagdetekst_pipeline_nl.md b/docs/_posts/ahmedlone127/2024-09-04-ner_bertje_tagdetekst_pipeline_nl.md
new file mode 100644
index 00000000000000..361146ca7adb59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_bertje_tagdetekst_pipeline_nl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Dutch, Flemish ner_bertje_tagdetekst_pipeline pipeline BertForTokenClassification from surferfelix
+author: John Snow Labs
+name: ner_bertje_tagdetekst_pipeline
+date: 2024-09-04
+tags: [nl, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_bertje_tagdetekst_pipeline` is a Dutch, Flemish model originally trained by surferfelix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_bertje_tagdetekst_pipeline_nl_5.5.0_3.0_1725477845476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_bertje_tagdetekst_pipeline_nl_5.5.0_3.0_1725477845476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_bertje_tagdetekst_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_bertje_tagdetekst_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_bertje_tagdetekst_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/surferfelix/ner-bertje-tagdetekst
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_cw_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_cw_model_pipeline_en.md
new file mode 100644
index 00000000000000..62251d806b2405
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_cw_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_cw_model_pipeline pipeline DistilBertForTokenClassification from ArshiaKarimian
+author: John Snow Labs
+name: ner_cw_model_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_cw_model_pipeline` is a English model originally trained by ArshiaKarimian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_cw_model_pipeline_en_5.5.0_3.0_1725448722986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_cw_model_pipeline_en_5.5.0_3.0_1725448722986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_cw_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_cw_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_cw_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ArshiaKarimian/NER_CW_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_1_en.md
new file mode 100644
index 00000000000000..7c152c35e624d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_distilbert_classifier_1 DistilBertForTokenClassification from Maaz911
+author: John Snow Labs
+name: ner_distilbert_classifier_1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_distilbert_classifier_1` is a English model originally trained by Maaz911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_distilbert_classifier_1_en_5.5.0_3.0_1725460443981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_distilbert_classifier_1_en_5.5.0_3.0_1725460443981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_distilbert_classifier_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_distilbert_classifier_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_distilbert_classifier_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Maaz911/NER-distilbert-classifier-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_en.md
new file mode 100644
index 00000000000000..75c0cdbf7f3069
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_distilbert_classifier DistilBertForTokenClassification from Maaz911
+author: John Snow Labs
+name: ner_distilbert_classifier
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_distilbert_classifier` is a English model originally trained by Maaz911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_distilbert_classifier_en_5.5.0_3.0_1725460404924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_distilbert_classifier_en_5.5.0_3.0_1725460404924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_distilbert_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_distilbert_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_distilbert_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Maaz911/NER-distilbert-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..a2fa2682fae9ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_distilbert_classifier_pipeline pipeline DistilBertForTokenClassification from Maaz911
+author: John Snow Labs
+name: ner_distilbert_classifier_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_distilbert_classifier_pipeline` is a English model originally trained by Maaz911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_distilbert_classifier_pipeline_en_5.5.0_3.0_1725460418050.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_distilbert_classifier_pipeline_en_5.5.0_3.0_1725460418050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_distilbert_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_distilbert_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_distilbert_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Maaz911/NER-distilbert-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_textminr_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_textminr_en.md
new file mode 100644
index 00000000000000..f0ad0bad3069c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_textminr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_distilbert_textminr DistilBertForTokenClassification from textminr
+author: John Snow Labs
+name: ner_distilbert_textminr
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_distilbert_textminr` is a English model originally trained by textminr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_distilbert_textminr_en_5.5.0_3.0_1725448946034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_distilbert_textminr_en_5.5.0_3.0_1725448946034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_distilbert_textminr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_distilbert_textminr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_distilbert_textminr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/textminr/ner-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_extracttotal_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_extracttotal_en.md
new file mode 100644
index 00000000000000..b7c471bef97ddf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_extracttotal_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_extracttotal DistilBertForTokenClassification from Pablito47
+author: John Snow Labs
+name: ner_extracttotal
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_extracttotal` is a English model originally trained by Pablito47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_extracttotal_en_5.5.0_3.0_1725460554569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_extracttotal_en_5.5.0_3.0_1725460554569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_extracttotal","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_extracttotal", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_extracttotal|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Pablito47/NER-ExtractTotal
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_extracttotal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_extracttotal_pipeline_en.md
new file mode 100644
index 00000000000000..fdaf1fc1cdf25f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_extracttotal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_extracttotal_pipeline pipeline DistilBertForTokenClassification from Pablito47
+author: John Snow Labs
+name: ner_extracttotal_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_extracttotal_pipeline` is a English model originally trained by Pablito47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_extracttotal_pipeline_en_5.5.0_3.0_1725460566696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_extracttotal_pipeline_en_5.5.0_3.0_1725460566696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_extracttotal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_extracttotal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_extracttotal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Pablito47/NER-ExtractTotal
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_finetuned_beto_paulrojasg_es.md b/docs/_posts/ahmedlone127/2024-09-04-ner_finetuned_beto_paulrojasg_es.md
new file mode 100644
index 00000000000000..10be85bf4c51e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_finetuned_beto_paulrojasg_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish ner_finetuned_beto_paulrojasg BertForTokenClassification from paulrojasg
+author: John Snow Labs
+name: ner_finetuned_beto_paulrojasg
+date: 2024-09-04
+tags: [es, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_finetuned_beto_paulrojasg` is a Castilian, Spanish model originally trained by paulrojasg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_finetuned_beto_paulrojasg_es_5.5.0_3.0_1725478124933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_finetuned_beto_paulrojasg_es_5.5.0_3.0_1725478124933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_finetuned_beto_paulrojasg","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_finetuned_beto_paulrojasg", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_finetuned_beto_paulrojasg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/paulrojasg/NER-finetuned-BETO
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_finetuned_beto_paulrojasg_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-ner_finetuned_beto_paulrojasg_pipeline_es.md
new file mode 100644
index 00000000000000..77d9916993ac13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_finetuned_beto_paulrojasg_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish ner_finetuned_beto_paulrojasg_pipeline pipeline BertForTokenClassification from paulrojasg
+author: John Snow Labs
+name: ner_finetuned_beto_paulrojasg_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_finetuned_beto_paulrojasg_pipeline` is a Castilian, Spanish model originally trained by paulrojasg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_finetuned_beto_paulrojasg_pipeline_es_5.5.0_3.0_1725478144287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_finetuned_beto_paulrojasg_pipeline_es_5.5.0_3.0_1725478144287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_finetuned_beto_paulrojasg_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_finetuned_beto_paulrojasg_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_finetuned_beto_paulrojasg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/paulrojasg/NER-finetuned-BETO
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_model_rujengelal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_model_rujengelal_pipeline_en.md
new file mode 100644
index 00000000000000..7f441bceb9fbd0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_model_rujengelal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_model_rujengelal_pipeline pipeline DistilBertForTokenClassification from rujengelal
+author: John Snow Labs
+name: ner_model_rujengelal_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_rujengelal_pipeline` is a English model originally trained by rujengelal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_rujengelal_pipeline_en_5.5.0_3.0_1725448637331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_rujengelal_pipeline_en_5.5.0_3.0_1725448637331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_model_rujengelal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_model_rujengelal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_rujengelal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/rujengelal/ner-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_model_techme_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_model_techme_en.md
new file mode 100644
index 00000000000000..8e82f182eb5955
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_model_techme_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_techme DistilBertForTokenClassification from techme
+author: John Snow Labs
+name: ner_model_techme
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_techme` is a English model originally trained by techme.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_techme_en_5.5.0_3.0_1725476140824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_techme_en_5.5.0_3.0_1725476140824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_model_techme","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_model_techme", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_techme|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/techme/ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_ner_random0_seed2_bernice_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_ner_random0_seed2_bernice_en.md
new file mode 100644
index 00000000000000..86dbe7d2da4cb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_ner_random0_seed2_bernice_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ner_random0_seed2_bernice XlmRoBertaForTokenClassification from tweettemposhift
+author: John Snow Labs
+name: ner_ner_random0_seed2_bernice
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ner_random0_seed2_bernice` is a English model originally trained by tweettemposhift.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ner_random0_seed2_bernice_en_5.5.0_3.0_1725437821138.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ner_random0_seed2_bernice_en_5.5.0_3.0_1725437821138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("ner_ner_random0_seed2_bernice","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner_ner_random0_seed2_bernice", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ner_random0_seed2_bernice|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|802.6 MB|
+
+## References
+
+https://huggingface.co/tweettemposhift/ner-ner_random0_seed2-bernice
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_ner_random0_seed2_bernice_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_ner_random0_seed2_bernice_pipeline_en.md
new file mode 100644
index 00000000000000..2dbf64ef63330b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_ner_random0_seed2_bernice_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ner_random0_seed2_bernice_pipeline pipeline XlmRoBertaForTokenClassification from tweettemposhift
+author: John Snow Labs
+name: ner_ner_random0_seed2_bernice_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ner_random0_seed2_bernice_pipeline` is a English model originally trained by tweettemposhift.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ner_random0_seed2_bernice_pipeline_en_5.5.0_3.0_1725437963294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ner_random0_seed2_bernice_pipeline_en_5.5.0_3.0_1725437963294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ner_random0_seed2_bernice_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ner_random0_seed2_bernice_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ner_random0_seed2_bernice_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|802.6 MB|
+
+## References
+
+https://huggingface.co/tweettemposhift/ner-ner_random0_seed2-bernice
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_on_bangla_language_bn.md b/docs/_posts/ahmedlone127/2024-09-04-ner_on_bangla_language_bn.md
new file mode 100644
index 00000000000000..bc0bcd6eab64fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_on_bangla_language_bn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Bengali ner_on_bangla_language BertForTokenClassification from engineersakibcse47
+author: John Snow Labs
+name: ner_on_bangla_language
+date: 2024-09-04
+tags: [bn, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: bn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_on_bangla_language` is a Bengali model originally trained by engineersakibcse47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_on_bangla_language_bn_5.5.0_3.0_1725449622151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_on_bangla_language_bn_5.5.0_3.0_1725449622151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_on_bangla_language","bn") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_on_bangla_language", "bn")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_on_bangla_language|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|bn|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/engineersakibcse47/NER_on_Bangla_Language
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_on_bangla_language_pipeline_bn.md b/docs/_posts/ahmedlone127/2024-09-04-ner_on_bangla_language_pipeline_bn.md
new file mode 100644
index 00000000000000..8b98dcc0ca36b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_on_bangla_language_pipeline_bn.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Bengali ner_on_bangla_language_pipeline pipeline BertForTokenClassification from engineersakibcse47
+author: John Snow Labs
+name: ner_on_bangla_language_pipeline
+date: 2024-09-04
+tags: [bn, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: bn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_on_bangla_language_pipeline` is a Bengali model originally trained by engineersakibcse47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_on_bangla_language_pipeline_bn_5.5.0_3.0_1725449659015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_on_bangla_language_pipeline_bn_5.5.0_3.0_1725449659015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_on_bangla_language_pipeline", lang = "bn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_on_bangla_language_pipeline", lang = "bn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_on_bangla_language_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bn|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/engineersakibcse47/NER_on_Bangla_Language
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-nlp_esgi_td4_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-nlp_esgi_td4_ner_pipeline_en.md
new file mode 100644
index 00000000000000..620b6d4ceb6ced
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-nlp_esgi_td4_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_esgi_td4_ner_pipeline pipeline DistilBertForTokenClassification from foucheta
+author: John Snow Labs
+name: nlp_esgi_td4_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_esgi_td4_ner_pipeline` is a English model originally trained by foucheta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_esgi_td4_ner_pipeline_en_5.5.0_3.0_1725492572297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_esgi_td4_ner_pipeline_en_5.5.0_3.0_1725492572297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_esgi_td4_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_esgi_td4_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_esgi_td4_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/foucheta/nlp_esgi_td4_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-nlp_mini_project_en.md b/docs/_posts/ahmedlone127/2024-09-04-nlp_mini_project_en.md
new file mode 100644
index 00000000000000..97ae97f527079d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-nlp_mini_project_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_mini_project DistilBertForTokenClassification from LightFury9
+author: John Snow Labs
+name: nlp_mini_project
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_mini_project` is a English model originally trained by LightFury9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_mini_project_en_5.5.0_3.0_1725476210669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_mini_project_en_5.5.0_3.0_1725476210669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_mini_project","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_mini_project", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_mini_project|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/LightFury9/nlp-mini-project
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-novelicious_qas_en.md b/docs/_posts/ahmedlone127/2024-09-04-novelicious_qas_en.md
new file mode 100644
index 00000000000000..acf0dfa874caf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-novelicious_qas_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English novelicious_qas DistilBertForQuestionAnswering from ndrakita
+author: John Snow Labs
+name: novelicious_qas
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`novelicious_qas` is a English model originally trained by ndrakita.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/novelicious_qas_en_5.5.0_3.0_1725465288662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/novelicious_qas_en_5.5.0_3.0_1725465288662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("novelicious_qas","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("novelicious_qas", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|novelicious_qas|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/ndrakita/novelicious-qas
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ope_bert_v1_3_en.md b/docs/_posts/ahmedlone127/2024-09-04-ope_bert_v1_3_en.md
new file mode 100644
index 00000000000000..809e14fb6c8eae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ope_bert_v1_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ope_bert_v1_3 DistilBertEmbeddings from RyotaroOKabe
+author: John Snow Labs
+name: ope_bert_v1_3
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ope_bert_v1_3` is a English model originally trained by RyotaroOKabe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ope_bert_v1_3_en_5.5.0_3.0_1725418739391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ope_bert_v1_3_en_5.5.0_3.0_1725418739391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("ope_bert_v1_3","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("ope_bert_v1_3","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ope_bert_v1_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/RyotaroOKabe/ope_bert_v1.3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-openai_detector_large_en.md b/docs/_posts/ahmedlone127/2024-09-04-openai_detector_large_en.md
new file mode 100644
index 00000000000000..f55929a5f5c1a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-openai_detector_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English openai_detector_large RoBertaForSequenceClassification from nbroad
+author: John Snow Labs
+name: openai_detector_large
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`openai_detector_large` is a English model originally trained by nbroad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/openai_detector_large_en_5.5.0_3.0_1725485551122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/openai_detector_large_en_5.5.0_3.0_1725485551122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("openai_detector_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("openai_detector_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|openai_detector_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/nbroad/openai-detector-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-openclip_negclip_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-openclip_negclip_pipeline_en.md
new file mode 100644
index 00000000000000..4b5eaaf8be03d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-openclip_negclip_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English openclip_negclip_pipeline pipeline CLIPForZeroShotClassification from Nano1337
+author: John Snow Labs
+name: openclip_negclip_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`openclip_negclip_pipeline` is a English model originally trained by Nano1337.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/openclip_negclip_pipeline_en_5.5.0_3.0_1725491551625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/openclip_negclip_pipeline_en_5.5.0_3.0_1725491551625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("openclip_negclip_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("openclip_negclip_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|openclip_negclip_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|567.0 MB|
+
+## References
+
+https://huggingface.co/Nano1337/openclip-negclip
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..b5029204d261ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english MarianTransformer from PontifexMaximus
+author: John Snow Labs
+name: opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english` is a English model originally trained by PontifexMaximus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english_en_5.5.0_3.0_1725494155983.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english_en_5.5.0_3.0_1725494155983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_german_finetuned_german_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|484.9 MB|
+
+## References
+
+https://huggingface.co/PontifexMaximus/opus-mt-en-de-finetuned-de-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan_en.md b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan_en.md
new file mode 100644
index 00000000000000..978e4afa22df6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan MarianTransformer from Rooshan
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan` is a English model originally trained by Rooshan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan_en_5.5.0_3.0_1725494139882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan_en_5.5.0_3.0_1725494139882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_rooshan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/Rooshan/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_en.md b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_en.md
new file mode 100644
index 00000000000000..7f15bd24752135
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad MarianTransformer from srirad
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad` is a English model originally trained by srirad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_en_5.5.0_3.0_1725493880529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_en_5.5.0_3.0_1725493880529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.5 MB|
+
+## References
+
+https://huggingface.co/srirad/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline_en.md
new file mode 100644
index 00000000000000..cadf8a11469e7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline pipeline MarianTransformer from srirad
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline` is a English model originally trained by srirad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline_en_5.5.0_3.0_1725493905485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline_en_5.5.0_3.0_1725493905485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_srirad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.1 MB|
+
+## References
+
+https://huggingface.co/srirad/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline_en.md
new file mode 100644
index 00000000000000..6ff80acaf5b94e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline pipeline MarianTransformer from Susmit99
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline` is a English model originally trained by Susmit99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline_en_5.5.0_3.0_1725494238242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline_en_5.5.0_3.0_1725494238242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_susmit99_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.1 MB|
+
+## References
+
+https://huggingface.co/Susmit99/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_finetuned_korean_german_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_finetuned_korean_german_pipeline_en.md
new file mode 100644
index 00000000000000..9082b6af4a51ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_finetuned_korean_german_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_finetuned_korean_german_pipeline pipeline MarianTransformer from Uiji
+author: John Snow Labs
+name: opus_maltese_finetuned_korean_german_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_finetuned_korean_german_pipeline` is a English model originally trained by Uiji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_finetuned_korean_german_pipeline_en_5.5.0_3.0_1725493779841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_finetuned_korean_german_pipeline_en_5.5.0_3.0_1725493779841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_finetuned_korean_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_finetuned_korean_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_finetuned_korean_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.8 MB|
+
+## References
+
+https://huggingface.co/Uiji/opus-mt-finetuned-ko-de
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_tc_big_arabic_english_en.md b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_tc_big_arabic_english_en.md
new file mode 100644
index 00000000000000..60ea607d77c6bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_tc_big_arabic_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_tc_big_arabic_english MarianTransformer from SaeedMLK
+author: John Snow Labs
+name: opus_maltese_tc_big_arabic_english
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tc_big_arabic_english` is a English model originally trained by SaeedMLK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_arabic_english_en_5.5.0_3.0_1725494257472.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_arabic_english_en_5.5.0_3.0_1725494257472.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_tc_big_arabic_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_tc_big_arabic_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_tc_big_arabic_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/SaeedMLK/opus-mt-tc-big-ar-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_tc_big_arabic_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_tc_big_arabic_english_pipeline_en.md
new file mode 100644
index 00000000000000..b8d0ea1c66a890
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-opus_maltese_tc_big_arabic_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_tc_big_arabic_english_pipeline pipeline MarianTransformer from SaeedMLK
+author: John Snow Labs
+name: opus_maltese_tc_big_arabic_english_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tc_big_arabic_english_pipeline` is a English model originally trained by SaeedMLK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_arabic_english_pipeline_en_5.5.0_3.0_1725494322242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_arabic_english_pipeline_en_5.5.0_3.0_1725494322242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_tc_big_arabic_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_tc_big_arabic_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_tc_big_arabic_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/SaeedMLK/opus-mt-tc-big-ar-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_en.md
new file mode 100644
index 00000000000000..5ec5b99d082d17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1 RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_en_5.5.0_3.0_1725483562080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_en_5.5.0_3.0_1725483562080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AnonymousSub/output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_LARGE_SECOND_EPOCHS_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline_en.md
new file mode 100644
index 00000000000000..1d32d5f79f0f55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline_en_5.5.0_3.0_1725483626221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline_en_5.5.0_3.0_1725483626221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_large_second_epochs_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AnonymousSub/output_mask_step_pretraining_plus_contr_roberta_model_from_pretrained_LARGE_SECOND_EPOCHS_1
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline_en.md
new file mode 100644
index 00000000000000..7459ddae1674f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline pipeline RoBertaForSequenceClassification from platzi
+author: John Snow Labs
+name: platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline` is a English model originally trained by platzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline_en_5.5.0_3.0_1725485765256.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline_en_5.5.0_3.0_1725485765256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|platzi_distilroberta_base_mrpc_glue_gio_testing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/platzi/platzi-distilroberta-base-mrpc-glue-gio-testing
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-portuguese_capitalization_punctuation_restoration_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-04-portuguese_capitalization_punctuation_restoration_pipeline_pt.md
new file mode 100644
index 00000000000000..ba28f82f330fe2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-portuguese_capitalization_punctuation_restoration_pipeline_pt.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Portuguese portuguese_capitalization_punctuation_restoration_pipeline pipeline XlmRoBertaForTokenClassification from UMUTeam
+author: John Snow Labs
+name: portuguese_capitalization_punctuation_restoration_pipeline
+date: 2024-09-04
+tags: [pt, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_capitalization_punctuation_restoration_pipeline` is a Portuguese model originally trained by UMUTeam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/portuguese_capitalization_punctuation_restoration_pipeline_pt_5.5.0_3.0_1725424035358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_capitalization_punctuation_restoration_pipeline_pt_5.5.0_3.0_1725424035358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("portuguese_capitalization_punctuation_restoration_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("portuguese_capitalization_punctuation_restoration_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_capitalization_punctuation_restoration_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|883.3 MB|
+
+## References
+
+https://huggingface.co/UMUTeam/portuguese_capitalization_punctuation_restoration
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-portuguese_capitalization_punctuation_restoration_pt.md b/docs/_posts/ahmedlone127/2024-09-04-portuguese_capitalization_punctuation_restoration_pt.md
new file mode 100644
index 00000000000000..1736b90e4ce591
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-portuguese_capitalization_punctuation_restoration_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese portuguese_capitalization_punctuation_restoration XlmRoBertaForTokenClassification from UMUTeam
+author: John Snow Labs
+name: portuguese_capitalization_punctuation_restoration
+date: 2024-09-04
+tags: [pt, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_capitalization_punctuation_restoration` is a Portuguese model originally trained by UMUTeam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/portuguese_capitalization_punctuation_restoration_pt_5.5.0_3.0_1725423976802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_capitalization_punctuation_restoration_pt_5.5.0_3.0_1725423976802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("portuguese_capitalization_punctuation_restoration","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("portuguese_capitalization_punctuation_restoration", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_capitalization_punctuation_restoration|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|pt|
+|Size:|883.3 MB|
+
+## References
+
+https://huggingface.co/UMUTeam/portuguese_capitalization_punctuation_restoration
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-practice_model_en.md b/docs/_posts/ahmedlone127/2024-09-04-practice_model_en.md
new file mode 100644
index 00000000000000..d4f1e47cfa98a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-practice_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English practice_model CamemBertEmbeddings from OOOHHHIII
+author: John Snow Labs
+name: practice_model
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`practice_model` is a English model originally trained by OOOHHHIII.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/practice_model_en_5.5.0_3.0_1725442509901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/practice_model_en_5.5.0_3.0_1725442509901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("practice_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("practice_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|practice_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/OOOHHHIII/practice-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-predict_political_group_camembert_large_en.md b/docs/_posts/ahmedlone127/2024-09-04-predict_political_group_camembert_large_en.md
new file mode 100644
index 00000000000000..d256c3128ebfa1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-predict_political_group_camembert_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English predict_political_group_camembert_large CamemBertForSequenceClassification from ekazuki
+author: John Snow Labs
+name: predict_political_group_camembert_large
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predict_political_group_camembert_large` is a English model originally trained by ekazuki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/predict_political_group_camembert_large_en_5.5.0_3.0_1725480913199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predict_political_group_camembert_large_en_5.5.0_3.0_1725480913199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("predict_political_group_camembert_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("predict_political_group_camembert_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predict_political_group_camembert_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|413.9 MB|
+
+## References
+
+https://huggingface.co/ekazuki/predict_political_group_camembert_large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-predict_political_group_camembert_tweet_en.md b/docs/_posts/ahmedlone127/2024-09-04-predict_political_group_camembert_tweet_en.md
new file mode 100644
index 00000000000000..9cdfde2ced4477
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-predict_political_group_camembert_tweet_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English predict_political_group_camembert_tweet CamemBertForSequenceClassification from ekazuki
+author: John Snow Labs
+name: predict_political_group_camembert_tweet
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predict_political_group_camembert_tweet` is a English model originally trained by ekazuki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/predict_political_group_camembert_tweet_en_5.5.0_3.0_1725480365376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predict_political_group_camembert_tweet_en_5.5.0_3.0_1725480365376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("predict_political_group_camembert_tweet","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("predict_political_group_camembert_tweet", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predict_political_group_camembert_tweet|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|400.8 MB|
+
+## References
+
+https://huggingface.co/ekazuki/predict_political_group_camembert_tweet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-privacy_300k_masking_en.md b/docs/_posts/ahmedlone127/2024-09-04-privacy_300k_masking_en.md
new file mode 100644
index 00000000000000..dd8c3abd348989
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-privacy_300k_masking_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English privacy_300k_masking DistilBertForTokenClassification from taro-pudding
+author: John Snow Labs
+name: privacy_300k_masking
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`privacy_300k_masking` is a English model originally trained by taro-pudding.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/privacy_300k_masking_en_5.5.0_3.0_1725476602810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/privacy_300k_masking_en_5.5.0_3.0_1725476602810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("privacy_300k_masking","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("privacy_300k_masking", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|privacy_300k_masking|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.6 MB|
+
+## References
+
+https://huggingface.co/taro-pudding/privacy-300k-masking
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-privacy_300k_masking_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-privacy_300k_masking_pipeline_en.md
new file mode 100644
index 00000000000000..a2e24e647217a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-privacy_300k_masking_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English privacy_300k_masking_pipeline pipeline DistilBertForTokenClassification from taro-pudding
+author: John Snow Labs
+name: privacy_300k_masking_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`privacy_300k_masking_pipeline` is a English model originally trained by taro-pudding.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/privacy_300k_masking_pipeline_en_5.5.0_3.0_1725476626385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/privacy_300k_masking_pipeline_en_5.5.0_3.0_1725476626385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("privacy_300k_masking_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("privacy_300k_masking_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|privacy_300k_masking_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.6 MB|
+
+## References
+
+https://huggingface.co/taro-pudding/privacy-300k-masking
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-promptengpromptclassification_en.md b/docs/_posts/ahmedlone127/2024-09-04-promptengpromptclassification_en.md
new file mode 100644
index 00000000000000..1de2cb7c2460a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-promptengpromptclassification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English promptengpromptclassification RoBertaForSequenceClassification from sahilml
+author: John Snow Labs
+name: promptengpromptclassification
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptengpromptclassification` is a English model originally trained by sahilml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptengpromptclassification_en_5.5.0_3.0_1725453298228.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptengpromptclassification_en_5.5.0_3.0_1725453298228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("promptengpromptclassification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("promptengpromptclassification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptengpromptclassification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|426.3 MB|
+
+## References
+
+https://huggingface.co/sahilml/promptEngPromptClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-pubmed_clip_vit_base_patch32_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-pubmed_clip_vit_base_patch32_pipeline_en.md
new file mode 100644
index 00000000000000..8154cf72a5a66c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-pubmed_clip_vit_base_patch32_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English pubmed_clip_vit_base_patch32_pipeline pipeline CLIPForZeroShotClassification from flaviagiammarino
+author: John Snow Labs
+name: pubmed_clip_vit_base_patch32_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubmed_clip_vit_base_patch32_pipeline` is a English model originally trained by flaviagiammarino.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubmed_clip_vit_base_patch32_pipeline_en_5.5.0_3.0_1725491392900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubmed_clip_vit_base_patch32_pipeline_en_5.5.0_3.0_1725491392900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pubmed_clip_vit_base_patch32_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pubmed_clip_vit_base_patch32_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubmed_clip_vit_base_patch32_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|399.9 MB|
+
+## References
+
+https://huggingface.co/flaviagiammarino/pubmed-clip-vit-base-patch32
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-puri_thai_albert_cased_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-puri_thai_albert_cased_v1_en.md
new file mode 100644
index 00000000000000..d9af2d6ca426cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-puri_thai_albert_cased_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English puri_thai_albert_cased_v1 AlbertEmbeddings from puri
+author: John Snow Labs
+name: puri_thai_albert_cased_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`puri_thai_albert_cased_v1` is a English model originally trained by puri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/puri_thai_albert_cased_v1_en_5.5.0_3.0_1725458177430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/puri_thai_albert_cased_v1_en_5.5.0_3.0_1725458177430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("puri_thai_albert_cased_v1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("puri_thai_albert_cased_v1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|puri_thai_albert_cased_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|804.8 MB|
+
+## References
+
+https://huggingface.co/puri/puri-thai-albert-cased-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-puri_thai_albert_cased_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-puri_thai_albert_cased_v1_pipeline_en.md
new file mode 100644
index 00000000000000..c7a25b20c16d78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-puri_thai_albert_cased_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English puri_thai_albert_cased_v1_pipeline pipeline AlbertEmbeddings from puri
+author: John Snow Labs
+name: puri_thai_albert_cased_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`puri_thai_albert_cased_v1_pipeline` is a English model originally trained by puri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/puri_thai_albert_cased_v1_pipeline_en_5.5.0_3.0_1725458215847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/puri_thai_albert_cased_v1_pipeline_en_5.5.0_3.0_1725458215847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("puri_thai_albert_cased_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("puri_thai_albert_cased_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|puri_thai_albert_cased_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|804.9 MB|
+
+## References
+
+https://huggingface.co/puri/puri-thai-albert-cased-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-qa_synth_03_oct_with_finetune_1_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-qa_synth_03_oct_with_finetune_1_1_en.md
new file mode 100644
index 00000000000000..689289735854bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-qa_synth_03_oct_with_finetune_1_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_synth_03_oct_with_finetune_1_1 XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synth_03_oct_with_finetune_1_1
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_03_oct_with_finetune_1_1` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_03_oct_with_finetune_1_1_en_5.5.0_3.0_1725482307263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_03_oct_with_finetune_1_1_en_5.5.0_3.0_1725482307263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_03_oct_with_finetune_1_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synth_03_oct_with_finetune_1_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synth_03_oct_with_finetune_1_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|808.1 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTH_03_OCT_WITH_FINETUNE_1.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-qa_synth_03_oct_with_finetune_1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-qa_synth_03_oct_with_finetune_1_1_pipeline_en.md
new file mode 100644
index 00000000000000..ba9f88d8eb121f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-qa_synth_03_oct_with_finetune_1_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_synth_03_oct_with_finetune_1_1_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synth_03_oct_with_finetune_1_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_03_oct_with_finetune_1_1_pipeline` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_03_oct_with_finetune_1_1_pipeline_en_5.5.0_3.0_1725482415006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_03_oct_with_finetune_1_1_pipeline_en_5.5.0_3.0_1725482415006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_synth_03_oct_with_finetune_1_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_synth_03_oct_with_finetune_1_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synth_03_oct_with_finetune_1_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|808.1 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTH_03_OCT_WITH_FINETUNE_1.1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-qa_synthetic_data_only_22_aug_xlm_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-04-qa_synthetic_data_only_22_aug_xlm_roberta_base_en.md
new file mode 100644
index 00000000000000..dc1faaa6c4b0a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-qa_synthetic_data_only_22_aug_xlm_roberta_base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_synthetic_data_only_22_aug_xlm_roberta_base XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synthetic_data_only_22_aug_xlm_roberta_base
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synthetic_data_only_22_aug_xlm_roberta_base` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synthetic_data_only_22_aug_xlm_roberta_base_en_5.5.0_3.0_1725481800826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synthetic_data_only_22_aug_xlm_roberta_base_en_5.5.0_3.0_1725481800826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synthetic_data_only_22_aug_xlm_roberta_base","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("qa_synthetic_data_only_22_aug_xlm_roberta_base", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synthetic_data_only_22_aug_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|805.8 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTHETIC_DATA_ONLY_22_AUG_xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..e60f16579bd970
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline_en_5.5.0_3.0_1725481913630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline_en_5.5.0_3.0_1725481913630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synthetic_data_only_22_aug_xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|805.8 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTHETIC_DATA_ONLY_22_AUG_xlm-roberta-base
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-question_answering_roberta_base_s_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-question_answering_roberta_base_s_pipeline_en.md
new file mode 100644
index 00000000000000..81224ed1f311d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-question_answering_roberta_base_s_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English question_answering_roberta_base_s_pipeline pipeline RoBertaForQuestionAnswering from consciousAI
+author: John Snow Labs
+name: question_answering_roberta_base_s_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_roberta_base_s_pipeline` is a English model originally trained by consciousAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_roberta_base_s_pipeline_en_5.5.0_3.0_1725451385463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_roberta_base_s_pipeline_en_5.5.0_3.0_1725451385463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("question_answering_roberta_base_s_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_answering_roberta_base_s_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_roberta_base_s_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|461.9 MB|
+
+## References
+
+https://huggingface.co/consciousAI/question-answering-roberta-base-s
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-readability_spanish_paragraphs_es.md b/docs/_posts/ahmedlone127/2024-09-04-readability_spanish_paragraphs_es.md
new file mode 100644
index 00000000000000..6967367e188c53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-readability_spanish_paragraphs_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish readability_spanish_paragraphs RoBertaForSequenceClassification from somosnlp-hackathon-2022
+author: John Snow Labs
+name: readability_spanish_paragraphs
+date: 2024-09-04
+tags: [es, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`readability_spanish_paragraphs` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2022.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/readability_spanish_paragraphs_es_5.5.0_3.0_1725485268310.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/readability_spanish_paragraphs_es_5.5.0_3.0_1725485268310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("readability_spanish_paragraphs","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("readability_spanish_paragraphs", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|readability_spanish_paragraphs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|444.5 MB|
+
+## References
+
+https://huggingface.co/somosnlp-hackathon-2022/readability-es-paragraphs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-recipes_trainer_wwm_sen_3_sep_true_prefix_true_en.md b/docs/_posts/ahmedlone127/2024-09-04-recipes_trainer_wwm_sen_3_sep_true_prefix_true_en.md
new file mode 100644
index 00000000000000..9caec264d6fa7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-recipes_trainer_wwm_sen_3_sep_true_prefix_true_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English recipes_trainer_wwm_sen_3_sep_true_prefix_true CamemBertEmbeddings from comartinez
+author: John Snow Labs
+name: recipes_trainer_wwm_sen_3_sep_true_prefix_true
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`recipes_trainer_wwm_sen_3_sep_true_prefix_true` is a English model originally trained by comartinez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/recipes_trainer_wwm_sen_3_sep_true_prefix_true_en_5.5.0_3.0_1725444889195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/recipes_trainer_wwm_sen_3_sep_true_prefix_true_en_5.5.0_3.0_1725444889195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("recipes_trainer_wwm_sen_3_sep_true_prefix_true","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("recipes_trainer_wwm_sen_3_sep_true_prefix_true","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|recipes_trainer_wwm_sen_3_sep_true_prefix_true|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/comartinez/recipes-trainer-wwm_sen_3_sep_True_prefix_True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-refpydst_10p_referredstates_split_v3_en.md b/docs/_posts/ahmedlone127/2024-09-04-refpydst_10p_referredstates_split_v3_en.md
new file mode 100644
index 00000000000000..7151f30969ce63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-refpydst_10p_referredstates_split_v3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English refpydst_10p_referredstates_split_v3 MPNetEmbeddings from Brendan
+author: John Snow Labs
+name: refpydst_10p_referredstates_split_v3
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`refpydst_10p_referredstates_split_v3` is a English model originally trained by Brendan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/refpydst_10p_referredstates_split_v3_en_5.5.0_3.0_1725470104153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_10p_referredstates_split_v3_en_5.5.0_3.0_1725470104153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("refpydst_10p_referredstates_split_v3","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("refpydst_10p_referredstates_split_v3","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|refpydst_10p_referredstates_split_v3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Brendan/refpydst-10p-referredstates-split-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-refpydst_10p_referredstates_split_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-refpydst_10p_referredstates_split_v3_pipeline_en.md
new file mode 100644
index 00000000000000..e255562e95d2fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-refpydst_10p_referredstates_split_v3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English refpydst_10p_referredstates_split_v3_pipeline pipeline MPNetEmbeddings from Brendan
+author: John Snow Labs
+name: refpydst_10p_referredstates_split_v3_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`refpydst_10p_referredstates_split_v3_pipeline` is a English model originally trained by Brendan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/refpydst_10p_referredstates_split_v3_pipeline_en_5.5.0_3.0_1725470125315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_10p_referredstates_split_v3_pipeline_en_5.5.0_3.0_1725470125315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("refpydst_10p_referredstates_split_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("refpydst_10p_referredstates_split_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|refpydst_10p_referredstates_split_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Brendan/refpydst-10p-referredstates-split-v3
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-relation_detection_textual_en.md b/docs/_posts/ahmedlone127/2024-09-04-relation_detection_textual_en.md
new file mode 100644
index 00000000000000..030578ced7f924
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-relation_detection_textual_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English relation_detection_textual CamemBertForSequenceClassification from lupobricco
+author: John Snow Labs
+name: relation_detection_textual
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`relation_detection_textual` is a English model originally trained by lupobricco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/relation_detection_textual_en_5.5.0_3.0_1725467001421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/relation_detection_textual_en_5.5.0_3.0_1725467001421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("relation_detection_textual","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("relation_detection_textual", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|relation_detection_textual|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|387.5 MB|
+
+## References
+
+https://huggingface.co/lupobricco/relation_detection_textual
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-results_raj_sharma01_en.md b/docs/_posts/ahmedlone127/2024-09-04-results_raj_sharma01_en.md
new file mode 100644
index 00000000000000..a03d2143e99678
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-results_raj_sharma01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_raj_sharma01 DistilBertForTokenClassification from Raj-sharma01
+author: John Snow Labs
+name: results_raj_sharma01
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_raj_sharma01` is a English model originally trained by Raj-sharma01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_raj_sharma01_en_5.5.0_3.0_1725492656124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_raj_sharma01_en_5.5.0_3.0_1725492656124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("results_raj_sharma01","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("results_raj_sharma01", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_raj_sharma01|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/Raj-sharma01/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-reward_model_deberta_v3_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-reward_model_deberta_v3_base_v2_en.md
new file mode 100644
index 00000000000000..c2db4ff2920e4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-reward_model_deberta_v3_base_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English reward_model_deberta_v3_base_v2 DeBertaForSequenceClassification from theblackcat102
+author: John Snow Labs
+name: reward_model_deberta_v3_base_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reward_model_deberta_v3_base_v2` is a English model originally trained by theblackcat102.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reward_model_deberta_v3_base_v2_en_5.5.0_3.0_1725440533973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reward_model_deberta_v3_base_v2_en_5.5.0_3.0_1725440533973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("reward_model_deberta_v3_base_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("reward_model_deberta_v3_base_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|reward_model_deberta_v3_base_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|679.5 MB|
+
+## References
+
+https://huggingface.co/theblackcat102/reward-model-deberta-v3-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-reward_model_deberta_v3_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-reward_model_deberta_v3_base_v2_pipeline_en.md
new file mode 100644
index 00000000000000..dd9313d0968057
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-reward_model_deberta_v3_base_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English reward_model_deberta_v3_base_v2_pipeline pipeline DeBertaForSequenceClassification from theblackcat102
+author: John Snow Labs
+name: reward_model_deberta_v3_base_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reward_model_deberta_v3_base_v2_pipeline` is a English model originally trained by theblackcat102.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reward_model_deberta_v3_base_v2_pipeline_en_5.5.0_3.0_1725440569354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reward_model_deberta_v3_base_v2_pipeline_en_5.5.0_3.0_1725440569354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("reward_model_deberta_v3_base_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("reward_model_deberta_v3_base_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|reward_model_deberta_v3_base_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|679.5 MB|
+
+## References
+
+https://huggingface.co/theblackcat102/reward-model-deberta-v3-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-rise_ner_distilbert_base_cased_system_a_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-rise_ner_distilbert_base_cased_system_a_v1_en.md
new file mode 100644
index 00000000000000..5264b627248185
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-rise_ner_distilbert_base_cased_system_a_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rise_ner_distilbert_base_cased_system_a_v1 DistilBertForTokenClassification from petersamoaa
+author: John Snow Labs
+name: rise_ner_distilbert_base_cased_system_a_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rise_ner_distilbert_base_cased_system_a_v1` is a English model originally trained by petersamoaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rise_ner_distilbert_base_cased_system_a_v1_en_5.5.0_3.0_1725492702575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rise_ner_distilbert_base_cased_system_a_v1_en_5.5.0_3.0_1725492702575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("rise_ner_distilbert_base_cased_system_a_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("rise_ner_distilbert_base_cased_system_a_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rise_ner_distilbert_base_cased_system_a_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/petersamoaa/rise-ner-distilbert-base-cased-system-a-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-rise_ner_en.md b/docs/_posts/ahmedlone127/2024-09-04-rise_ner_en.md
new file mode 100644
index 00000000000000..6aa6465946d397
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-rise_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rise_ner DistilBertForTokenClassification from mappelgren
+author: John Snow Labs
+name: rise_ner
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rise_ner` is a English model originally trained by mappelgren.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rise_ner_en_5.5.0_3.0_1725475994222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rise_ner_en_5.5.0_3.0_1725475994222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("rise_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("rise_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rise_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/mappelgren/RISE_NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-robako_base_asante_twi_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-04-robako_base_asante_twi_uncased_en.md
new file mode 100644
index 00000000000000..bc726ccde20391
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-robako_base_asante_twi_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English robako_base_asante_twi_uncased RoBertaEmbeddings from Ghana-NLP
+author: John Snow Labs
+name: robako_base_asante_twi_uncased
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robako_base_asante_twi_uncased` is a English model originally trained by Ghana-NLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robako_base_asante_twi_uncased_en_5.5.0_3.0_1725412662143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robako_base_asante_twi_uncased_en_5.5.0_3.0_1725412662143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("robako_base_asante_twi_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("robako_base_asante_twi_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robako_base_asante_twi_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|311.8 MB|
+
+## References
+
+https://huggingface.co/Ghana-NLP/robako-base-asante-twi-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-robbert_v2_dutch_base_finetuned_emotion_dominance_en.md b/docs/_posts/ahmedlone127/2024-09-04-robbert_v2_dutch_base_finetuned_emotion_dominance_en.md
new file mode 100644
index 00000000000000..b82001a0aaa5f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-robbert_v2_dutch_base_finetuned_emotion_dominance_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English robbert_v2_dutch_base_finetuned_emotion_dominance RoBertaForSequenceClassification from antalvdb
+author: John Snow Labs
+name: robbert_v2_dutch_base_finetuned_emotion_dominance
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_v2_dutch_base_finetuned_emotion_dominance` is a English model originally trained by antalvdb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_v2_dutch_base_finetuned_emotion_dominance_en_5.5.0_3.0_1725486110350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_v2_dutch_base_finetuned_emotion_dominance_en_5.5.0_3.0_1725486110350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("robbert_v2_dutch_base_finetuned_emotion_dominance","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("robbert_v2_dutch_base_finetuned_emotion_dominance", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_v2_dutch_base_finetuned_emotion_dominance|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|437.9 MB|
+
+## References
+
+https://huggingface.co/antalvdb/robbert-v2-dutch-base-finetuned-emotion-dominance
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline_en.md
new file mode 100644
index 00000000000000..dbbbf8b66a893e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline pipeline RoBertaForSequenceClassification from antalvdb
+author: John Snow Labs
+name: robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline` is a English model originally trained by antalvdb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline_en_5.5.0_3.0_1725486130866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline_en_5.5.0_3.0_1725486130866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_v2_dutch_base_finetuned_emotion_dominance_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|438.0 MB|
+
+## References
+
+https://huggingface.co/antalvdb/robbert-v2-dutch-base-finetuned-emotion-dominance
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-robert_mlm_en.md b/docs/_posts/ahmedlone127/2024-09-04-robert_mlm_en.md
new file mode 100644
index 00000000000000..4e3d401767d864
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-robert_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English robert_mlm RoBertaEmbeddings from ugiugi
+author: John Snow Labs
+name: robert_mlm
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robert_mlm` is a English model originally trained by ugiugi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robert_mlm_en_5.5.0_3.0_1725412667519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robert_mlm_en_5.5.0_3.0_1725412667519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("robert_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("robert_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robert_mlm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/ugiugi/RoBERT-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-robert_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-robert_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..035ac24005784f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-robert_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English robert_mlm_pipeline pipeline RoBertaEmbeddings from ugiugi
+author: John Snow Labs
+name: robert_mlm_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robert_mlm_pipeline` is a English model originally trained by ugiugi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robert_mlm_pipeline_en_5.5.0_3.0_1725412692090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robert_mlm_pipeline_en_5.5.0_3.0_1725412692090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("robert_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robert_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robert_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/ugiugi/RoBERT-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_biomedical_spanish_bsc_lt_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_biomedical_spanish_bsc_lt_pipeline_es.md
new file mode 100644
index 00000000000000..19b0ee055e3962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_biomedical_spanish_bsc_lt_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_spanish_bsc_lt_pipeline pipeline RoBertaEmbeddings from BSC-LT
+author: John Snow Labs
+name: roberta_base_biomedical_spanish_bsc_lt_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_spanish_bsc_lt_pipeline` is a Castilian, Spanish model originally trained by BSC-LT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_bsc_lt_pipeline_es_5.5.0_3.0_1725413167686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_bsc_lt_pipeline_es_5.5.0_3.0_1725413167686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_biomedical_spanish_bsc_lt_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_biomedical_spanish_bsc_lt_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_spanish_bsc_lt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|299.0 MB|
+
+## References
+
+https://huggingface.co/BSC-LT/roberta-base-biomedical-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_fine_tuned_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_fine_tuned_en.md
new file mode 100644
index 00000000000000..acdee6a44050d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_fine_tuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_base_fine_tuned RoBertaForQuestionAnswering from ClemMbote
+author: John Snow Labs
+name: roberta_base_fine_tuned
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_fine_tuned` is a English model originally trained by ClemMbote.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_fine_tuned_en_5.5.0_3.0_1725479184062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_fine_tuned_en_5.5.0_3.0_1725479184062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_fine_tuned","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_fine_tuned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_fine_tuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|450.3 MB|
+
+## References
+
+https://huggingface.co/ClemMbote/roberta-base-fine-tuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_hate_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_hate_en.md
new file mode 100644
index 00000000000000..cd1e6a4d5f264d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_hate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_hate RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: roberta_base_hate
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_hate` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_hate_en_5.5.0_3.0_1725485444813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_hate_en_5.5.0_3.0_1725485444813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_hate","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_hate", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_hate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|441.2 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/roberta-base-hate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_imdb_mtreviso_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_imdb_mtreviso_en.md
new file mode 100644
index 00000000000000..e0d618a7dd0e35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_imdb_mtreviso_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_imdb_mtreviso RoBertaForSequenceClassification from mtreviso
+author: John Snow Labs
+name: roberta_base_imdb_mtreviso
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_imdb_mtreviso` is a English model originally trained by mtreviso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_imdb_mtreviso_en_5.5.0_3.0_1725452938648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_imdb_mtreviso_en_5.5.0_3.0_1725452938648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_imdb_mtreviso","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_imdb_mtreviso", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_imdb_mtreviso|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|465.0 MB|
+
+## References
+
+https://huggingface.co/mtreviso/roberta-base-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_imdb_mtreviso_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_imdb_mtreviso_pipeline_en.md
new file mode 100644
index 00000000000000..7e64da9d0e470c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_imdb_mtreviso_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_imdb_mtreviso_pipeline pipeline RoBertaForSequenceClassification from mtreviso
+author: John Snow Labs
+name: roberta_base_imdb_mtreviso_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_imdb_mtreviso_pipeline` is a English model originally trained by mtreviso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_imdb_mtreviso_pipeline_en_5.5.0_3.0_1725452962042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_imdb_mtreviso_pipeline_en_5.5.0_3.0_1725452962042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_imdb_mtreviso_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_imdb_mtreviso_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_imdb_mtreviso_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.1 MB|
+
+## References
+
+https://huggingface.co/mtreviso/roberta-base-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_miguelpr_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_miguelpr_en.md
new file mode 100644
index 00000000000000..bcec48eaee66ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_miguelpr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_miguelpr RoBertaForSequenceClassification from miguelpr
+author: John Snow Labs
+name: roberta_base_miguelpr
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_miguelpr` is a English model originally trained by miguelpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_miguelpr_en_5.5.0_3.0_1725452655855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_miguelpr_en_5.5.0_3.0_1725452655855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_miguelpr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_miguelpr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_miguelpr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|437.4 MB|
+
+## References
+
+https://huggingface.co/miguelpr/roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_miguelpr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_miguelpr_pipeline_en.md
new file mode 100644
index 00000000000000..3117ce404cf5ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_miguelpr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_miguelpr_pipeline pipeline RoBertaForSequenceClassification from miguelpr
+author: John Snow Labs
+name: roberta_base_miguelpr_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_miguelpr_pipeline` is a English model originally trained by miguelpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_miguelpr_pipeline_en_5.5.0_3.0_1725452689404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_miguelpr_pipeline_en_5.5.0_3.0_1725452689404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_miguelpr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_miguelpr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_miguelpr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|437.4 MB|
+
+## References
+
+https://huggingface.co/miguelpr/roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_namecalling_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_namecalling_en.md
new file mode 100644
index 00000000000000..459a98897d628e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_namecalling_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_namecalling RoBertaForSequenceClassification from civility-lab
+author: John Snow Labs
+name: roberta_base_namecalling
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_namecalling` is a English model originally trained by civility-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_namecalling_en_5.5.0_3.0_1725485136155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_namecalling_en_5.5.0_3.0_1725485136155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_namecalling","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_namecalling", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_namecalling|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|451.2 MB|
+
+## References
+
+https://huggingface.co/civility-lab/roberta-base-namecalling
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_namecalling_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_namecalling_pipeline_en.md
new file mode 100644
index 00000000000000..a70e896e51f87c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_namecalling_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_namecalling_pipeline pipeline RoBertaForSequenceClassification from civility-lab
+author: John Snow Labs
+name: roberta_base_namecalling_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_namecalling_pipeline` is a English model originally trained by civility-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_namecalling_pipeline_en_5.5.0_3.0_1725485164844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_namecalling_pipeline_en_5.5.0_3.0_1725485164844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_namecalling_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_namecalling_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_namecalling_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|451.2 MB|
+
+## References
+
+https://huggingface.co/civility-lab/roberta-base-namecalling
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_spanish_es.md
new file mode 100644
index 00000000000000..b34781660be2e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_spanish_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_spanish RoBertaEmbeddings from ClassCat
+author: John Snow Labs
+name: roberta_base_spanish
+date: 2024-09-04
+tags: [es, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_spanish` is a Castilian, Spanish model originally trained by ClassCat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_spanish_es_5.5.0_3.0_1725412514543.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_spanish_es_5.5.0_3.0_1725412514543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_spanish","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_spanish","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|es|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/ClassCat/roberta-base-spanish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..17df16f636b409
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_spanish_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_spanish_pipeline pipeline RoBertaEmbeddings from ClassCat
+author: John Snow Labs
+name: roberta_base_spanish_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_spanish_pipeline` is a Castilian, Spanish model originally trained by ClassCat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_spanish_pipeline_es_5.5.0_3.0_1725412542004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_spanish_pipeline_es_5.5.0_3.0_1725412542004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/ClassCat/roberta-base-spanish
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline_en.md
new file mode 100644
index 00000000000000..ade9bdd27ff5ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline pipeline RoBertaForQuestionAnswering from themariolinml
+author: John Snow Labs
+name: roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline` is a English model originally trained by themariolinml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline_en_5.5.0_3.0_1725479991429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline_en_5.5.0_3.0_1725479991429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_sqaud2_on_medical_meadow_medqa_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+https://huggingface.co/themariolinml/roberta-base-sqaud2-on-medical_meadow_medqa-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_dourc_squad_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_dourc_squad_en.md
new file mode 100644
index 00000000000000..a1ad589546e9f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_dourc_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_base_squad2_finetuned_dourc_squad RoBertaForQuestionAnswering from suthanhcong
+author: John Snow Labs
+name: roberta_base_squad2_finetuned_dourc_squad
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_finetuned_dourc_squad` is a English model originally trained by suthanhcong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_dourc_squad_en_5.5.0_3.0_1725479333174.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_dourc_squad_en_5.5.0_3.0_1725479333174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_finetuned_dourc_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_finetuned_dourc_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad2_finetuned_dourc_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.5 MB|
+
+## References
+
+https://huggingface.co/suthanhcong/roberta-base-squad2-finetuned-DouRC_squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_en.md
new file mode 100644
index 00000000000000..d2d04c88839e59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English roberta_base_squad2_finetuned RoBertaForQuestionAnswering from DeepaKrish
+author: John Snow Labs
+name: roberta_base_squad2_finetuned
+date: 2024-09-04
+tags: [roberta, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_finetuned` is a English model originally trained by DeepaKrish.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_en_5.5.0_3.0_1725483576476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_en_5.5.0_3.0_1725483576476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_finetuned","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering  
+    .pretrained("roberta_base_squad2_finetuned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad2_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/DeepaKrish/roberta-base-squad2-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad_i8_f32_p65_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad_i8_f32_p65_en.md
new file mode 100644
index 00000000000000..be3fd1e0ba41ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad_i8_f32_p65_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_base_squad_i8_f32_p65 RoBertaForQuestionAnswering from pminha
+author: John Snow Labs
+name: roberta_base_squad_i8_f32_p65
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad_i8_f32_p65` is a English model originally trained by pminha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad_i8_f32_p65_en_5.5.0_3.0_1725483535279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad_i8_f32_p65_en_5.5.0_3.0_1725483535279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad_i8_f32_p65","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad_i8_f32_p65", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad_i8_f32_p65|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|209.8 MB|
+
+## References
+
+https://huggingface.co/pminha/roberta-base-squad-i8-f32-p65
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad_i8_f32_p65_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad_i8_f32_p65_pipeline_en.md
new file mode 100644
index 00000000000000..3259828edea0fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad_i8_f32_p65_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_squad_i8_f32_p65_pipeline pipeline RoBertaForQuestionAnswering from pminha
+author: John Snow Labs
+name: roberta_base_squad_i8_f32_p65_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad_i8_f32_p65_pipeline` is a English model originally trained by pminha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_squad_i8_f32_p65_pipeline_en_5.5.0_3.0_1725483562925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad_i8_f32_p65_pipeline_en_5.5.0_3.0_1725483562925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_squad_i8_f32_p65_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_squad_i8_f32_p65_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad_i8_f32_p65_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|209.8 MB|
+
+## References
+
+https://huggingface.co/pminha/roberta-base-squad-i8-f32-p65
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_classifier_base_bne_finetuned_cyberbullying_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_classifier_base_bne_finetuned_cyberbullying_spanish_es.md
new file mode 100644
index 00000000000000..40dfb864af6300
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_classifier_base_bne_finetuned_cyberbullying_spanish_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish roberta_classifier_base_bne_finetuned_cyberbullying_spanish RoBertaForSequenceClassification from JonatanGk
+author: John Snow Labs
+name: roberta_classifier_base_bne_finetuned_cyberbullying_spanish
+date: 2024-09-04
+tags: [es, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_base_bne_finetuned_cyberbullying_spanish` is a Castilian, Spanish model originally trained by JonatanGk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_classifier_base_bne_finetuned_cyberbullying_spanish_es_5.5.0_3.0_1725452801363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_base_bne_finetuned_cyberbullying_spanish_es_5.5.0_3.0_1725452801363.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_classifier_base_bne_finetuned_cyberbullying_spanish","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_base_bne_finetuned_cyberbullying_spanish", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_classifier_base_bne_finetuned_cyberbullying_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|464.6 MB|
+
+## References
+
+https://huggingface.co/JonatanGk/roberta-base-bne-finetuned-cyberbullying-spanish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_echr_truncated_facts_all_labels_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_echr_truncated_facts_all_labels_en.md
new file mode 100644
index 00000000000000..699dd7e6fe26f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_echr_truncated_facts_all_labels_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_echr_truncated_facts_all_labels RoBertaForSequenceClassification from LawItApps
+author: John Snow Labs
+name: roberta_echr_truncated_facts_all_labels
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_echr_truncated_facts_all_labels` is a English model originally trained by LawItApps.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_echr_truncated_facts_all_labels_en_5.5.0_3.0_1725485424931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_echr_truncated_facts_all_labels_en_5.5.0_3.0_1725485424931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_echr_truncated_facts_all_labels","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_echr_truncated_facts_all_labels", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_echr_truncated_facts_all_labels|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|456.6 MB|
+
+## References
+
+https://huggingface.co/LawItApps/roberta_echr_truncated_facts_all_labels
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_machinesfaults_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_machinesfaults_pipeline_en.md
new file mode 100644
index 00000000000000..c1713e06d6ce07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_machinesfaults_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_machinesfaults_pipeline pipeline RoBertaForQuestionAnswering from mbarte
+author: John Snow Labs
+name: roberta_finetuned_machinesfaults_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_machinesfaults_pipeline` is a English model originally trained by mbarte.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_machinesfaults_pipeline_en_5.5.0_3.0_1725483742159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_machinesfaults_pipeline_en_5.5.0_3.0_1725483742159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_machinesfaults_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_machinesfaults_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_machinesfaults_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/mbarte/roberta_finetuned_machinesfaults
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_squad_noushsuon_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_squad_noushsuon_en.md
new file mode 100644
index 00000000000000..b8aaf3e7ccb80c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_squad_noushsuon_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_squad_noushsuon RoBertaForQuestionAnswering from noushsuon
+author: John Snow Labs
+name: roberta_finetuned_squad_noushsuon
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_squad_noushsuon` is a English model originally trained by noushsuon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_squad_noushsuon_en_5.5.0_3.0_1725479448875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_squad_noushsuon_en_5.5.0_3.0_1725479448875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_squad_noushsuon","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_squad_noushsuon", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_squad_noushsuon|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|461.9 MB|
+
+## References
+
+https://huggingface.co/noushsuon/roberta-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_squad_noushsuon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_squad_noushsuon_pipeline_en.md
new file mode 100644
index 00000000000000..43416a2ba526ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_squad_noushsuon_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_squad_noushsuon_pipeline pipeline RoBertaForQuestionAnswering from noushsuon
+author: John Snow Labs
+name: roberta_finetuned_squad_noushsuon_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_squad_noushsuon_pipeline` is a English model originally trained by noushsuon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_squad_noushsuon_pipeline_en_5.5.0_3.0_1725479473218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_squad_noushsuon_pipeline_en_5.5.0_3.0_1725479473218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_squad_noushsuon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_squad_noushsuon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_squad_noushsuon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|461.9 MB|
+
+## References
+
+https://huggingface.co/noushsuon/roberta-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_event_model_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_event_model_en.md
new file mode 100644
index 00000000000000..18b7d6af149e4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_event_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_event_model RoBertaForQuestionAnswering from nageen
+author: John Snow Labs
+name: roberta_finetuned_subjqa_event_model
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_event_model` is a English model originally trained by nageen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_event_model_en_5.5.0_3.0_1725483954286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_event_model_en_5.5.0_3.0_1725483954286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_event_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_event_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_event_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/nageen/roberta-finetuned-subjqa-event_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_event_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_event_model_pipeline_en.md
new file mode 100644
index 00000000000000..fa65823061aa17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_event_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_event_model_pipeline pipeline RoBertaForQuestionAnswering from nageen
+author: John Snow Labs
+name: roberta_finetuned_subjqa_event_model_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_event_model_pipeline` is a English model originally trained by nageen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_event_model_pipeline_en_5.5.0_3.0_1725483976506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_event_model_pipeline_en_5.5.0_3.0_1725483976506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_subjqa_event_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_event_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_event_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/nageen/roberta-finetuned-subjqa-event_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_1110pm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_1110pm_pipeline_en.md
new file mode 100644
index 00000000000000..add728c13d6ad2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_1110pm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_movies_1110pm_pipeline pipeline RoBertaForQuestionAnswering from 96harsh56
+author: John Snow Labs
+name: roberta_finetuned_subjqa_movies_1110pm_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_1110pm_pipeline` is a English model originally trained by 96harsh56.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_1110pm_pipeline_en_5.5.0_3.0_1725451718394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_1110pm_pipeline_en_5.5.0_3.0_1725451718394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_1110pm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_1110pm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_movies_1110pm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.5 MB|
+
+## References
+
+https://huggingface.co/96harsh56/roberta-finetuned-subjqa-movies_1110pm
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline_en.md
new file mode 100644
index 00000000000000..f585822ce2928d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline pipeline RoBertaForQuestionAnswering from Jose-Ribeir
+author: John Snow Labs
+name: roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline` is a English model originally trained by Jose-Ribeir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline_en_5.5.0_3.0_1725479095259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline_en_5.5.0_3.0_1725479095259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_movies_2_jose_ribeir_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.5 MB|
+
+## References
+
+https://huggingface.co/Jose-Ribeir/roberta-finetuned-subjqa-movies_2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_ngchuchi_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_ngchuchi_en.md
new file mode 100644
index 00000000000000..dff8118a7b77d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_ngchuchi_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_movies_2_ngchuchi RoBertaForQuestionAnswering from ngchuchi
+author: John Snow Labs
+name: roberta_finetuned_subjqa_movies_2_ngchuchi
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_ngchuchi` is a English model originally trained by ngchuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_ngchuchi_en_5.5.0_3.0_1725484083333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_ngchuchi_en_5.5.0_3.0_1725484083333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_ngchuchi","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_ngchuchi", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_movies_2_ngchuchi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/roberta-finetuned-subjqa-movies_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline_en.md
new file mode 100644
index 00000000000000..c8fbe1f10d40b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline pipeline RoBertaForQuestionAnswering from ngchuchi
+author: John Snow Labs
+name: roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline` is a English model originally trained by ngchuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline_en_5.5.0_3.0_1725484105841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline_en_5.5.0_3.0_1725484105841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_movies_2_ngchuchi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/roberta-finetuned-subjqa-movies_2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_soumiknayak_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_soumiknayak_en.md
new file mode 100644
index 00000000000000..cca605334aea3d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_finetuned_subjqa_movies_2_soumiknayak_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_movies_2_soumiknayak RoBertaForQuestionAnswering from SoumikNayak
+author: John Snow Labs
+name: roberta_finetuned_subjqa_movies_2_soumiknayak
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_soumiknayak` is a English model originally trained by SoumikNayak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_soumiknayak_en_5.5.0_3.0_1725483334697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_soumiknayak_en_5.5.0_3.0_1725483334697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_soumiknayak","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_soumiknayak", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_movies_2_soumiknayak|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/SoumikNayak/roberta-finetuned-subjqa-movies_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_korean_small_ko.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_korean_small_ko.md
new file mode 100644
index 00000000000000..bf651c44c5efb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_korean_small_ko.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Korean roberta_korean_small RoBertaEmbeddings from lassl
+author: John Snow Labs
+name: roberta_korean_small
+date: 2024-09-04
+tags: [ko, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_korean_small` is a Korean model originally trained by lassl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_korean_small_ko_5.5.0_3.0_1725412319252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_korean_small_ko_5.5.0_3.0_1725412319252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_korean_small","ko") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_korean_small","ko") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_korean_small|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|ko|
+|Size:|86.3 MB|
+
+## References
+
+https://huggingface.co/lassl/roberta-ko-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_korean_small_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_korean_small_pipeline_ko.md
new file mode 100644
index 00000000000000..7bc4ee81ff9e1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_korean_small_pipeline_ko.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Korean roberta_korean_small_pipeline pipeline RoBertaEmbeddings from lassl
+author: John Snow Labs
+name: roberta_korean_small_pipeline
+date: 2024-09-04
+tags: [ko, open_source, pipeline, onnx]
+task: Embeddings
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_korean_small_pipeline` is a Korean model originally trained by lassl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_korean_small_pipeline_ko_5.5.0_3.0_1725412323783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_korean_small_pipeline_ko_5.5.0_3.0_1725412323783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_korean_small_pipeline", lang = "ko")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_korean_small_pipeline", lang = "ko")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_korean_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ko|
+|Size:|86.4 MB|
+
+## References
+
+https://huggingface.co/lassl/roberta-ko-small
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_large_cuad_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_large_cuad_en.md
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@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_large_cuad RoBertaForQuestionAnswering from mgigena
+author: John Snow Labs
+name: roberta_large_cuad
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_cuad` is a English model originally trained by mgigena.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_cuad_en_5.5.0_3.0_1725483420949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_cuad_en_5.5.0_3.0_1725483420949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_cuad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_cuad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_cuad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mgigena/roberta-large-cuad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_large_cuad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_large_cuad_pipeline_en.md
new file mode 100644
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_large_cuad_pipeline pipeline RoBertaForQuestionAnswering from mgigena
+author: John Snow Labs
+name: roberta_large_cuad_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_cuad_pipeline` is a English model originally trained by mgigena.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_cuad_pipeline_en_5.5.0_3.0_1725483494368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_cuad_pipeline_en_5.5.0_3.0_1725483494368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_cuad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_cuad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_cuad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mgigena/roberta-large-cuad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_large_nqtqatrecwqsqd_mrc_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_large_nqtqatrecwqsqd_mrc_en.md
new file mode 100644
index 00000000000000..95f04676d17646
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_large_nqtqatrecwqsqd_mrc_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_large_nqtqatrecwqsqd_mrc RoBertaForQuestionAnswering from dmis-lab
+author: John Snow Labs
+name: roberta_large_nqtqatrecwqsqd_mrc
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_nqtqatrecwqsqd_mrc` is a English model originally trained by dmis-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_nqtqatrecwqsqd_mrc_en_5.5.0_3.0_1725484442890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_nqtqatrecwqsqd_mrc_en_5.5.0_3.0_1725484442890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_nqtqatrecwqsqd_mrc","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_nqtqatrecwqsqd_mrc", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_nqtqatrecwqsqd_mrc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/dmis-lab/roberta-large-nqtqatrecwqsqd-mrc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_large_nqtqatrecwqsqd_mrc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_large_nqtqatrecwqsqd_mrc_pipeline_en.md
new file mode 100644
index 00000000000000..36aeb3dca44b08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_large_nqtqatrecwqsqd_mrc_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_large_nqtqatrecwqsqd_mrc_pipeline pipeline RoBertaForQuestionAnswering from dmis-lab
+author: John Snow Labs
+name: roberta_large_nqtqatrecwqsqd_mrc_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_nqtqatrecwqsqd_mrc_pipeline` is a English model originally trained by dmis-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_nqtqatrecwqsqd_mrc_pipeline_en_5.5.0_3.0_1725484504464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_nqtqatrecwqsqd_mrc_pipeline_en_5.5.0_3.0_1725484504464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_nqtqatrecwqsqd_mrc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_nqtqatrecwqsqd_mrc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_nqtqatrecwqsqd_mrc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/dmis-lab/roberta-large-nqtqatrecwqsqd-mrc
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_model_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_model_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_model RoBertaForQuestionAnswering from mihaien
+author: John Snow Labs
+name: roberta_model
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_model` is a English model originally trained by mihaien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_model_en_5.5.0_3.0_1725450898404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_model_en_5.5.0_3.0_1725450898404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|462.9 MB|
+
+## References
+
+https://huggingface.co/mihaien/roberta-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_model_pipeline_en.md
new file mode 100644
index 00000000000000..3edbc08bb4859e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_model_pipeline pipeline RoBertaForQuestionAnswering from mihaien
+author: John Snow Labs
+name: roberta_model_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_model_pipeline` is a English model originally trained by mihaien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_model_pipeline_en_5.5.0_3.0_1725450921358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_model_pipeline_en_5.5.0_3.0_1725450921358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.9 MB|
+
+## References
+
+https://huggingface.co/mihaien/roberta-model
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_mrqa_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_mrqa_en.md
new file mode 100644
index 00000000000000..95f5021dd4c931
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_mrqa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_mrqa RoBertaForQuestionAnswering from enriquesaou
+author: John Snow Labs
+name: roberta_mrqa
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_mrqa` is a English model originally trained by enriquesaou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_mrqa_en_5.5.0_3.0_1725483879313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_mrqa_en_5.5.0_3.0_1725483879313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_mrqa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_mrqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_mrqa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.9 MB|
+
+## References
+
+https://huggingface.co/enriquesaou/roberta-mrqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline_en.md
new file mode 100644
index 00000000000000..73284c27980a6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline pipeline RoBertaForQuestionAnswering from AyushPJ
+author: John Snow Labs
+name: roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline` is a English model originally trained by AyushPJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline_en_5.5.0_3.0_1725451243370.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline_en_5.5.0_3.0_1725451243370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_ai_club_inductions_21_nlp_roBERTa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.6 MB|
+
+## References
+
+https://huggingface.co/AyushPJ/ai-club-inductions-21-nlp-roBERTa
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_base_spanish_squades_becasincentivos2_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_base_spanish_squades_becasincentivos2_pipeline_es.md
new file mode 100644
index 00000000000000..1b4022df217c25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_base_spanish_squades_becasincentivos2_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish roberta_qa_base_spanish_squades_becasincentivos2_pipeline pipeline RoBertaForQuestionAnswering from Evelyn18
+author: John Snow Labs
+name: roberta_qa_base_spanish_squades_becasincentivos2_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_spanish_squades_becasincentivos2_pipeline` is a Castilian, Spanish model originally trained by Evelyn18.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasincentivos2_pipeline_es_5.5.0_3.0_1725479307058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_spanish_squades_becasincentivos2_pipeline_es_5.5.0_3.0_1725479307058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_base_spanish_squades_becasincentivos2_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_base_spanish_squades_becasincentivos2_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_base_spanish_squades_becasincentivos2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|459.1 MB|
+
+## References
+
+https://huggingface.co/Evelyn18/roberta-base-spanish-squades-becasIncentivos2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_canard_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_canard_en.md
new file mode 100644
index 00000000000000..33cb40440c0f33
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_canard_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Cased model (from peggyhuang)
+author: John Snow Labs
+name: roberta_qa_canard
+date: 2024-09-04
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-canard` is a English model originally trained by `peggyhuang`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_canard_en_5.5.0_3.0_1725479431497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_canard_en_5.5.0_3.0_1725479431497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_canard","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_canard","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_canard|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/peggyhuang/roberta-canard
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_checkpoint_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_checkpoint_finetuned_squad_en.md
new file mode 100644
index 00000000000000..db23f659482287
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_checkpoint_finetuned_squad_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Cased model (from xinranyyyy)
+author: John Snow Labs
+name: roberta_qa_checkpoint_finetuned_squad
+date: 2024-09-04
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta_checkpoint-finetuned-squad` is a English model originally trained by `xinranyyyy`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_checkpoint_finetuned_squad_en_5.5.0_3.0_1725451034730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_checkpoint_finetuned_squad_en_5.5.0_3.0_1725451034730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_checkpoint_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_checkpoint_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_checkpoint_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/xinranyyyy/roberta_checkpoint-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_checkpoint_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_checkpoint_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..d869c08581c2dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_checkpoint_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_checkpoint_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from xinranyyyy
+author: John Snow Labs
+name: roberta_qa_checkpoint_finetuned_squad_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_checkpoint_finetuned_squad_pipeline` is a English model originally trained by xinranyyyy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_checkpoint_finetuned_squad_pipeline_en_5.5.0_3.0_1725451060827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_checkpoint_finetuned_squad_pipeline_en_5.5.0_3.0_1725451060827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_checkpoint_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_checkpoint_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_checkpoint_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.8 MB|
+
+## References
+
+https://huggingface.co/xinranyyyy/roberta_checkpoint-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_cline_squad2.0_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_cline_squad2.0_en.md
new file mode 100644
index 00000000000000..b5b2546a5a9c19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_cline_squad2.0_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from AnonymousSub)
+author: John Snow Labs
+name: roberta_qa_cline_squad2.0
+date: 2024-09-04
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `cline_squad2.0` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_cline_squad2.0_en_5.5.0_3.0_1725451633001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_cline_squad2.0_en_5.5.0_3.0_1725451633001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_cline_squad2.0","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_cline_squad2.0","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.roberta.cline.by_AnonymousSub").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_cline_squad2.0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|465.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/cline_squad2.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_cline_squad2.0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_cline_squad2.0_pipeline_en.md
new file mode 100644
index 00000000000000..e1fe593bff6c7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_cline_squad2.0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_cline_squad2.0_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_cline_squad2.0_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_cline_squad2.0_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_cline_squad2.0_pipeline_en_5.5.0_3.0_1725451660233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_cline_squad2.0_pipeline_en_5.5.0_3.0_1725451660233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_cline_squad2.0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_cline_squad2.0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_cline_squad2.0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.6 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/cline_squad2.0
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_finetuned_city_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_finetuned_city_en.md
new file mode 100644
index 00000000000000..4dfe2d7e5a9bed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_finetuned_city_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Cased model (from skandaonsolve)
+author: John Snow Labs
+name: roberta_qa_finetuned_city
+date: 2024-09-04
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-finetuned-city` is a English model originally trained by `skandaonsolve`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_city_en_5.5.0_3.0_1725450750498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_city_en_5.5.0_3.0_1725450750498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_city","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_city","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_finetuned_city|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.9 MB|
+
+## References
+
+References
+
+- https://huggingface.co/skandaonsolve/roberta-finetuned-city
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline_en.md
new file mode 100644
index 00000000000000..017d7f7af92994
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline_en_5.5.0_3.0_1725451199760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline_en_5.5.0_3.0_1725451199760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_fpdm_hier_roberta_FT_newsqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|457.8 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/fpdm_hier_roberta_FT_newsqa
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_fpdm_roberta_FT_newsqa_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_fpdm_roberta_FT_newsqa_en.md
new file mode 100644
index 00000000000000..4c212c6f38dff8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_fpdm_roberta_FT_newsqa_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from AnonymousSub)
+author: John Snow Labs
+name: roberta_qa_fpdm_roberta_FT_newsqa
+date: 2024-09-04
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `fpdm_roberta_FT_newsqa` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_fpdm_roberta_FT_newsqa_en_5.5.0_3.0_1725451796649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_fpdm_roberta_FT_newsqa_en_5.5.0_3.0_1725451796649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_fpdm_roberta_FT_newsqa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_fpdm_roberta_FT_newsqa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.news.roberta.qa_fpdm_roberta_ft_newsqa.by_AnonymousSub").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_fpdm_roberta_FT_newsqa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|457.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/fpdm_roberta_FT_newsqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en.md
new file mode 100644
index 00000000000000..36d16ddbebc331
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en_5.5.0_3.0_1725479048350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline_en_5.5.0_3.0_1725479048350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_large_few_shot_k_1024_finetuned_squad_seed_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-1024-finetuned-squad-seed-4
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_squad_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_squad_en.md
new file mode 100644
index 00000000000000..26b2df6902eb0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_squad_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Large Cased model (from susghosh)
+author: John Snow Labs
+name: roberta_qa_large_squad
+date: 2024-09-04
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-squad` is a English model originally trained by `susghosh`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_large_squad_en_5.5.0_3.0_1725451033501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_large_squad_en_5.5.0_3.0_1725451033501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_large_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_large_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_large_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/susghosh/roberta-large-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_es.md
new file mode 100644
index 00000000000000..3dfe03916c4779
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_es.md
@@ -0,0 +1,107 @@
+---
+layout: model
+title: Spanish RobertaForQuestionAnswering (from mrm8488)
+author: John Snow Labs
+name: roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac
+date: 2024-09-04
+tags: [es, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-bne-finetuned-sqac` is a Spanish model originally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_es_5.5.0_3.0_1725450786768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_es_5.5.0_3.0_1725450786768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac","es") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac","es")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("es.answer_question.sqac.roberta.base.by_mrm8488").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|459.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/roberta-base-bne-finetuned-sqac
+- https://paperswithcode.com/sota?task=Question+Answering&dataset=sqac
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline_es.md
new file mode 100644
index 00000000000000..97caa958ccbe97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline pipeline RoBertaForQuestionAnswering from mrm8488
+author: John Snow Labs
+name: roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline` is a Castilian, Spanish model originally trained by mrm8488.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline_es_5.5.0_3.0_1725450811408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline_es_5.5.0_3.0_1725450811408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|459.7 MB|
+
+## References
+
+https://huggingface.co/mrm8488/roberta-base-bne-finetuned-sqac
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline_en.md
new file mode 100644
index 00000000000000..3185c188de0f99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline_en_5.5.0_3.0_1725479484203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline_en_5.5.0_3.0_1725479484203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_news_pretrain_roberta_FT_newsqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/news_pretrain_roberta_FT_newsqa
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..30ba85ec8734dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Base Cased model (from AnonymousSub)
+author: John Snow Labs
+name: roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3
+date: 2024-09-04
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_recipes-roberta-base_EASY_TIMESTEP_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_en_5.5.0_3.0_1725450750490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_en_5.5.0_3.0_1725450750490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_recipes-roberta-base_EASY_TIMESTEP_squadv2_epochs_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline_en.md
new file mode 100644
index 00000000000000..d55e7c2174065b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline_en_5.5.0_3.0_1725450777398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline_en_5.5.0_3.0_1725450777398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_recipe_triplet_recipes_base_easy_timestep_squadv2_epochs_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/recipe_triplet_recipes-roberta-base_EASY_TIMESTEP_squadv2_epochs_3
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_chaii_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_chaii_en.md
new file mode 100644
index 00000000000000..1511c99873a073
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_chaii_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from SauravMaheshkar)
+author: John Snow Labs
+name: roberta_qa_roberta_base_chaii
+date: 2024-09-04
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-chaii` is a English model originally trained by `SauravMaheshkar`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_chaii_en_5.5.0_3.0_1725479103035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_chaii_en_5.5.0_3.0_1725479103035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_chaii","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_chaii","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.chaii.roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_chaii|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.0 MB|
+
+## References
+
+References
+
+- https://huggingface.co/SauravMaheshkar/roberta-base-chaii
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_en.md
new file mode 100644
index 00000000000000..e774a8b1fd933c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from anas-awadalla)
+author: John Snow Labs
+name: roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4
+date: 2024-09-04
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-few-shot-k-128-finetuned-squad-seed-4` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_en_5.5.0_3.0_1725451593462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_en_5.5.0_3.0_1725451593462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.roberta.base_128d_seed_4").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|422.5 MB|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-128-finetuned-squad-seed-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline_en.md
new file mode 100644
index 00000000000000..7fd92198fd4f30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline_en_5.5.0_3.0_1725451633247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline_en_5.5.0_3.0_1725451633247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|422.5 MB|
+
+## References
+
+https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-128-finetuned-squad-seed-4
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_en.md
new file mode 100644
index 00000000000000..46a4f7fa96855b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from anas-awadalla)
+author: John Snow Labs
+name: roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6
+date: 2024-09-04
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-few-shot-k-32-finetuned-squad-seed-6` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_en_5.5.0_3.0_1725479052864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_en_5.5.0_3.0_1725479052864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.roberta.base_32d_seed_6").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|416.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-32-finetuned-squad-seed-6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline_en.md
new file mode 100644
index 00000000000000..e329bf365eab80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline_en_5.5.0_3.0_1725479098207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline_en_5.5.0_3.0_1725479098207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|416.6 MB|
+
+## References
+
+https://huggingface.co/anas-awadalla/roberta-base-few-shot-k-32-finetuned-squad-seed-6
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_l_squadv1.1_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_l_squadv1.1_en.md
new file mode 100644
index 00000000000000..a95cab5238d62c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_l_squadv1.1_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from vuiseng9)
+author: John Snow Labs
+name: roberta_qa_roberta_l_squadv1.1
+date: 2024-09-04
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-l-squadv1.1` is a English model originally trained by `vuiseng9`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_l_squadv1.1_en_5.5.0_3.0_1725451581063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_l_squadv1.1_en_5.5.0_3.0_1725451581063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_l_squadv1.1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_l_squadv1.1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.roberta").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_l_squadv1.1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/vuiseng9/roberta-l-squadv1.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_l_squadv1.1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_l_squadv1.1_pipeline_en.md
new file mode 100644
index 00000000000000..fab309a453c874
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_l_squadv1.1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_l_squadv1.1_pipeline pipeline RoBertaForQuestionAnswering from vuiseng9
+author: John Snow Labs
+name: roberta_qa_roberta_l_squadv1.1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_l_squadv1.1_pipeline` is a English model originally trained by vuiseng9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_l_squadv1.1_pipeline_en_5.5.0_3.0_1725451646527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_l_squadv1.1_pipeline_en_5.5.0_3.0_1725451646527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_l_squadv1.1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_l_squadv1.1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_l_squadv1.1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/vuiseng9/roberta-l-squadv1.1
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_es.md
new file mode 100644
index 00000000000000..da82b90fd2c988
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_es.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Castilian, Spanish roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju RoBertaForQuestionAnswering from jamarju
+author: John Snow Labs
+name: roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju
+date: 2024-09-04
+tags: [es, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju` is a Castilian, Spanish model originally trained by jamarju.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_es_5.5.0_3.0_1725479047523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_es_5.5.0_3.0_1725479047523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju","es") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju", "es")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/jamarju/roberta-large-bne-squad-2.0-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline_es.md
new file mode 100644
index 00000000000000..1d7a4dfd287b8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline pipeline RoBertaForQuestionAnswering from jamarju
+author: John Snow Labs
+name: roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline` is a Castilian, Spanish model originally trained by jamarju.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline_es_5.5.0_3.0_1725479125769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline_es_5.5.0_3.0_1725479125769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_large_bne_squad_2.0_spanish_jamarju_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/jamarju/roberta-large-bne-squad-2.0-es
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..3f45b051729643
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline_en_5.5.0_3.0_1725451177064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline_en_5.5.0_3.0_1725451177064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_squadv2_recipe_tokenwise_token_and_step_losses_3_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/squadv2-recipe-roberta-tokenwise-token-and-step-losses-3-epochs
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-robust_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-04-robust_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..9e003a27341f64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-robust_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English robust_sentiment_analysis BertForSequenceClassification from tabularisai
+author: John Snow Labs
+name: robust_sentiment_analysis
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robust_sentiment_analysis` is a English model originally trained by tabularisai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robust_sentiment_analysis_en_5.5.0_3.0_1725433363285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robust_sentiment_analysis_en_5.5.0_3.0_1725433363285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("robust_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("robust_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robust_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|208.1 MB|
+
+## References
+
+https://huggingface.co/tabularisai/robust-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-robust_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-robust_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..8c1f9a18d5fbb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-robust_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English robust_sentiment_analysis_pipeline pipeline BertForSequenceClassification from tabularisai
+author: John Snow Labs
+name: robust_sentiment_analysis_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robust_sentiment_analysis_pipeline` is a English model originally trained by tabularisai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robust_sentiment_analysis_pipeline_en_5.5.0_3.0_1725433433276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robust_sentiment_analysis_pipeline_en_5.5.0_3.0_1725433433276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("robust_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robust_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robust_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|208.2 MB|
+
+## References
+
+https://huggingface.co/tabularisai/robust-sentiment-analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-rulebert_v0_5_k4_it.md b/docs/_posts/ahmedlone127/2024-09-04-rulebert_v0_5_k4_it.md
new file mode 100644
index 00000000000000..11fa781d3c16a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-rulebert_v0_5_k4_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian rulebert_v0_5_k4 XlmRoBertaForSequenceClassification from ribesstefano
+author: John Snow Labs
+name: rulebert_v0_5_k4
+date: 2024-09-04
+tags: [it, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rulebert_v0_5_k4` is a Italian model originally trained by ribesstefano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rulebert_v0_5_k4_it_5.5.0_3.0_1725411416299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rulebert_v0_5_k4_it_5.5.0_3.0_1725411416299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("rulebert_v0_5_k4","it") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("rulebert_v0_5_k4", "it")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rulebert_v0_5_k4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|it|
+|Size:|870.4 MB|
+
+## References
+
+https://huggingface.co/ribesstefano/RuleBert-v0.5-k4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-rulebert_v0_5_k4_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-04-rulebert_v0_5_k4_pipeline_it.md
new file mode 100644
index 00000000000000..f7bdb03a4723a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-rulebert_v0_5_k4_pipeline_it.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Italian rulebert_v0_5_k4_pipeline pipeline XlmRoBertaForSequenceClassification from ribesstefano
+author: John Snow Labs
+name: rulebert_v0_5_k4_pipeline
+date: 2024-09-04
+tags: [it, open_source, pipeline, onnx]
+task: Text Classification
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rulebert_v0_5_k4_pipeline` is a Italian model originally trained by ribesstefano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rulebert_v0_5_k4_pipeline_it_5.5.0_3.0_1725411529398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rulebert_v0_5_k4_pipeline_it_5.5.0_3.0_1725411529398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rulebert_v0_5_k4_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rulebert_v0_5_k4_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rulebert_v0_5_k4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|870.5 MB|
+
+## References
+
+https://huggingface.co/ribesstefano/RuleBert-v0.5-k4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-runorm_tagger_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-04-runorm_tagger_pipeline_ru.md
new file mode 100644
index 00000000000000..a2ef2586be3df0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-runorm_tagger_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian runorm_tagger_pipeline pipeline BertForTokenClassification from RUNorm
+author: John Snow Labs
+name: runorm_tagger_pipeline
+date: 2024-09-04
+tags: [ru, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`runorm_tagger_pipeline` is a Russian model originally trained by RUNorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/runorm_tagger_pipeline_ru_5.5.0_3.0_1725450224885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/runorm_tagger_pipeline_ru_5.5.0_3.0_1725450224885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("runorm_tagger_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("runorm_tagger_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|runorm_tagger_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|43.9 MB|
+
+## References
+
+https://huggingface.co/RUNorm/RUNorm-tagger
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-runorm_tagger_ru.md b/docs/_posts/ahmedlone127/2024-09-04-runorm_tagger_ru.md
new file mode 100644
index 00000000000000..bf2182ab24d558
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-runorm_tagger_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian runorm_tagger BertForTokenClassification from RUNorm
+author: John Snow Labs
+name: runorm_tagger
+date: 2024-09-04
+tags: [ru, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`runorm_tagger` is a Russian model originally trained by RUNorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/runorm_tagger_ru_5.5.0_3.0_1725450222461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/runorm_tagger_ru_5.5.0_3.0_1725450222461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("runorm_tagger","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("runorm_tagger", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|runorm_tagger|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ru|
+|Size:|43.9 MB|
+
+## References
+
+https://huggingface.co/RUNorm/RUNorm-tagger
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sanbert_from_scratch_en.md b/docs/_posts/ahmedlone127/2024-09-04-sanbert_from_scratch_en.md
new file mode 100644
index 00000000000000..669e53ff0156d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sanbert_from_scratch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sanbert_from_scratch AlbertEmbeddings from surajp
+author: John Snow Labs
+name: sanbert_from_scratch
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sanbert_from_scratch` is a English model originally trained by surajp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sanbert_from_scratch_en_5.5.0_3.0_1725458234720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sanbert_from_scratch_en_5.5.0_3.0_1725458234720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("sanbert_from_scratch","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("sanbert_from_scratch","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sanbert_from_scratch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|en|
+|Size:|121.6 MB|
+
+## References
+
+https://huggingface.co/surajp/sanbert-from-scratch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sanbert_from_scratch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sanbert_from_scratch_pipeline_en.md
new file mode 100644
index 00000000000000..7e989e2ed16b17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sanbert_from_scratch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sanbert_from_scratch_pipeline pipeline AlbertEmbeddings from surajp
+author: John Snow Labs
+name: sanbert_from_scratch_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sanbert_from_scratch_pipeline` is a English model originally trained by surajp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sanbert_from_scratch_pipeline_en_5.5.0_3.0_1725458241529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sanbert_from_scratch_pipeline_en_5.5.0_3.0_1725458241529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sanbert_from_scratch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sanbert_from_scratch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sanbert_from_scratch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|121.6 MB|
+
+## References
+
+https://huggingface.co/surajp/sanbert-from-scratch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-saya_test_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-04-saya_test_sentiment_en.md
new file mode 100644
index 00000000000000..d92ff84bdf4e02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-saya_test_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English saya_test_sentiment XlmRoBertaForSequenceClassification from wnic00
+author: John Snow Labs
+name: saya_test_sentiment
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`saya_test_sentiment` is a English model originally trained by wnic00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/saya_test_sentiment_en_5.5.0_3.0_1725411105722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/saya_test_sentiment_en_5.5.0_3.0_1725411105722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("saya_test_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("saya_test_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|saya_test_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/wnic00/saya_test_sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-saya_test_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-saya_test_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..014a3d532fe8ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-saya_test_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English saya_test_sentiment_pipeline pipeline XlmRoBertaForSequenceClassification from wnic00
+author: John Snow Labs
+name: saya_test_sentiment_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`saya_test_sentiment_pipeline` is a English model originally trained by wnic00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/saya_test_sentiment_pipeline_en_5.5.0_3.0_1725411167943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/saya_test_sentiment_pipeline_en_5.5.0_3.0_1725411167943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("saya_test_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("saya_test_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|saya_test_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/wnic00/saya_test_sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-schemeclassifier3_eng_dial_en.md b/docs/_posts/ahmedlone127/2024-09-04-schemeclassifier3_eng_dial_en.md
new file mode 100644
index 00000000000000..19a9fe66113e26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-schemeclassifier3_eng_dial_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English schemeclassifier3_eng_dial RoBertaForSequenceClassification from raruidol
+author: John Snow Labs
+name: schemeclassifier3_eng_dial
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`schemeclassifier3_eng_dial` is a English model originally trained by raruidol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/schemeclassifier3_eng_dial_en_5.5.0_3.0_1725452386865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/schemeclassifier3_eng_dial_en_5.5.0_3.0_1725452386865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("schemeclassifier3_eng_dial","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("schemeclassifier3_eng_dial", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|schemeclassifier3_eng_dial|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/raruidol/SchemeClassifier3-ENG-Dial
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..b8e007dbdae11a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline pipeline DeBertaForTokenClassification from sohamtiwari3120
+author: John Snow Labs
+name: scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline` is a English model originally trained by sohamtiwari3120.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline_en_5.5.0_3.0_1725473494171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline_en_5.5.0_3.0_1725473494171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scideberta_czech_tdm_pretrained_finetuned_ner_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|560.9 MB|
+
+## References
+
+https://huggingface.co/sohamtiwari3120/scideberta-cs-tdm-pretrained-finetuned-ner-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-search_shield_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-search_shield_pipeline_en.md
new file mode 100644
index 00000000000000..e5407adc43fcba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-search_shield_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English search_shield_pipeline pipeline DistilBertForSequenceClassification from shivamkumaramehta
+author: John Snow Labs
+name: search_shield_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`search_shield_pipeline` is a English model originally trained by shivamkumaramehta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/search_shield_pipeline_en_5.5.0_3.0_1725490289196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/search_shield_pipeline_en_5.5.0_3.0_1725490289196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("search_shield_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("search_shield_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|search_shield_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/shivamkumaramehta/Search-Shield
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_afro_xlmr_base_76l_script_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-04-sent_afro_xlmr_base_76l_script_pipeline_xx.md
new file mode 100644
index 00000000000000..67644ae95de9a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_afro_xlmr_base_76l_script_pipeline_xx.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Multilingual sent_afro_xlmr_base_76l_script_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_afro_xlmr_base_76l_script_pipeline
+date: 2024-09-04
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afro_xlmr_base_76l_script_pipeline` is a Multilingual model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_76l_script_pipeline_xx_5.5.0_3.0_1725420421647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_76l_script_pipeline_xx_5.5.0_3.0_1725420421647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_afro_xlmr_base_76l_script_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_afro_xlmr_base_76l_script_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afro_xlmr_base_76l_script_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Davlan/afro-xlmr-base-76L_script
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_afro_xlmr_base_76l_script_xx.md b/docs/_posts/ahmedlone127/2024-09-04-sent_afro_xlmr_base_76l_script_xx.md
new file mode 100644
index 00000000000000..05755f4abdabc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_afro_xlmr_base_76l_script_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sent_afro_xlmr_base_76l_script XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_afro_xlmr_base_76l_script
+date: 2024-09-04
+tags: [xx, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afro_xlmr_base_76l_script` is a Multilingual model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_76l_script_xx_5.5.0_3.0_1725420358912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_76l_script_xx_5.5.0_3.0_1725420358912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afro_xlmr_base_76l_script","xx") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afro_xlmr_base_76l_script","xx") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afro_xlmr_base_76l_script|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Davlan/afro-xlmr-base-76L_script
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_arabert_c19_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_arabert_c19_ar.md
new file mode 100644
index 00000000000000..3379c25799e242
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_arabert_c19_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_arabert_c19 BertSentenceEmbeddings from moha
+author: John Snow Labs
+name: sent_arabert_c19
+date: 2024-09-04
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_arabert_c19` is a Arabic model originally trained by moha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_arabert_c19_ar_5.5.0_3.0_1725434451963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_arabert_c19_ar_5.5.0_3.0_1725434451963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_arabert_c19","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_arabert_c19","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_arabert_c19|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|504.9 MB|
+
+## References
+
+https://huggingface.co/moha/arabert_c19
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_batterybert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_batterybert_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..2e4ca37c6f1c06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_batterybert_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_batterybert_uncased_pipeline pipeline BertSentenceEmbeddings from batterydata
+author: John Snow Labs
+name: sent_batterybert_uncased_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_batterybert_uncased_pipeline` is a English model originally trained by batterydata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_batterybert_uncased_pipeline_en_5.5.0_3.0_1725454183381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_batterybert_uncased_pipeline_en_5.5.0_3.0_1725454183381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_batterybert_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_batterybert_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_batterybert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.6 MB|
+
+## References
+
+https://huggingface.co/batterydata/batterybert-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_berel_dicta_il_he.md b/docs/_posts/ahmedlone127/2024-09-04-sent_berel_dicta_il_he.md
new file mode 100644
index 00000000000000..9b3ade3dba2862
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_berel_dicta_il_he.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hebrew sent_berel_dicta_il BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_berel_dicta_il
+date: 2024-09-04
+tags: [he, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: he
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berel_dicta_il` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berel_dicta_il_he_5.5.0_3.0_1725453896847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berel_dicta_il_he_5.5.0_3.0_1725453896847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_berel_dicta_il","he") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_berel_dicta_il","he") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berel_dicta_il|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|he|
+|Size:|690.1 MB|
+
+## References
+
+https://huggingface.co/dicta-il/BEREL
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_berel_dicta_il_pipeline_he.md b/docs/_posts/ahmedlone127/2024-09-04-sent_berel_dicta_il_pipeline_he.md
new file mode 100644
index 00000000000000..e009da217a55b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_berel_dicta_il_pipeline_he.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Hebrew sent_berel_dicta_il_pipeline pipeline BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_berel_dicta_il_pipeline
+date: 2024-09-04
+tags: [he, open_source, pipeline, onnx]
+task: Embeddings
+language: he
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berel_dicta_il_pipeline` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berel_dicta_il_pipeline_he_5.5.0_3.0_1725453930843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berel_dicta_il_pipeline_he_5.5.0_3.0_1725453930843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_berel_dicta_il_pipeline", lang = "he")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_berel_dicta_il_pipeline", lang = "he")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berel_dicta_il_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|he|
+|Size:|690.7 MB|
+
+## References
+
+https://huggingface.co/dicta-il/BEREL
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_arabic_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_arabic_ar.md
new file mode 100644
index 00000000000000..c5252dbaa12145
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_arabic_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_bert_base_arabic BertSentenceEmbeddings from asafaya
+author: John Snow Labs
+name: sent_bert_base_arabic
+date: 2024-09-04
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabic` is a Arabic model originally trained by asafaya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_ar_5.5.0_3.0_1725453798860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_ar_5.5.0_3.0_1725453798860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_arabic","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_arabic","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_arabic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|412.0 MB|
+
+## References
+
+https://huggingface.co/asafaya/bert-base-arabic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_arabic_pipeline_ar.md
new file mode 100644
index 00000000000000..b065ff05a2f8e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_arabic_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_bert_base_arabic_pipeline pipeline BertSentenceEmbeddings from asafaya
+author: John Snow Labs
+name: sent_bert_base_arabic_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabic_pipeline` is a Arabic model originally trained by asafaya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_pipeline_ar_5.5.0_3.0_1725453819076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_pipeline_ar_5.5.0_3.0_1725453819076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_arabic_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_arabic_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|412.5 MB|
+
+## References
+
+https://huggingface.co/asafaya/bert-base-arabic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_bulgarian_bg.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_bulgarian_bg.md
new file mode 100644
index 00000000000000..fb03e676cd98e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_bulgarian_bg.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Bulgarian sent_bert_base_bulgarian BertSentenceEmbeddings from rmihaylov
+author: John Snow Labs
+name: sent_bert_base_bulgarian
+date: 2024-09-04
+tags: [bg, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: bg
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_bulgarian` is a Bulgarian model originally trained by rmihaylov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_bulgarian_bg_5.5.0_3.0_1725454747021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_bulgarian_bg_5.5.0_3.0_1725454747021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_bulgarian","bg") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_bulgarian","bg") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_bulgarian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|bg|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/rmihaylov/bert-base-bg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_bulgarian_pipeline_bg.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_bulgarian_pipeline_bg.md
new file mode 100644
index 00000000000000..4b5a948b295a2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_bulgarian_pipeline_bg.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Bulgarian sent_bert_base_bulgarian_pipeline pipeline BertSentenceEmbeddings from rmihaylov
+author: John Snow Labs
+name: sent_bert_base_bulgarian_pipeline
+date: 2024-09-04
+tags: [bg, open_source, pipeline, onnx]
+task: Embeddings
+language: bg
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_bulgarian_pipeline` is a Bulgarian model originally trained by rmihaylov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_bulgarian_pipeline_bg_5.5.0_3.0_1725454779297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_bulgarian_pipeline_bg_5.5.0_3.0_1725454779297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_bulgarian_pipeline", lang = "bg")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_bulgarian_pipeline", lang = "bg")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_bulgarian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bg|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/rmihaylov/bert-base-bg
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_dutch_cased_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_dutch_cased_en.md
new file mode 100644
index 00000000000000..d82fba72bcbbd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_dutch_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_dutch_cased BertSentenceEmbeddings from wietsedv
+author: John Snow Labs
+name: sent_bert_base_dutch_cased
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_dutch_cased` is a English model originally trained by wietsedv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_dutch_cased_en_5.5.0_3.0_1725415680545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_dutch_cased_en_5.5.0_3.0_1725415680545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_dutch_cased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_dutch_cased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_dutch_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/wietsedv/bert-base-dutch-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_dutch_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_dutch_cased_pipeline_en.md
new file mode 100644
index 00000000000000..4f2f10cb11a3e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_dutch_cased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_dutch_cased_pipeline pipeline BertSentenceEmbeddings from wietsedv
+author: John Snow Labs
+name: sent_bert_base_dutch_cased_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_dutch_cased_pipeline` is a English model originally trained by wietsedv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_dutch_cased_pipeline_en_5.5.0_3.0_1725415702182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_dutch_cased_pipeline_en_5.5.0_3.0_1725415702182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_dutch_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_dutch_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_dutch_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/wietsedv/bert-base-dutch-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_german_cased_dbmdz_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_german_cased_dbmdz_pipeline_de.md
new file mode 100644
index 00000000000000..5c7a0f6ad00fc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_german_cased_dbmdz_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_bert_base_german_cased_dbmdz_pipeline pipeline BertSentenceEmbeddings from dbmdz
+author: John Snow Labs
+name: sent_bert_base_german_cased_dbmdz_pipeline
+date: 2024-09-04
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_cased_dbmdz_pipeline` is a German model originally trained by dbmdz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_dbmdz_pipeline_de_5.5.0_3.0_1725415755259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_dbmdz_pipeline_de_5.5.0_3.0_1725415755259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_german_cased_dbmdz_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_german_cased_dbmdz_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_cased_dbmdz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/dbmdz/bert-base-german-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_german_dbmdz_uncased_de.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_german_dbmdz_uncased_de.md
new file mode 100644
index 00000000000000..4f53c04182949b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_german_dbmdz_uncased_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German sent_bert_base_german_dbmdz_uncased BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_base_german_dbmdz_uncased
+date: 2024-09-04
+tags: [de, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_dbmdz_uncased` is a German model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_dbmdz_uncased_de_5.5.0_3.0_1725454028364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_dbmdz_uncased_de_5.5.0_3.0_1725454028364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_dbmdz_uncased","de") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_dbmdz_uncased","de") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_dbmdz_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-german-dbmdz-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_indonesian_1_5g_id.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_indonesian_1_5g_id.md
new file mode 100644
index 00000000000000..4fe358687efae3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_indonesian_1_5g_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian sent_bert_base_indonesian_1_5g BertSentenceEmbeddings from cahya
+author: John Snow Labs
+name: sent_bert_base_indonesian_1_5g
+date: 2024-09-04
+tags: [id, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_indonesian_1_5g` is a Indonesian model originally trained by cahya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_indonesian_1_5g_id_5.5.0_3.0_1725434409368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_indonesian_1_5g_id_5.5.0_3.0_1725434409368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_indonesian_1_5g","id") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_indonesian_1_5g","id") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_indonesian_1_5g|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|id|
+|Size:|412.6 MB|
+
+## References
+
+https://huggingface.co/cahya/bert-base-indonesian-1.5G
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_indonesian_1_5g_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_indonesian_1_5g_pipeline_id.md
new file mode 100644
index 00000000000000..3286904dc742ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_indonesian_1_5g_pipeline_id.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Indonesian sent_bert_base_indonesian_1_5g_pipeline pipeline BertSentenceEmbeddings from cahya
+author: John Snow Labs
+name: sent_bert_base_indonesian_1_5g_pipeline
+date: 2024-09-04
+tags: [id, open_source, pipeline, onnx]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_indonesian_1_5g_pipeline` is a Indonesian model originally trained by cahya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_indonesian_1_5g_pipeline_id_5.5.0_3.0_1725434430011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_indonesian_1_5g_pipeline_id_5.5.0_3.0_1725434430011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_indonesian_1_5g_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_indonesian_1_5g_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_indonesian_1_5g_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|413.1 MB|
+
+## References
+
+https://huggingface.co/cahya/bert-base-indonesian-1.5G
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_cased_dccuchile_es.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_cased_dccuchile_es.md
new file mode 100644
index 00000000000000..e1c769c3d18115
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_cased_dccuchile_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish sent_bert_base_spanish_wwm_cased_dccuchile BertSentenceEmbeddings from dccuchile
+author: John Snow Labs
+name: sent_bert_base_spanish_wwm_cased_dccuchile
+date: 2024-09-04
+tags: [es, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_spanish_wwm_cased_dccuchile` is a Castilian, Spanish model originally trained by dccuchile.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_cased_dccuchile_es_5.5.0_3.0_1725454157425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_cased_dccuchile_es_5.5.0_3.0_1725454157425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_spanish_wwm_cased_dccuchile","es") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_spanish_wwm_cased_dccuchile","es") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_spanish_wwm_cased_dccuchile|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|es|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_cased_dccuchile_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_cased_dccuchile_pipeline_es.md
new file mode 100644
index 00000000000000..aa79d1c399fdc8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_cased_dccuchile_pipeline_es.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Castilian, Spanish sent_bert_base_spanish_wwm_cased_dccuchile_pipeline pipeline BertSentenceEmbeddings from dccuchile
+author: John Snow Labs
+name: sent_bert_base_spanish_wwm_cased_dccuchile_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_spanish_wwm_cased_dccuchile_pipeline` is a Castilian, Spanish model originally trained by dccuchile.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_cased_dccuchile_pipeline_es_5.5.0_3.0_1725454177885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_cased_dccuchile_pipeline_es_5.5.0_3.0_1725454177885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_spanish_wwm_cased_dccuchile_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_spanish_wwm_cased_dccuchile_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_spanish_wwm_cased_dccuchile_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_uncased_es.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_uncased_es.md
new file mode 100644
index 00000000000000..eca33e09833eb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_spanish_wwm_uncased_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish sent_bert_base_spanish_wwm_uncased BertSentenceEmbeddings from dccuchile
+author: John Snow Labs
+name: sent_bert_base_spanish_wwm_uncased
+date: 2024-09-04
+tags: [es, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_spanish_wwm_uncased` is a Castilian, Spanish model originally trained by dccuchile.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_uncased_es_5.5.0_3.0_1725415936960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_uncased_es_5.5.0_3.0_1725415936960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_spanish_wwm_uncased","es") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_spanish_wwm_uncased","es") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_spanish_wwm_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|es|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kb_pipeline_sv.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kb_pipeline_sv.md
new file mode 100644
index 00000000000000..a1180351f1284e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kb_pipeline_sv.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Swedish sent_bert_base_swedish_cased_kb_pipeline pipeline BertSentenceEmbeddings from KB
+author: John Snow Labs
+name: sent_bert_base_swedish_cased_kb_pipeline
+date: 2024-09-04
+tags: [sv, open_source, pipeline, onnx]
+task: Embeddings
+language: sv
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_swedish_cased_kb_pipeline` is a Swedish model originally trained by KB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_swedish_cased_kb_pipeline_sv_5.5.0_3.0_1725454605650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_swedish_cased_kb_pipeline_sv_5.5.0_3.0_1725454605650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_swedish_cased_kb_pipeline", lang = "sv")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_swedish_cased_kb_pipeline", lang = "sv")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_swedish_cased_kb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sv|
+|Size:|465.8 MB|
+
+## References
+
+https://huggingface.co/KB/bert-base-swedish-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kb_sv.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kb_sv.md
new file mode 100644
index 00000000000000..35ea49f6ae4fac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kb_sv.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Swedish sent_bert_base_swedish_cased_kb BertSentenceEmbeddings from KB
+author: John Snow Labs
+name: sent_bert_base_swedish_cased_kb
+date: 2024-09-04
+tags: [sv, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: sv
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_swedish_cased_kb` is a Swedish model originally trained by KB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_swedish_cased_kb_sv_5.5.0_3.0_1725454582705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_swedish_cased_kb_sv_5.5.0_3.0_1725454582705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_swedish_cased_kb","sv") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_swedish_cased_kb","sv") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_swedish_cased_kb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|sv|
+|Size:|465.2 MB|
+
+## References
+
+https://huggingface.co/KB/bert-base-swedish-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kblab_pipeline_sv.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kblab_pipeline_sv.md
new file mode 100644
index 00000000000000..6f1c76ecbd9275
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_swedish_cased_kblab_pipeline_sv.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Swedish sent_bert_base_swedish_cased_kblab_pipeline pipeline BertSentenceEmbeddings from KBLab
+author: John Snow Labs
+name: sent_bert_base_swedish_cased_kblab_pipeline
+date: 2024-09-04
+tags: [sv, open_source, pipeline, onnx]
+task: Embeddings
+language: sv
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_swedish_cased_kblab_pipeline` is a Swedish model originally trained by KBLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_swedish_cased_kblab_pipeline_sv_5.5.0_3.0_1725415511171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_swedish_cased_kblab_pipeline_sv_5.5.0_3.0_1725415511171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_swedish_cased_kblab_pipeline", lang = "sv")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_swedish_cased_kblab_pipeline", lang = "sv")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_swedish_cased_kblab_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sv|
+|Size:|465.8 MB|
+
+## References
+
+https://huggingface.co/KBLab/bert-base-swedish-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_uncased_contracts_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_uncased_contracts_en.md
new file mode 100644
index 00000000000000..b3c2ce2bcecb63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_uncased_contracts_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_contracts BertSentenceEmbeddings from nlpaueb
+author: John Snow Labs
+name: sent_bert_base_uncased_contracts
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_contracts` is a English model originally trained by nlpaueb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_contracts_en_5.5.0_3.0_1725434164523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_contracts_en_5.5.0_3.0_1725434164523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_contracts","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_contracts","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_contracts|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/nlpaueb/bert-base-uncased-contracts
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_uncased_contracts_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_uncased_contracts_pipeline_en.md
new file mode 100644
index 00000000000000..1c398a08d9b13e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_base_uncased_contracts_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_contracts_pipeline pipeline BertSentenceEmbeddings from nlpaueb
+author: John Snow Labs
+name: sent_bert_base_uncased_contracts_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_contracts_pipeline` is a English model originally trained by nlpaueb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_contracts_pipeline_en_5.5.0_3.0_1725434186064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_contracts_pipeline_en_5.5.0_3.0_1725434186064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_contracts_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_contracts_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_contracts_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.6 MB|
+
+## References
+
+https://huggingface.co/nlpaueb/bert-base-uncased-contracts
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline_pt.md
new file mode 100644
index 00000000000000..8ebb33f5e15ef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline_pt.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Portuguese sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline pipeline BertSentenceEmbeddings from stjiris
+author: John Snow Labs
+name: sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline
+date: 2024-09-04
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline` is a Portuguese model originally trained by stjiris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline_pt_5.5.0_3.0_1725454318727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline_pt_5.5.0_3.0_1725454318727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-tsdae-gpl-nli-sts-MetaKD-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline_pt.md
new file mode 100644
index 00000000000000..fe3eadc3bdead3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline_pt.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Portuguese sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline pipeline BertSentenceEmbeddings from stjiris
+author: John Snow Labs
+name: sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline
+date: 2024-09-04
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline` is a Portuguese model originally trained by stjiris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline_pt_5.5.0_3.0_1725454870670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline_pt_5.5.0_3.0_1725454870670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-tsdae-gpl-nli-sts-v0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pt.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pt.md
new file mode 100644
index 00000000000000..e07b82011a6737
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pt.md
@@ -0,0 +1,79 @@
+---
+layout: model
+title: Portuguese Legal BERT Sentence Embedding Large Cased model
+author: John Snow Labs
+name: sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0
+date: 2024-09-04
+tags: [bert, pt, embeddings, sentence, open_source, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Legal BERT Sentence Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-portuguese-cased-legal-tsdae-gpl-nli-sts-v0` is a Portuguese model originally trained by `stjiris`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pt_5.5.0_3.0_1725454812697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0_pt_5.5.0_3.0_1725454812697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0", "pt") \
+.setInputCols("sentence") \
+.setOutputCol("bert_sentence")
+
+nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, sent_embeddings ])
+  result = pipeline.fit(data).transform(data)
+```
+```scala
+val sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0", "pt")
+.setInputCols("sentence")
+.setOutputCol("bert_sentence")
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, sent_embeddings ))
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_v0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+References
+
+- https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-tsdae-gpl-nli-sts-v0
+- https://rufimelo99.github.io/SemanticSearchSystemForSTJ/
+- https://www.SBERT.net
+- https://github.com/rufimelo99
+- https://www.inesc-id.pt/projects/PR07005/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_distil_ita_legal_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_distil_ita_legal_bert_pipeline_en.md
new file mode 100644
index 00000000000000..7a9ea9b76c6472
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_distil_ita_legal_bert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_distil_ita_legal_bert_pipeline pipeline BertSentenceEmbeddings from dlicari
+author: John Snow Labs
+name: sent_bert_distil_ita_legal_bert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_distil_ita_legal_bert_pipeline` is a English model originally trained by dlicari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_distil_ita_legal_bert_pipeline_en_5.5.0_3.0_1725415797770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_distil_ita_legal_bert_pipeline_en_5.5.0_3.0_1725415797770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_distil_ita_legal_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_distil_ita_legal_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_distil_ita_legal_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|200.9 MB|
+
+## References
+
+https://huggingface.co/dlicari/distil-ita-legal-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv02_twitter_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv02_twitter_ar.md
new file mode 100644
index 00000000000000..736280c4470974
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv02_twitter_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_bert_large_arabertv02_twitter BertSentenceEmbeddings from aubmindlab
+author: John Snow Labs
+name: sent_bert_large_arabertv02_twitter
+date: 2024-09-04
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_arabertv02_twitter` is a Arabic model originally trained by aubmindlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv02_twitter_ar_5.5.0_3.0_1725433988167.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv02_twitter_ar_5.5.0_3.0_1725433988167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_arabertv02_twitter","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_arabertv02_twitter","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_arabertv02_twitter|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/aubmindlab/bert-large-arabertv02-twitter
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv2_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv2_ar.md
new file mode 100644
index 00000000000000..0a07d5c2dadc5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv2_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_bert_large_arabertv2 BertSentenceEmbeddings from aubmindlab
+author: John Snow Labs
+name: sent_bert_large_arabertv2
+date: 2024-09-04
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_arabertv2` is a Arabic model originally trained by aubmindlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv2_ar_5.5.0_3.0_1725416485723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv2_ar_5.5.0_3.0_1725416485723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_arabertv2","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_arabertv2","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_arabertv2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/aubmindlab/bert-large-arabertv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv2_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv2_pipeline_ar.md
new file mode 100644
index 00000000000000..0499744730080d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_large_arabertv2_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_bert_large_arabertv2_pipeline pipeline BertSentenceEmbeddings from aubmindlab
+author: John Snow Labs
+name: sent_bert_large_arabertv2_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_arabertv2_pipeline` is a Arabic model originally trained by aubmindlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv2_pipeline_ar_5.5.0_3.0_1725416553458.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_arabertv2_pipeline_ar_5.5.0_3.0_1725416553458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_large_arabertv2_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_large_arabertv2_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_arabertv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/aubmindlab/bert-large-arabertv2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_mini_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_mini_uncased_en.md
new file mode 100644
index 00000000000000..44f18d63852e00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_mini_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_mini_uncased BertSentenceEmbeddings from gaunernst
+author: John Snow Labs
+name: sent_bert_mini_uncased
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_mini_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_mini_uncased_en_5.5.0_3.0_1725415508581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_mini_uncased_en_5.5.0_3.0_1725415508581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_mini_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_mini_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_mini_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|41.9 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-mini-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_mini_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_mini_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..905acb09f6473a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_mini_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_mini_uncased_pipeline pipeline BertSentenceEmbeddings from gaunernst
+author: John Snow Labs
+name: sent_bert_mini_uncased_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_mini_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_mini_uncased_pipeline_en_5.5.0_3.0_1725415511187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_mini_uncased_pipeline_en_5.5.0_3.0_1725415511187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_mini_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_mini_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_mini_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.4 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-mini-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_en.md
new file mode 100644
index 00000000000000..289cf07f31b28f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0 BertSentenceEmbeddings from m-polignano-uniba
+author: John Snow Labs
+name: sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0` is a English model originally trained by m-polignano-uniba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_en_5.5.0_3.0_1725434724275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_en_5.5.0_3.0_1725434724275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|689.7 MB|
+
+## References
+
+https://huggingface.co/m-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alb3rt0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline_en.md
new file mode 100644
index 00000000000000..a5dd84e4055053
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline pipeline BertSentenceEmbeddings from m-polignano-uniba
+author: John Snow Labs
+name: sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline` is a English model originally trained by m-polignano-uniba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline_en_5.5.0_3.0_1725434758646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline_en_5.5.0_3.0_1725434758646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_uncased_l_12_h_768_a_12_italian_alb3rt0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|690.3 MB|
+
+## References
+
+https://huggingface.co/m-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alb3rt0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bertu_mt.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bertu_mt.md
new file mode 100644
index 00000000000000..6ef8ed5fed0d10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bertu_mt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Maltese sent_bertu BertSentenceEmbeddings from MLRS
+author: John Snow Labs
+name: sent_bertu
+date: 2024-09-04
+tags: [mt, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: mt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertu` is a Maltese model originally trained by MLRS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertu_mt_5.5.0_3.0_1725434422055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertu_mt_5.5.0_3.0_1725434422055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bertu","mt") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bertu","mt") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|mt|
+|Size:|468.7 MB|
+
+## References
+
+https://huggingface.co/MLRS/BERTu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bertweet_persian_farsi_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bertweet_persian_farsi_pipeline_fa.md
new file mode 100644
index 00000000000000..0d077dff8d0c67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bertweet_persian_farsi_pipeline_fa.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Persian sent_bertweet_persian_farsi_pipeline pipeline BertSentenceEmbeddings from arm-on
+author: John Snow Labs
+name: sent_bertweet_persian_farsi_pipeline
+date: 2024-09-04
+tags: [fa, open_source, pipeline, onnx]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertweet_persian_farsi_pipeline` is a Persian model originally trained by arm-on.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertweet_persian_farsi_pipeline_fa_5.5.0_3.0_1725454622167.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertweet_persian_farsi_pipeline_fa_5.5.0_3.0_1725454622167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bertweet_persian_farsi_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bertweet_persian_farsi_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertweet_persian_farsi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|406.3 MB|
+
+## References
+
+https://huggingface.co/arm-on/BERTweet-FA
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_biobert_v1_1_pubmed_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_biobert_v1_1_pubmed_en.md
new file mode 100644
index 00000000000000..4e9082ff2286d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_biobert_v1_1_pubmed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_biobert_v1_1_pubmed BertSentenceEmbeddings from monologg
+author: John Snow Labs
+name: sent_biobert_v1_1_pubmed
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobert_v1_1_pubmed` is a English model originally trained by monologg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobert_v1_1_pubmed_en_5.5.0_3.0_1725434466096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobert_v1_1_pubmed_en_5.5.0_3.0_1725434466096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_biobert_v1_1_pubmed","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_biobert_v1_1_pubmed","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobert_v1_1_pubmed|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/monologg/biobert_v1.1_pubmed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_biobert_v1_1_pubmed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_biobert_v1_1_pubmed_pipeline_en.md
new file mode 100644
index 00000000000000..1e9cfdffb2787c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_biobert_v1_1_pubmed_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_biobert_v1_1_pubmed_pipeline pipeline BertSentenceEmbeddings from monologg
+author: John Snow Labs
+name: sent_biobert_v1_1_pubmed_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobert_v1_1_pubmed_pipeline` is a English model originally trained by monologg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobert_v1_1_pubmed_pipeline_en_5.5.0_3.0_1725434487199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobert_v1_1_pubmed_pipeline_en_5.5.0_3.0_1725434487199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_biobert_v1_1_pubmed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_biobert_v1_1_pubmed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobert_v1_1_pubmed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/monologg/biobert_v1.1_pubmed
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_checkpoint_14200_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_checkpoint_14200_en.md
new file mode 100644
index 00000000000000..0a5bb78c946783
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_checkpoint_14200_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_checkpoint_14200 XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_checkpoint_14200
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_14200` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_14200_en_5.5.0_3.0_1725419824241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_14200_en_5.5.0_3.0_1725419824241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_checkpoint_14200","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_checkpoint_14200","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_checkpoint_14200|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-14200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_checkpoint_14200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_checkpoint_14200_pipeline_en.md
new file mode 100644
index 00000000000000..1326d8e02e26fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_checkpoint_14200_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_checkpoint_14200_pipeline pipeline XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_checkpoint_14200_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_14200_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_14200_pipeline_en_5.5.0_3.0_1725419879976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_14200_pipeline_en_5.5.0_3.0_1725419879976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_checkpoint_14200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_checkpoint_14200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_checkpoint_14200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-14200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_darijabert_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_darijabert_pipeline_ar.md
new file mode 100644
index 00000000000000..a04f9b103d3492
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_darijabert_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_darijabert_pipeline pipeline BertSentenceEmbeddings from SI2M-Lab
+author: John Snow Labs
+name: sent_darijabert_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_darijabert_pipeline` is a Arabic model originally trained by SI2M-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_darijabert_pipeline_ar_5.5.0_3.0_1725415825588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_darijabert_pipeline_ar_5.5.0_3.0_1725415825588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_darijabert_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_darijabert_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_darijabert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|552.0 MB|
+
+## References
+
+https://huggingface.co/SI2M-Lab/DarijaBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_dictabert_he.md b/docs/_posts/ahmedlone127/2024-09-04-sent_dictabert_he.md
new file mode 100644
index 00000000000000..78308dc5b2534d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_dictabert_he.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hebrew sent_dictabert BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_dictabert
+date: 2024-09-04
+tags: [he, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: he
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dictabert` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dictabert_he_5.5.0_3.0_1725416153876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dictabert_he_5.5.0_3.0_1725416153876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dictabert","he") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dictabert","he") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dictabert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|he|
+|Size:|440.2 MB|
+
+## References
+
+https://huggingface.co/dicta-il/dictabert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_dictabert_pipeline_he.md b/docs/_posts/ahmedlone127/2024-09-04-sent_dictabert_pipeline_he.md
new file mode 100644
index 00000000000000..bc0e3ae4c53bb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_dictabert_pipeline_he.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Hebrew sent_dictabert_pipeline pipeline BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_dictabert_pipeline
+date: 2024-09-04
+tags: [he, open_source, pipeline, onnx]
+task: Embeddings
+language: he
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dictabert_pipeline` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dictabert_pipeline_he_5.5.0_3.0_1725416286071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dictabert_pipeline_he_5.5.0_3.0_1725416286071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dictabert_pipeline", lang = "he")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dictabert_pipeline", lang = "he")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dictabert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|he|
+|Size:|440.7 MB|
+
+## References
+
+https://huggingface.co/dicta-il/dictabert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_disorbert_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_disorbert_en.md
new file mode 100644
index 00000000000000..ed9a4cb8f2f572
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_disorbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_disorbert BertSentenceEmbeddings from citiusLTL
+author: John Snow Labs
+name: sent_disorbert
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_disorbert` is a English model originally trained by citiusLTL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_disorbert_en_5.5.0_3.0_1725433954653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_disorbert_en_5.5.0_3.0_1725433954653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_disorbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_disorbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_disorbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/citiusLTL/DisorBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_disorbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_disorbert_pipeline_en.md
new file mode 100644
index 00000000000000..f2d0b8b103db9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_disorbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_disorbert_pipeline pipeline BertSentenceEmbeddings from citiusLTL
+author: John Snow Labs
+name: sent_disorbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_disorbert_pipeline` is a English model originally trained by citiusLTL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_disorbert_pipeline_en_5.5.0_3.0_1725433975029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_disorbert_pipeline_en_5.5.0_3.0_1725433975029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_disorbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_disorbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_disorbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.6 MB|
+
+## References
+
+https://huggingface.co/citiusLTL/DisorBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_dziribert_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_dziribert_ar.md
new file mode 100644
index 00000000000000..2223c3e33fd399
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_dziribert_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_dziribert BertSentenceEmbeddings from alger-ia
+author: John Snow Labs
+name: sent_dziribert
+date: 2024-09-04
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dziribert` is a Arabic model originally trained by alger-ia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dziribert_ar_5.5.0_3.0_1725454501276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dziribert_ar_5.5.0_3.0_1725454501276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dziribert","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dziribert","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dziribert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|462.5 MB|
+
+## References
+
+https://huggingface.co/alger-ia/dziribert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_dziribert_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-sent_dziribert_pipeline_ar.md
new file mode 100644
index 00000000000000..c35e398599e1e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_dziribert_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_dziribert_pipeline pipeline BertSentenceEmbeddings from alger-ia
+author: John Snow Labs
+name: sent_dziribert_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dziribert_pipeline` is a Arabic model originally trained by alger-ia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dziribert_pipeline_ar_5.5.0_3.0_1725454524052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dziribert_pipeline_ar_5.5.0_3.0_1725454524052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dziribert_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dziribert_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dziribert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|463.1 MB|
+
+## References
+
+https://huggingface.co/alger-ia/dziribert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_entitycs_39_pep_malay_mlm_xlmr_base_xx.md b/docs/_posts/ahmedlone127/2024-09-04-sent_entitycs_39_pep_malay_mlm_xlmr_base_xx.md
new file mode 100644
index 00000000000000..9088aeb5e9a578
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_entitycs_39_pep_malay_mlm_xlmr_base_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sent_entitycs_39_pep_malay_mlm_xlmr_base XlmRoBertaSentenceEmbeddings from huawei-noah
+author: John Snow Labs
+name: sent_entitycs_39_pep_malay_mlm_xlmr_base
+date: 2024-09-04
+tags: [xx, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_entitycs_39_pep_malay_mlm_xlmr_base` is a Multilingual model originally trained by huawei-noah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_entitycs_39_pep_malay_mlm_xlmr_base_xx_5.5.0_3.0_1725420529592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_entitycs_39_pep_malay_mlm_xlmr_base_xx_5.5.0_3.0_1725420529592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_entitycs_39_pep_malay_mlm_xlmr_base","xx") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_entitycs_39_pep_malay_mlm_xlmr_base","xx") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_entitycs_39_pep_malay_mlm_xlmr_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|944.5 MB|
+
+## References
+
+https://huggingface.co/huawei-noah/EntityCS-39-PEP_MS_MLM-xlmr-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_entitycs_39_wep_xlmr_base_xx.md b/docs/_posts/ahmedlone127/2024-09-04-sent_entitycs_39_wep_xlmr_base_xx.md
new file mode 100644
index 00000000000000..010fb3569f7464
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_entitycs_39_wep_xlmr_base_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sent_entitycs_39_wep_xlmr_base XlmRoBertaSentenceEmbeddings from huawei-noah
+author: John Snow Labs
+name: sent_entitycs_39_wep_xlmr_base
+date: 2024-09-04
+tags: [xx, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_entitycs_39_wep_xlmr_base` is a Multilingual model originally trained by huawei-noah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_entitycs_39_wep_xlmr_base_xx_5.5.0_3.0_1725419208921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_entitycs_39_wep_xlmr_base_xx_5.5.0_3.0_1725419208921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_entitycs_39_wep_xlmr_base","xx") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_entitycs_39_wep_xlmr_base","xx") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_entitycs_39_wep_xlmr_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|944.9 MB|
+
+## References
+
+https://huggingface.co/huawei-noah/EntityCS-39-WEP-xlmr-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_estbert_et.md b/docs/_posts/ahmedlone127/2024-09-04-sent_estbert_et.md
new file mode 100644
index 00000000000000..d26952aef57273
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_estbert_et.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Estonian sent_estbert BertSentenceEmbeddings from tartuNLP
+author: John Snow Labs
+name: sent_estbert
+date: 2024-09-04
+tags: [et, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: et
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_estbert` is a Estonian model originally trained by tartuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_estbert_et_5.5.0_3.0_1725454417118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_estbert_et_5.5.0_3.0_1725454417118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_estbert","et") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_estbert","et") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_estbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|et|
+|Size:|463.4 MB|
+
+## References
+
+https://huggingface.co/tartuNLP/EstBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_estbert_pipeline_et.md b/docs/_posts/ahmedlone127/2024-09-04-sent_estbert_pipeline_et.md
new file mode 100644
index 00000000000000..2c3e3e42161d63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_estbert_pipeline_et.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Estonian sent_estbert_pipeline pipeline BertSentenceEmbeddings from tartuNLP
+author: John Snow Labs
+name: sent_estbert_pipeline
+date: 2024-09-04
+tags: [et, open_source, pipeline, onnx]
+task: Embeddings
+language: et
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_estbert_pipeline` is a Estonian model originally trained by tartuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_estbert_pipeline_et_5.5.0_3.0_1725454439383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_estbert_pipeline_et_5.5.0_3.0_1725454439383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_estbert_pipeline", lang = "et")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_estbert_pipeline", lang = "et")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_estbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|et|
+|Size:|464.0 MB|
+
+## References
+
+https://huggingface.co/tartuNLP/EstBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_fabert_fa.md b/docs/_posts/ahmedlone127/2024-09-04-sent_fabert_fa.md
new file mode 100644
index 00000000000000..6190d7d9bb2d2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_fabert_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian sent_fabert BertSentenceEmbeddings from sbunlp
+author: John Snow Labs
+name: sent_fabert
+date: 2024-09-04
+tags: [fa, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fabert` is a Persian model originally trained by sbunlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_fabert_fa_5.5.0_3.0_1725415640249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fabert_fa_5.5.0_3.0_1725415640249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_fabert","fa") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_fabert","fa") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fabert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|fa|
+|Size:|464.5 MB|
+
+## References
+
+https://huggingface.co/sbunlp/fabert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_fabert_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-04-sent_fabert_pipeline_fa.md
new file mode 100644
index 00000000000000..6df3705d8a2fc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_fabert_pipeline_fa.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Persian sent_fabert_pipeline pipeline BertSentenceEmbeddings from sbunlp
+author: John Snow Labs
+name: sent_fabert_pipeline
+date: 2024-09-04
+tags: [fa, open_source, pipeline, onnx]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fabert_pipeline` is a Persian model originally trained by sbunlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_fabert_pipeline_fa_5.5.0_3.0_1725415665592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fabert_pipeline_fa_5.5.0_3.0_1725415665592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_fabert_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_fabert_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fabert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|465.1 MB|
+
+## References
+
+https://huggingface.co/sbunlp/fabert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_finbert_pretrain_yiyanghkust_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_finbert_pretrain_yiyanghkust_pipeline_en.md
new file mode 100644
index 00000000000000..18242efee2b386
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_finbert_pretrain_yiyanghkust_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_finbert_pretrain_yiyanghkust_pipeline pipeline BertSentenceEmbeddings from yiyanghkust
+author: John Snow Labs
+name: sent_finbert_pretrain_yiyanghkust_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_finbert_pretrain_yiyanghkust_pipeline` is a English model originally trained by yiyanghkust.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_finbert_pretrain_yiyanghkust_pipeline_en_5.5.0_3.0_1725454066581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_finbert_pretrain_yiyanghkust_pipeline_en_5.5.0_3.0_1725454066581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_finbert_pretrain_yiyanghkust_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_finbert_pretrain_yiyanghkust_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_finbert_pretrain_yiyanghkust_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/yiyanghkust/finbert-pretrain
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_greek_media_bert_base_uncased_el.md b/docs/_posts/ahmedlone127/2024-09-04-sent_greek_media_bert_base_uncased_el.md
new file mode 100644
index 00000000000000..5855aa21cac263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_greek_media_bert_base_uncased_el.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Modern Greek (1453-) sent_greek_media_bert_base_uncased BertSentenceEmbeddings from dimitriz
+author: John Snow Labs
+name: sent_greek_media_bert_base_uncased
+date: 2024-09-04
+tags: [el, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: el
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_greek_media_bert_base_uncased` is a Modern Greek (1453-) model originally trained by dimitriz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_greek_media_bert_base_uncased_el_5.5.0_3.0_1725434004878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_greek_media_bert_base_uncased_el_5.5.0_3.0_1725434004878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_greek_media_bert_base_uncased","el") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_greek_media_bert_base_uncased","el") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_greek_media_bert_base_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|el|
+|Size:|420.8 MB|
+
+## References
+
+https://huggingface.co/dimitriz/greek-media-bert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_greek_media_bert_base_uncased_pipeline_el.md b/docs/_posts/ahmedlone127/2024-09-04-sent_greek_media_bert_base_uncased_pipeline_el.md
new file mode 100644
index 00000000000000..c63d26acbe2c9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_greek_media_bert_base_uncased_pipeline_el.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Modern Greek (1453-) sent_greek_media_bert_base_uncased_pipeline pipeline BertSentenceEmbeddings from dimitriz
+author: John Snow Labs
+name: sent_greek_media_bert_base_uncased_pipeline
+date: 2024-09-04
+tags: [el, open_source, pipeline, onnx]
+task: Embeddings
+language: el
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_greek_media_bert_base_uncased_pipeline` is a Modern Greek (1453-) model originally trained by dimitriz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_greek_media_bert_base_uncased_pipeline_el_5.5.0_3.0_1725434027109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_greek_media_bert_base_uncased_pipeline_el_5.5.0_3.0_1725434027109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_greek_media_bert_base_uncased_pipeline", lang = "el")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_greek_media_bert_base_uncased_pipeline", lang = "el")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_greek_media_bert_base_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|el|
+|Size:|421.4 MB|
+
+## References
+
+https://huggingface.co/dimitriz/greek-media-bert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_gujarati_xlm_r_base_gu.md b/docs/_posts/ahmedlone127/2024-09-04-sent_gujarati_xlm_r_base_gu.md
new file mode 100644
index 00000000000000..b21ac23323d680
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_gujarati_xlm_r_base_gu.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Gujarati sent_gujarati_xlm_r_base XlmRoBertaSentenceEmbeddings from ashwani-tanwar
+author: John Snow Labs
+name: sent_gujarati_xlm_r_base
+date: 2024-09-04
+tags: [gu, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: gu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gujarati_xlm_r_base` is a Gujarati model originally trained by ashwani-tanwar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gujarati_xlm_r_base_gu_5.5.0_3.0_1725419786115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gujarati_xlm_r_base_gu_5.5.0_3.0_1725419786115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_gujarati_xlm_r_base","gu") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_gujarati_xlm_r_base","gu") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gujarati_xlm_r_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|gu|
+|Size:|653.1 MB|
+
+## References
+
+https://huggingface.co/ashwani-tanwar/Gujarati-XLM-R-Base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_gujarati_xlm_r_base_pipeline_gu.md b/docs/_posts/ahmedlone127/2024-09-04-sent_gujarati_xlm_r_base_pipeline_gu.md
new file mode 100644
index 00000000000000..f9eae1790109de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_gujarati_xlm_r_base_pipeline_gu.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Gujarati sent_gujarati_xlm_r_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from ashwani-tanwar
+author: John Snow Labs
+name: sent_gujarati_xlm_r_base_pipeline
+date: 2024-09-04
+tags: [gu, open_source, pipeline, onnx]
+task: Embeddings
+language: gu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gujarati_xlm_r_base_pipeline` is a Gujarati model originally trained by ashwani-tanwar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gujarati_xlm_r_base_pipeline_gu_5.5.0_3.0_1725419984495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gujarati_xlm_r_base_pipeline_gu_5.5.0_3.0_1725419984495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_gujarati_xlm_r_base_pipeline", lang = "gu")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_gujarati_xlm_r_base_pipeline", lang = "gu")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gujarati_xlm_r_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|gu|
+|Size:|653.7 MB|
+
+## References
+
+https://huggingface.co/ashwani-tanwar/Gujarati-XLM-R-Base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_hindi_roberta_hi.md b/docs/_posts/ahmedlone127/2024-09-04-sent_hindi_roberta_hi.md
new file mode 100644
index 00000000000000..7a67aa6a12720a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_hindi_roberta_hi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hindi sent_hindi_roberta XlmRoBertaSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hindi_roberta
+date: 2024-09-04
+tags: [hi, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hindi_roberta` is a Hindi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hindi_roberta_hi_5.5.0_3.0_1725419364829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hindi_roberta_hi_5.5.0_3.0_1725419364829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_hindi_roberta","hi") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_hindi_roberta","hi") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hindi_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|hi|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hindi-roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_hindi_roberta_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-04-sent_hindi_roberta_pipeline_hi.md
new file mode 100644
index 00000000000000..d4c9c50cc86b40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_hindi_roberta_pipeline_hi.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Hindi sent_hindi_roberta_pipeline pipeline XlmRoBertaSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hindi_roberta_pipeline
+date: 2024-09-04
+tags: [hi, open_source, pipeline, onnx]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hindi_roberta_pipeline` is a Hindi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hindi_roberta_pipeline_hi_5.5.0_3.0_1725419420039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hindi_roberta_pipeline_hi_5.5.0_3.0_1725419420039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_hindi_roberta_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_hindi_roberta_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hindi_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hindi-roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_inlegalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_inlegalbert_pipeline_en.md
new file mode 100644
index 00000000000000..aa4fad96273d59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_inlegalbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_inlegalbert_pipeline pipeline BertSentenceEmbeddings from law-ai
+author: John Snow Labs
+name: sent_inlegalbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_inlegalbert_pipeline` is a English model originally trained by law-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_inlegalbert_pipeline_en_5.5.0_3.0_1725453928451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_inlegalbert_pipeline_en_5.5.0_3.0_1725453928451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_inlegalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_inlegalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_inlegalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/law-ai/InLegalBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_italian_legal_bert_it.md b/docs/_posts/ahmedlone127/2024-09-04-sent_italian_legal_bert_it.md
new file mode 100644
index 00000000000000..c86e71c511b058
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_italian_legal_bert_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian sent_italian_legal_bert BertSentenceEmbeddings from dlicari
+author: John Snow Labs
+name: sent_italian_legal_bert
+date: 2024-09-04
+tags: [it, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_italian_legal_bert` is a Italian model originally trained by dlicari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_italian_legal_bert_it_5.5.0_3.0_1725415606294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_italian_legal_bert_it_5.5.0_3.0_1725415606294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_italian_legal_bert","it") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_italian_legal_bert","it") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_italian_legal_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|it|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/dlicari/Italian-Legal-BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_italian_legal_bert_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-04-sent_italian_legal_bert_pipeline_it.md
new file mode 100644
index 00000000000000..539fb3ecba39aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_italian_legal_bert_pipeline_it.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Italian sent_italian_legal_bert_pipeline pipeline BertSentenceEmbeddings from dlicari
+author: John Snow Labs
+name: sent_italian_legal_bert_pipeline
+date: 2024-09-04
+tags: [it, open_source, pipeline, onnx]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_italian_legal_bert_pipeline` is a Italian model originally trained by dlicari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_italian_legal_bert_pipeline_it_5.5.0_3.0_1725415629446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_italian_legal_bert_pipeline_it_5.5.0_3.0_1725415629446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_italian_legal_bert_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_italian_legal_bert_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_italian_legal_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/dlicari/Italian-Legal-BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_jmedroberta_base_sentencepiece_ja.md b/docs/_posts/ahmedlone127/2024-09-04-sent_jmedroberta_base_sentencepiece_ja.md
new file mode 100644
index 00000000000000..d967a7fcffb23c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_jmedroberta_base_sentencepiece_ja.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Japanese sent_jmedroberta_base_sentencepiece BertSentenceEmbeddings from alabnii
+author: John Snow Labs
+name: sent_jmedroberta_base_sentencepiece
+date: 2024-09-04
+tags: [ja, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_jmedroberta_base_sentencepiece` is a Japanese model originally trained by alabnii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_jmedroberta_base_sentencepiece_ja_5.5.0_3.0_1725416080185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_jmedroberta_base_sentencepiece_ja_5.5.0_3.0_1725416080185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_jmedroberta_base_sentencepiece","ja") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_jmedroberta_base_sentencepiece","ja") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_jmedroberta_base_sentencepiece|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ja|
+|Size:|406.1 MB|
+
+## References
+
+https://huggingface.co/alabnii/jmedroberta-base-sentencepiece
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_kbioxlm_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_kbioxlm_en.md
new file mode 100644
index 00000000000000..102777484d7046
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_kbioxlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_kbioxlm XlmRoBertaSentenceEmbeddings from ngwlh
+author: John Snow Labs
+name: sent_kbioxlm
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kbioxlm` is a English model originally trained by ngwlh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kbioxlm_en_5.5.0_3.0_1725419621207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kbioxlm_en_5.5.0_3.0_1725419621207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_kbioxlm","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_kbioxlm","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kbioxlm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|658.6 MB|
+
+## References
+
+https://huggingface.co/ngwlh/KBioXLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_kbioxlm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_kbioxlm_pipeline_en.md
new file mode 100644
index 00000000000000..03b22662d48c0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_kbioxlm_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_kbioxlm_pipeline pipeline XlmRoBertaSentenceEmbeddings from ngwlh
+author: John Snow Labs
+name: sent_kbioxlm_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kbioxlm_pipeline` is a English model originally trained by ngwlh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kbioxlm_pipeline_en_5.5.0_3.0_1725419815581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kbioxlm_pipeline_en_5.5.0_3.0_1725419815581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_kbioxlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_kbioxlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kbioxlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|659.1 MB|
+
+## References
+
+https://huggingface.co/ngwlh/KBioXLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_legal_bert_base_uncased_nlpaueb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_legal_bert_base_uncased_nlpaueb_pipeline_en.md
new file mode 100644
index 00000000000000..282c5f4545d68d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_legal_bert_base_uncased_nlpaueb_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_legal_bert_base_uncased_nlpaueb_pipeline pipeline BertSentenceEmbeddings from nlpaueb
+author: John Snow Labs
+name: sent_legal_bert_base_uncased_nlpaueb_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_bert_base_uncased_nlpaueb_pipeline` is a English model originally trained by nlpaueb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_bert_base_uncased_nlpaueb_pipeline_en_5.5.0_3.0_1725453997802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_bert_base_uncased_nlpaueb_pipeline_en_5.5.0_3.0_1725453997802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_legal_bert_base_uncased_nlpaueb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_legal_bert_base_uncased_nlpaueb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_bert_base_uncased_nlpaueb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/nlpaueb/legal-bert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_legalbert_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_legalbert_en.md
new file mode 100644
index 00000000000000..4e24a4eea4362e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_legalbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_legalbert BertSentenceEmbeddings from casehold
+author: John Snow Labs
+name: sent_legalbert
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legalbert` is a English model originally trained by casehold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legalbert_en_5.5.0_3.0_1725454381722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legalbert_en_5.5.0_3.0_1725454381722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_legalbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_legalbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legalbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/casehold/legalbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_legalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_legalbert_pipeline_en.md
new file mode 100644
index 00000000000000..1b533ede95010f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_legalbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_legalbert_pipeline pipeline BertSentenceEmbeddings from casehold
+author: John Snow Labs
+name: sent_legalbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legalbert_pipeline` is a English model originally trained by casehold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legalbert_pipeline_en_5.5.0_3.0_1725454402596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legalbert_pipeline_en_5.5.0_3.0_1725454402596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_legalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_legalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/casehold/legalbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_matscibert_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_matscibert_en.md
new file mode 100644
index 00000000000000..f0521f44573737
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_matscibert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_matscibert BertSentenceEmbeddings from m3rg-iitd
+author: John Snow Labs
+name: sent_matscibert
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_matscibert` is a English model originally trained by m3rg-iitd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_matscibert_en_5.5.0_3.0_1725416337905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_matscibert_en_5.5.0_3.0_1725416337905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_matscibert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_matscibert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_matscibert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/m3rg-iitd/matscibert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_matscibert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_matscibert_pipeline_en.md
new file mode 100644
index 00000000000000..79bfeda4b046a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_matscibert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_matscibert_pipeline pipeline BertSentenceEmbeddings from m3rg-iitd
+author: John Snow Labs
+name: sent_matscibert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_matscibert_pipeline` is a English model originally trained by m3rg-iitd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_matscibert_pipeline_en_5.5.0_3.0_1725416358754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_matscibert_pipeline_en_5.5.0_3.0_1725416358754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_matscibert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_matscibert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_matscibert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.5 MB|
+
+## References
+
+https://huggingface.co/m3rg-iitd/matscibert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_medbert_512_norwegian_duplicates_de.md b/docs/_posts/ahmedlone127/2024-09-04-sent_medbert_512_norwegian_duplicates_de.md
new file mode 100644
index 00000000000000..ccc1e349ddcfb3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_medbert_512_norwegian_duplicates_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German sent_medbert_512_norwegian_duplicates BertSentenceEmbeddings from GerMedBERT
+author: John Snow Labs
+name: sent_medbert_512_norwegian_duplicates
+date: 2024-09-04
+tags: [de, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_medbert_512_norwegian_duplicates` is a German model originally trained by GerMedBERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_medbert_512_norwegian_duplicates_de_5.5.0_3.0_1725434505264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_medbert_512_norwegian_duplicates_de_5.5.0_3.0_1725434505264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_medbert_512_norwegian_duplicates","de") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_medbert_512_norwegian_duplicates","de") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_medbert_512_norwegian_duplicates|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/GerMedBERT/medbert-512-no-duplicates
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_medbert_512_norwegian_duplicates_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-04-sent_medbert_512_norwegian_duplicates_pipeline_de.md
new file mode 100644
index 00000000000000..5520ae8cf73ffa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_medbert_512_norwegian_duplicates_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_medbert_512_norwegian_duplicates_pipeline pipeline BertSentenceEmbeddings from GerMedBERT
+author: John Snow Labs
+name: sent_medbert_512_norwegian_duplicates_pipeline
+date: 2024-09-04
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_medbert_512_norwegian_duplicates_pipeline` is a German model originally trained by GerMedBERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_medbert_512_norwegian_duplicates_pipeline_de_5.5.0_3.0_1725434525609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_medbert_512_norwegian_duplicates_pipeline_de_5.5.0_3.0_1725434525609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_medbert_512_norwegian_duplicates_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_medbert_512_norwegian_duplicates_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_medbert_512_norwegian_duplicates_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/GerMedBERT/medbert-512-no-duplicates
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_naija_xlm_twitter_base_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_naija_xlm_twitter_base_en.md
new file mode 100644
index 00000000000000..ff0d8ed3d978ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_naija_xlm_twitter_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_naija_xlm_twitter_base XlmRoBertaSentenceEmbeddings from worldbank
+author: John Snow Labs
+name: sent_naija_xlm_twitter_base
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_naija_xlm_twitter_base` is a English model originally trained by worldbank.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_naija_xlm_twitter_base_en_5.5.0_3.0_1725420157552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_naija_xlm_twitter_base_en_5.5.0_3.0_1725420157552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_naija_xlm_twitter_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_naija_xlm_twitter_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_naija_xlm_twitter_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/worldbank/naija-xlm-twitter-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_naija_xlm_twitter_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_naija_xlm_twitter_base_pipeline_en.md
new file mode 100644
index 00000000000000..14fa0d64ea6058
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_naija_xlm_twitter_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_naija_xlm_twitter_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from worldbank
+author: John Snow Labs
+name: sent_naija_xlm_twitter_base_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_naija_xlm_twitter_base_pipeline` is a English model originally trained by worldbank.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_naija_xlm_twitter_base_pipeline_en_5.5.0_3.0_1725420211385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_naija_xlm_twitter_base_pipeline_en_5.5.0_3.0_1725420211385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_naija_xlm_twitter_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_naija_xlm_twitter_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_naija_xlm_twitter_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/worldbank/naija-xlm-twitter-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_nepalibert_ne.md b/docs/_posts/ahmedlone127/2024-09-04-sent_nepalibert_ne.md
new file mode 100644
index 00000000000000..346d887904903a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_nepalibert_ne.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Nepali (macrolanguage) sent_nepalibert BertSentenceEmbeddings from Shushant
+author: John Snow Labs
+name: sent_nepalibert
+date: 2024-09-04
+tags: [ne, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ne
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_nepalibert` is a Nepali (macrolanguage) model originally trained by Shushant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_nepalibert_ne_5.5.0_3.0_1725415792381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_nepalibert_ne_5.5.0_3.0_1725415792381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_nepalibert","ne") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_nepalibert","ne") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_nepalibert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ne|
+|Size:|408.5 MB|
+
+## References
+
+https://huggingface.co/Shushant/nepaliBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_nepalibert_pipeline_ne.md b/docs/_posts/ahmedlone127/2024-09-04-sent_nepalibert_pipeline_ne.md
new file mode 100644
index 00000000000000..bae85b400f9c61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_nepalibert_pipeline_ne.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Nepali (macrolanguage) sent_nepalibert_pipeline pipeline BertSentenceEmbeddings from Shushant
+author: John Snow Labs
+name: sent_nepalibert_pipeline
+date: 2024-09-04
+tags: [ne, open_source, pipeline, onnx]
+task: Embeddings
+language: ne
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_nepalibert_pipeline` is a Nepali (macrolanguage) model originally trained by Shushant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_nepalibert_pipeline_ne_5.5.0_3.0_1725415820116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_nepalibert_pipeline_ne_5.5.0_3.0_1725415820116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_nepalibert_pipeline", lang = "ne")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_nepalibert_pipeline", lang = "ne")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_nepalibert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ne|
+|Size:|409.1 MB|
+
+## References
+
+https://huggingface.co/Shushant/nepaliBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_netbert_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_netbert_en.md
new file mode 100644
index 00000000000000..37d2226011b5de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_netbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_netbert BertSentenceEmbeddings from antoinelouis
+author: John Snow Labs
+name: sent_netbert
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_netbert` is a English model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_netbert_en_5.5.0_3.0_1725454743432.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_netbert_en_5.5.0_3.0_1725454743432.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_netbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_netbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_netbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/antoinelouis/netbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_netbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_netbert_pipeline_en.md
new file mode 100644
index 00000000000000..1454a61072bbb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_netbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_netbert_pipeline pipeline BertSentenceEmbeddings from antoinelouis
+author: John Snow Labs
+name: sent_netbert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_netbert_pipeline` is a English model originally trained by antoinelouis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_netbert_pipeline_en_5.5.0_3.0_1725454763420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_netbert_pipeline_en_5.5.0_3.0_1725454763420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_netbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_netbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_netbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/antoinelouis/netbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_norbert2_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-04-sent_norbert2_pipeline_no.md
new file mode 100644
index 00000000000000..8762abc3833295
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_norbert2_pipeline_no.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Norwegian sent_norbert2_pipeline pipeline BertSentenceEmbeddings from ltg
+author: John Snow Labs
+name: sent_norbert2_pipeline
+date: 2024-09-04
+tags: ["no", open_source, pipeline, onnx]
+task: Embeddings
+language: "no"
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norbert2_pipeline` is a Norwegian model originally trained by ltg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_norbert2_pipeline_no_5.5.0_3.0_1725453824364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norbert2_pipeline_no_5.5.0_3.0_1725453824364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_norbert2_pipeline", lang = "no")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_norbert2_pipeline", lang = "no")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_norbert2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|no|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/ltg/norbert2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_regex_gb_2021_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_regex_gb_2021_en.md
new file mode 100644
index 00000000000000..1e32010a398483
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_regex_gb_2021_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_regex_gb_2021 BertSentenceEmbeddings from mossaic-candle
+author: John Snow Labs
+name: sent_regex_gb_2021
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_regex_gb_2021` is a English model originally trained by mossaic-candle.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_regex_gb_2021_en_5.5.0_3.0_1725454565590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_regex_gb_2021_en_5.5.0_3.0_1725454565590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_regex_gb_2021","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_regex_gb_2021","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_regex_gb_2021|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|258.7 MB|
+
+## References
+
+https://huggingface.co/mossaic-candle/regex-gb-2021
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_regex_gb_2021_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_regex_gb_2021_pipeline_en.md
new file mode 100644
index 00000000000000..e33ac5372ac23b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_regex_gb_2021_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_regex_gb_2021_pipeline pipeline BertSentenceEmbeddings from mossaic-candle
+author: John Snow Labs
+name: sent_regex_gb_2021_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_regex_gb_2021_pipeline` is a English model originally trained by mossaic-candle.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_regex_gb_2021_pipeline_en_5.5.0_3.0_1725454640837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_regex_gb_2021_pipeline_en_5.5.0_3.0_1725454640837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_regex_gb_2021_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_regex_gb_2021_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_regex_gb_2021_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|259.3 MB|
+
+## References
+
+https://huggingface.co/mossaic-candle/regex-gb-2021
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_relu_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_relu_bert_base_uncased_en.md
new file mode 100644
index 00000000000000..a4bdf992c8b3ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_relu_bert_base_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_relu_bert_base_uncased BertSentenceEmbeddings from mpiorczynski
+author: John Snow Labs
+name: sent_relu_bert_base_uncased
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_relu_bert_base_uncased` is a English model originally trained by mpiorczynski.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_relu_bert_base_uncased_en_5.5.0_3.0_1725416065417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_relu_bert_base_uncased_en_5.5.0_3.0_1725416065417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_relu_bert_base_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_relu_bert_base_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_relu_bert_base_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/mpiorczynski/relu-bert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_relu_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_relu_bert_base_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..43e1f200e2b14f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_relu_bert_base_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_relu_bert_base_uncased_pipeline pipeline BertSentenceEmbeddings from mpiorczynski
+author: John Snow Labs
+name: sent_relu_bert_base_uncased_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_relu_bert_base_uncased_pipeline` is a English model originally trained by mpiorczynski.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_relu_bert_base_uncased_pipeline_en_5.5.0_3.0_1725416086877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_relu_bert_base_uncased_pipeline_en_5.5.0_3.0_1725416086877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_relu_bert_base_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_relu_bert_base_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_relu_bert_base_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/mpiorczynski/relu-bert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_sikubert_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-04-sent_sikubert_pipeline_zh.md
new file mode 100644
index 00000000000000..763ff5eccdaad8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_sikubert_pipeline_zh.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Chinese sent_sikubert_pipeline pipeline BertSentenceEmbeddings from SIKU-BERT
+author: John Snow Labs
+name: sent_sikubert_pipeline
+date: 2024-09-04
+tags: [zh, open_source, pipeline, onnx]
+task: Embeddings
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_sikubert_pipeline` is a Chinese model originally trained by SIKU-BERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_sikubert_pipeline_zh_5.5.0_3.0_1725433912557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_sikubert_pipeline_zh_5.5.0_3.0_1725433912557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_sikubert_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_sikubert_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_sikubert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|406.6 MB|
+
+## References
+
+https://huggingface.co/SIKU-BERT/sikubert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_sikubert_zh.md b/docs/_posts/ahmedlone127/2024-09-04-sent_sikubert_zh.md
new file mode 100644
index 00000000000000..6e837af744aba8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_sikubert_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese sent_sikubert BertSentenceEmbeddings from SIKU-BERT
+author: John Snow Labs
+name: sent_sikubert
+date: 2024-09-04
+tags: [zh, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_sikubert` is a Chinese model originally trained by SIKU-BERT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_sikubert_zh_5.5.0_3.0_1725433892161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_sikubert_zh_5.5.0_3.0_1725433892161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_sikubert","zh") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_sikubert","zh") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_sikubert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|zh|
+|Size:|406.1 MB|
+
+## References
+
+https://huggingface.co/SIKU-BERT/sikubert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_splade_pp_english_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_splade_pp_english_v2_en.md
new file mode 100644
index 00000000000000..8513285f0caa13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_splade_pp_english_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_splade_pp_english_v2 BertSentenceEmbeddings from prithivida
+author: John Snow Labs
+name: sent_splade_pp_english_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_splade_pp_english_v2` is a English model originally trained by prithivida.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_splade_pp_english_v2_en_5.5.0_3.0_1725415474383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_splade_pp_english_v2_en_5.5.0_3.0_1725415474383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_splade_pp_english_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_splade_pp_english_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_splade_pp_english_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/prithivida/Splade_PP_en_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_tinybert_general_4l_312d_german_de.md b/docs/_posts/ahmedlone127/2024-09-04-sent_tinybert_general_4l_312d_german_de.md
new file mode 100644
index 00000000000000..b787ad295829dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_tinybert_general_4l_312d_german_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German sent_tinybert_general_4l_312d_german BertSentenceEmbeddings from dvm1983
+author: John Snow Labs
+name: sent_tinybert_general_4l_312d_german
+date: 2024-09-04
+tags: [de, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tinybert_general_4l_312d_german` is a German model originally trained by dvm1983.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tinybert_general_4l_312d_german_de_5.5.0_3.0_1725454497647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tinybert_general_4l_312d_german_de_5.5.0_3.0_1725454497647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_tinybert_general_4l_312d_german","de") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_tinybert_general_4l_312d_german","de") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tinybert_general_4l_312d_german|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|54.5 MB|
+
+## References
+
+https://huggingface.co/dvm1983/TinyBERT_General_4L_312D_de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_tinybert_general_4l_312d_german_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-04-sent_tinybert_general_4l_312d_german_pipeline_de.md
new file mode 100644
index 00000000000000..cda57f96fa471b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_tinybert_general_4l_312d_german_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_tinybert_general_4l_312d_german_pipeline pipeline BertSentenceEmbeddings from dvm1983
+author: John Snow Labs
+name: sent_tinybert_general_4l_312d_german_pipeline
+date: 2024-09-04
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tinybert_general_4l_312d_german_pipeline` is a German model originally trained by dvm1983.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tinybert_general_4l_312d_german_pipeline_de_5.5.0_3.0_1725454500915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tinybert_general_4l_312d_german_pipeline_de_5.5.0_3.0_1725454500915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_tinybert_general_4l_312d_german_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_tinybert_general_4l_312d_german_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tinybert_general_4l_312d_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|55.1 MB|
+
+## References
+
+https://huggingface.co/dvm1983/TinyBERT_General_4L_312D_de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_pretrain_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_pretrain_en.md
new file mode 100644
index 00000000000000..e413fc588aa45a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_pretrain_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_pretrain XlmRoBertaSentenceEmbeddings from hadifar
+author: John Snow Labs
+name: sent_xlm_pretrain
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_pretrain` is a English model originally trained by hadifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_pretrain_en_5.5.0_3.0_1725419911513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_pretrain_en_5.5.0_3.0_1725419911513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_pretrain","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_pretrain","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_pretrain|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hadifar/xlm_pretrain
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_pretrain_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_pretrain_pipeline_en.md
new file mode 100644
index 00000000000000..b8dae7b1ea7b10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_pretrain_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_pretrain_pipeline pipeline XlmRoBertaSentenceEmbeddings from hadifar
+author: John Snow Labs
+name: sent_xlm_pretrain_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_pretrain_pipeline` is a English model originally trained by hadifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_pretrain_pipeline_en_5.5.0_3.0_1725419967751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_pretrain_pipeline_en_5.5.0_3.0_1725419967751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_pretrain_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_pretrain_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_pretrain_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hadifar/xlm_pretrain
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_english_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_english_en.md
new file mode 100644
index 00000000000000..9276e0bbdde112
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_english XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_english
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_english` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_english_en_5.5.0_3.0_1725419665713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_english_en_5.5.0_3.0_1725419665713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-english
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_kintweetse_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_kintweetse_en.md
new file mode 100644
index 00000000000000..858889193e3ce6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_kintweetse_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_kintweetse XlmRoBertaSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_kintweetse
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_kintweetse` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kintweetse_en_5.5.0_3.0_1725420745613.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kintweetse_en_5.5.0_3.0_1725420745613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_kintweetse","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_kintweetse","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_kintweetse|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kintweetsE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_kintweetse_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_kintweetse_pipeline_en.md
new file mode 100644
index 00000000000000..1904dd4539a2ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_kintweetse_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_kintweetse_pipeline pipeline XlmRoBertaSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_kintweetse_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_kintweetse_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kintweetse_pipeline_en_5.5.0_3.0_1725420802849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kintweetse_pipeline_en_5.5.0_3.0_1725420802849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_kintweetse_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_kintweetse_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_kintweetse_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kintweetsE
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_luganda_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_luganda_en.md
new file mode 100644
index 00000000000000..4b2fe588886b64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_luganda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_luganda XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_luganda
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_luganda` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_luganda_en_5.5.0_3.0_1725420995244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_luganda_en_5.5.0_3.0_1725420995244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_luganda","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_luganda","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_luganda|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-luganda
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_yiddish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_yiddish_pipeline_en.md
new file mode 100644
index 00000000000000..189a6b02a9a819
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_yiddish_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_yiddish_pipeline pipeline XlmRoBertaSentenceEmbeddings from urieli
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_yiddish_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_yiddish_pipeline` is a English model originally trained by urieli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_yiddish_pipeline_en_5.5.0_3.0_1725420145167.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_yiddish_pipeline_en_5.5.0_3.0_1725420145167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_yiddish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_yiddish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_yiddish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/urieli/xlm-roberta-base-finetuned-yiddish
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_longformer_4096_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_longformer_4096_pipeline_en.md
new file mode 100644
index 00000000000000..dd9e46fb0d3234
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_longformer_4096_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_longformer_4096_pipeline pipeline XlmRoBertaSentenceEmbeddings from ogaloglu
+author: John Snow Labs
+name: sent_xlm_roberta_base_longformer_4096_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_longformer_4096_pipeline` is a English model originally trained by ogaloglu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_longformer_4096_pipeline_en_5.5.0_3.0_1725419231670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_longformer_4096_pipeline_en_5.5.0_3.0_1725419231670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_longformer_4096_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_longformer_4096_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_longformer_4096_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ogaloglu/xlm-roberta-base-longformer-4096
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_longformer_base_4096_peltarion_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_longformer_base_4096_peltarion_en.md
new file mode 100644
index 00000000000000..7b3143a62d8537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_longformer_base_4096_peltarion_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_longformer_base_4096_peltarion XlmRoBertaSentenceEmbeddings from Peltarion
+author: John Snow Labs
+name: sent_xlm_roberta_longformer_base_4096_peltarion
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_longformer_base_4096_peltarion` is a English model originally trained by Peltarion.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_longformer_base_4096_peltarion_en_5.5.0_3.0_1725419782056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_longformer_base_4096_peltarion_en_5.5.0_3.0_1725419782056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_longformer_base_4096_peltarion","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_longformer_base_4096_peltarion","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_longformer_base_4096_peltarion|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Peltarion/xlm-roberta-longformer-base-4096
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_longformer_base_4096_peltarion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_longformer_base_4096_peltarion_pipeline_en.md
new file mode 100644
index 00000000000000..15583e33fe1ca5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_longformer_base_4096_peltarion_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_longformer_base_4096_peltarion_pipeline pipeline XlmRoBertaSentenceEmbeddings from Peltarion
+author: John Snow Labs
+name: sent_xlm_roberta_longformer_base_4096_peltarion_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_longformer_base_4096_peltarion_pipeline` is a English model originally trained by Peltarion.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_longformer_base_4096_peltarion_pipeline_en_5.5.0_3.0_1725419843914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_longformer_base_4096_peltarion_pipeline_en_5.5.0_3.0_1725419843914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_longformer_base_4096_peltarion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_longformer_base_4096_peltarion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_longformer_base_4096_peltarion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Peltarion/xlm-roberta-longformer-base-4096
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sentencepiecebpe_cc100_french_morphemes_en.md b/docs/_posts/ahmedlone127/2024-09-04-sentencepiecebpe_cc100_french_morphemes_en.md
new file mode 100644
index 00000000000000..86908f974d68a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sentencepiecebpe_cc100_french_morphemes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentencepiecebpe_cc100_french_morphemes CamemBertEmbeddings from BioMedTok
+author: John Snow Labs
+name: sentencepiecebpe_cc100_french_morphemes
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentencepiecebpe_cc100_french_morphemes` is a English model originally trained by BioMedTok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentencepiecebpe_cc100_french_morphemes_en_5.5.0_3.0_1725441908937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentencepiecebpe_cc100_french_morphemes_en_5.5.0_3.0_1725441908937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("sentencepiecebpe_cc100_french_morphemes","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("sentencepiecebpe_cc100_french_morphemes","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentencepiecebpe_cc100_french_morphemes|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|412.6 MB|
+
+## References
+
+https://huggingface.co/BioMedTok/SentencePieceBPE-CC100-FR-Morphemes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sentiment_detection_using_bert_en.md b/docs/_posts/ahmedlone127/2024-09-04-sentiment_detection_using_bert_en.md
new file mode 100644
index 00000000000000..aaa64d6b54cab8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sentiment_detection_using_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_detection_using_bert RoBertaForSequenceClassification from nikesh66
+author: John Snow Labs
+name: sentiment_detection_using_bert
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_detection_using_bert` is a English model originally trained by nikesh66.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_detection_using_bert_en_5.5.0_3.0_1725486255533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_detection_using_bert_en_5.5.0_3.0_1725486255533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("sentiment_detection_using_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("sentiment_detection_using_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_detection_using_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.8 MB|
+
+## References
+
+https://huggingface.co/nikesh66/Sentiment-Detection-using-BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sentiment_detection_using_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sentiment_detection_using_bert_pipeline_en.md
new file mode 100644
index 00000000000000..92ce4a2fc4f720
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sentiment_detection_using_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_detection_using_bert_pipeline pipeline RoBertaForSequenceClassification from nikesh66
+author: John Snow Labs
+name: sentiment_detection_using_bert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_detection_using_bert_pipeline` is a English model originally trained by nikesh66.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_detection_using_bert_pipeline_en_5.5.0_3.0_1725486270705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_detection_using_bert_pipeline_en_5.5.0_3.0_1725486270705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_detection_using_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_detection_using_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_detection_using_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.9 MB|
+
+## References
+
+https://huggingface.co/nikesh66/Sentiment-Detection-using-BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sentiment_finnlp_thai_katkatkuu_en.md b/docs/_posts/ahmedlone127/2024-09-04-sentiment_finnlp_thai_katkatkuu_en.md
new file mode 100644
index 00000000000000..3226a7422c4c1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sentiment_finnlp_thai_katkatkuu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_finnlp_thai_katkatkuu CamemBertForSequenceClassification from Katkatkuu
+author: John Snow Labs
+name: sentiment_finnlp_thai_katkatkuu
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_finnlp_thai_katkatkuu` is a English model originally trained by Katkatkuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_finnlp_thai_katkatkuu_en_5.5.0_3.0_1725466406225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_finnlp_thai_katkatkuu_en_5.5.0_3.0_1725466406225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("sentiment_finnlp_thai_katkatkuu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sentiment_finnlp_thai_katkatkuu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_finnlp_thai_katkatkuu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/Katkatkuu/sentiment-finnlp-th
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sentiment_finnlp_thai_katkatkuu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sentiment_finnlp_thai_katkatkuu_pipeline_en.md
new file mode 100644
index 00000000000000..a5234287d0541b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sentiment_finnlp_thai_katkatkuu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_finnlp_thai_katkatkuu_pipeline pipeline CamemBertForSequenceClassification from Katkatkuu
+author: John Snow Labs
+name: sentiment_finnlp_thai_katkatkuu_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_finnlp_thai_katkatkuu_pipeline` is a English model originally trained by Katkatkuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_finnlp_thai_katkatkuu_pipeline_en_5.5.0_3.0_1725466425218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_finnlp_thai_katkatkuu_pipeline_en_5.5.0_3.0_1725466425218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_finnlp_thai_katkatkuu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_finnlp_thai_katkatkuu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_finnlp_thai_katkatkuu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/Katkatkuu/sentiment-finnlp-th
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-serbian_test_clip_en.md b/docs/_posts/ahmedlone127/2024-09-04-serbian_test_clip_en.md
new file mode 100644
index 00000000000000..0350eaca125c68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-serbian_test_clip_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English serbian_test_clip CLIPForZeroShotClassification from aurelio-ai
+author: John Snow Labs
+name: serbian_test_clip
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`serbian_test_clip` is a English model originally trained by aurelio-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/serbian_test_clip_en_5.5.0_3.0_1725456655782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/serbian_test_clip_en_5.5.0_3.0_1725456655782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("serbian_test_clip","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("serbian_test_clip","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|serbian_test_clip|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|536.6 KB|
+
+## References
+
+https://huggingface.co/aurelio-ai/sr-test-clip
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-serbocroatian_camembert_lstm_en.md b/docs/_posts/ahmedlone127/2024-09-04-serbocroatian_camembert_lstm_en.md
new file mode 100644
index 00000000000000..89c5b4af21cf2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-serbocroatian_camembert_lstm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English serbocroatian_camembert_lstm CamemBertForSequenceClassification from elmazouri
+author: John Snow Labs
+name: serbocroatian_camembert_lstm
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`serbocroatian_camembert_lstm` is a English model originally trained by elmazouri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/serbocroatian_camembert_lstm_en_5.5.0_3.0_1725466819198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/serbocroatian_camembert_lstm_en_5.5.0_3.0_1725466819198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("serbocroatian_camembert_lstm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("serbocroatian_camembert_lstm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|serbocroatian_camembert_lstm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.8 MB|
+
+## References
+
+https://huggingface.co/elmazouri/SH_Camembert_LSTM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-serbocroatian_camembert_lstm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-serbocroatian_camembert_lstm_pipeline_en.md
new file mode 100644
index 00000000000000..3fe36eee17e269
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-serbocroatian_camembert_lstm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English serbocroatian_camembert_lstm_pipeline pipeline CamemBertForSequenceClassification from elmazouri
+author: John Snow Labs
+name: serbocroatian_camembert_lstm_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`serbocroatian_camembert_lstm_pipeline` is a English model originally trained by elmazouri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/serbocroatian_camembert_lstm_pipeline_en_5.5.0_3.0_1725466846239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/serbocroatian_camembert_lstm_pipeline_en_5.5.0_3.0_1725466846239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("serbocroatian_camembert_lstm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("serbocroatian_camembert_lstm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|serbocroatian_camembert_lstm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|394.9 MB|
+
+## References
+
+https://huggingface.co/elmazouri/SH_Camembert_LSTM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-setfit_model_feb11_misinformation_on_convoy_en.md b/docs/_posts/ahmedlone127/2024-09-04-setfit_model_feb11_misinformation_on_convoy_en.md
new file mode 100644
index 00000000000000..0629031e56dc16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-setfit_model_feb11_misinformation_on_convoy_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English setfit_model_feb11_misinformation_on_convoy MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_feb11_misinformation_on_convoy
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_feb11_misinformation_on_convoy` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_feb11_misinformation_on_convoy_en_5.5.0_3.0_1725470208830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_feb11_misinformation_on_convoy_en_5.5.0_3.0_1725470208830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("setfit_model_feb11_misinformation_on_convoy","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("setfit_model_feb11_misinformation_on_convoy","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_feb11_misinformation_on_convoy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit-model-Feb11-Misinformation-on-Convoy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-setfit_model_feb11_misinformation_on_convoy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-setfit_model_feb11_misinformation_on_convoy_pipeline_en.md
new file mode 100644
index 00000000000000..8ee715d6a39acf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-setfit_model_feb11_misinformation_on_convoy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_model_feb11_misinformation_on_convoy_pipeline pipeline MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_feb11_misinformation_on_convoy_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_feb11_misinformation_on_convoy_pipeline` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_feb11_misinformation_on_convoy_pipeline_en_5.5.0_3.0_1725470229431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_feb11_misinformation_on_convoy_pipeline_en_5.5.0_3.0_1725470229431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("setfit_model_feb11_misinformation_on_convoy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_model_feb11_misinformation_on_convoy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_feb11_misinformation_on_convoy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit-model-Feb11-Misinformation-on-Convoy
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-setfit_model_ireland_binary_label0_epochs2_en.md b/docs/_posts/ahmedlone127/2024-09-04-setfit_model_ireland_binary_label0_epochs2_en.md
new file mode 100644
index 00000000000000..e700708e978990
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-setfit_model_ireland_binary_label0_epochs2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English setfit_model_ireland_binary_label0_epochs2 MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_ireland_binary_label0_epochs2
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_ireland_binary_label0_epochs2` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_binary_label0_epochs2_en_5.5.0_3.0_1725469981598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_binary_label0_epochs2_en_5.5.0_3.0_1725469981598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("setfit_model_ireland_binary_label0_epochs2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("setfit_model_ireland_binary_label0_epochs2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_ireland_binary_label0_epochs2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit_model_Ireland_binary_label0_epochs2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-setfit_model_ireland_binary_label0_epochs2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-setfit_model_ireland_binary_label0_epochs2_pipeline_en.md
new file mode 100644
index 00000000000000..cc8e24c58b48ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-setfit_model_ireland_binary_label0_epochs2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_model_ireland_binary_label0_epochs2_pipeline pipeline MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_ireland_binary_label0_epochs2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_ireland_binary_label0_epochs2_pipeline` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_binary_label0_epochs2_pipeline_en_5.5.0_3.0_1725470002292.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_binary_label0_epochs2_pipeline_en_5.5.0_3.0_1725470002292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("setfit_model_ireland_binary_label0_epochs2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_model_ireland_binary_label0_epochs2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_ireland_binary_label0_epochs2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit_model_Ireland_binary_label0_epochs2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-setfit_sentiment_analysis_ep20_en.md b/docs/_posts/ahmedlone127/2024-09-04-setfit_sentiment_analysis_ep20_en.md
new file mode 100644
index 00000000000000..3d596a0e996464
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-setfit_sentiment_analysis_ep20_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English setfit_sentiment_analysis_ep20 MPNetEmbeddings from gayatrividhate
+author: John Snow Labs
+name: setfit_sentiment_analysis_ep20
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_sentiment_analysis_ep20` is a English model originally trained by gayatrividhate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_sentiment_analysis_ep20_en_5.5.0_3.0_1725469895670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_sentiment_analysis_ep20_en_5.5.0_3.0_1725469895670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("setfit_sentiment_analysis_ep20","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("setfit_sentiment_analysis_ep20","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_sentiment_analysis_ep20|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/gayatrividhate/SetFit_sentiment_analysis_ep20
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-setfit_sentiment_analysis_ep20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-setfit_sentiment_analysis_ep20_pipeline_en.md
new file mode 100644
index 00000000000000..4e2019fc4bcb91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-setfit_sentiment_analysis_ep20_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_sentiment_analysis_ep20_pipeline pipeline MPNetEmbeddings from gayatrividhate
+author: John Snow Labs
+name: setfit_sentiment_analysis_ep20_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_sentiment_analysis_ep20_pipeline` is a English model originally trained by gayatrividhate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_sentiment_analysis_ep20_pipeline_en_5.5.0_3.0_1725469917076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_sentiment_analysis_ep20_pipeline_en_5.5.0_3.0_1725469917076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("setfit_sentiment_analysis_ep20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_sentiment_analysis_ep20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_sentiment_analysis_ep20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/gayatrividhate/SetFit_sentiment_analysis_ep20
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-single_docalog_en.md b/docs/_posts/ahmedlone127/2024-09-04-single_docalog_en.md
new file mode 100644
index 00000000000000..dea0a036b91242
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-single_docalog_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English single_docalog RoBertaForQuestionAnswering from alistvt
+author: John Snow Labs
+name: single_docalog
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`single_docalog` is a English model originally trained by alistvt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/single_docalog_en_5.5.0_3.0_1725480054284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/single_docalog_en_5.5.0_3.0_1725480054284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("single_docalog","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("single_docalog", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|single_docalog|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/alistvt/single-docalog
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-single_docalog_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-single_docalog_pipeline_en.md
new file mode 100644
index 00000000000000..974307da3865d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-single_docalog_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English single_docalog_pipeline pipeline RoBertaForQuestionAnswering from alistvt
+author: John Snow Labs
+name: single_docalog_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`single_docalog_pipeline` is a English model originally trained by alistvt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/single_docalog_pipeline_en_5.5.0_3.0_1725480118128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/single_docalog_pipeline_en_5.5.0_3.0_1725480118128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("single_docalog_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("single_docalog_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|single_docalog_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/alistvt/single-docalog
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb25_en.md b/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb25_en.md
new file mode 100644
index 00000000000000..196f668c5e04b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb25_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sitexsometre_camembert_base_ccnet_stsb25 CamemBertForSequenceClassification from Kigo1974
+author: John Snow Labs
+name: sitexsometre_camembert_base_ccnet_stsb25
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_base_ccnet_stsb25` is a English model originally trained by Kigo1974.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb25_en_5.5.0_3.0_1725466660031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb25_en_5.5.0_3.0_1725466660031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_base_ccnet_stsb25","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_base_ccnet_stsb25", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sitexsometre_camembert_base_ccnet_stsb25|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|390.8 MB|
+
+## References
+
+https://huggingface.co/Kigo1974/sitexsometre-camembert-base-ccnet-stsb25
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb50_en.md b/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb50_en.md
new file mode 100644
index 00000000000000..dbf10fd84f8b98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb50_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sitexsometre_camembert_base_ccnet_stsb50 CamemBertForSequenceClassification from Kigo1974
+author: John Snow Labs
+name: sitexsometre_camembert_base_ccnet_stsb50
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_base_ccnet_stsb50` is a English model originally trained by Kigo1974.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb50_en_5.5.0_3.0_1725467056975.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb50_en_5.5.0_3.0_1725467056975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_base_ccnet_stsb50","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sitexsometre_camembert_base_ccnet_stsb50", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sitexsometre_camembert_base_ccnet_stsb50|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|390.8 MB|
+
+## References
+
+https://huggingface.co/Kigo1974/sitexsometre-camembert-base-ccnet-stsb50
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb50_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb50_pipeline_en.md
new file mode 100644
index 00000000000000..3b5cfe12664d89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_base_ccnet_stsb50_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sitexsometre_camembert_base_ccnet_stsb50_pipeline pipeline CamemBertForSequenceClassification from Kigo1974
+author: John Snow Labs
+name: sitexsometre_camembert_base_ccnet_stsb50_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_base_ccnet_stsb50_pipeline` is a English model originally trained by Kigo1974.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb50_pipeline_en_5.5.0_3.0_1725467086223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_base_ccnet_stsb50_pipeline_en_5.5.0_3.0_1725467086223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sitexsometre_camembert_base_ccnet_stsb50_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sitexsometre_camembert_base_ccnet_stsb50_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sitexsometre_camembert_base_ccnet_stsb50_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|390.8 MB|
+
+## References
+
+https://huggingface.co/Kigo1974/sitexsometre-camembert-base-ccnet-stsb50
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_large_stsb25_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_large_stsb25_pipeline_en.md
new file mode 100644
index 00000000000000..30f4d6ce745c55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sitexsometre_camembert_large_stsb25_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sitexsometre_camembert_large_stsb25_pipeline pipeline CamemBertForSequenceClassification from Kigo1974
+author: John Snow Labs
+name: sitexsometre_camembert_large_stsb25_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sitexsometre_camembert_large_stsb25_pipeline` is a English model originally trained by Kigo1974.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_large_stsb25_pipeline_en_5.5.0_3.0_1725467216281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sitexsometre_camembert_large_stsb25_pipeline_en_5.5.0_3.0_1725467216281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sitexsometre_camembert_large_stsb25_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sitexsometre_camembert_large_stsb25_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sitexsometre_camembert_large_stsb25_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|805.5 MB|
+
+## References
+
+https://huggingface.co/Kigo1974/sitexsometre-camembert-large-stsb25
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sota_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-sota_1_en.md
new file mode 100644
index 00000000000000..05e22af6f5cd11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sota_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sota_1 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: sota_1
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sota_1` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sota_1_en_5.5.0_3.0_1725453435965.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sota_1_en_5.5.0_3.0_1725453435965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("sota_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("sota_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sota_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/SOTA_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sota_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sota_1_pipeline_en.md
new file mode 100644
index 00000000000000..b1da848965bc46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sota_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sota_1_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: sota_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sota_1_pipeline` is a English model originally trained by BaronSch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sota_1_pipeline_en_5.5.0_3.0_1725453458344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sota_1_pipeline_en_5.5.0_3.0_1725453458344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sota_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sota_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sota_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/SOTA_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-southern_sotho_all_mpnet_finetuned_comb_3000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-southern_sotho_all_mpnet_finetuned_comb_3000_pipeline_en.md
new file mode 100644
index 00000000000000..4517677a5b2c57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-southern_sotho_all_mpnet_finetuned_comb_3000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_comb_3000_pipeline pipeline MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_comb_3000_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_comb_3000_pipeline` is a English model originally trained by danfeg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_comb_3000_pipeline_en_5.5.0_3.0_1725470251964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_comb_3000_pipeline_en_5.5.0_3.0_1725470251964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("southern_sotho_all_mpnet_finetuned_comb_3000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("southern_sotho_all_mpnet_finetuned_comb_3000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_comb_3000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-COMB-3000
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-spark_name_georgian_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-04-spark_name_georgian_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..5b8426e75b427a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-spark_name_georgian_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spark_name_georgian_tonga_tonga_islands_english MarianTransformer from ihebaker10
+author: John Snow Labs
+name: spark_name_georgian_tonga_tonga_islands_english
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spark_name_georgian_tonga_tonga_islands_english` is a English model originally trained by ihebaker10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spark_name_georgian_tonga_tonga_islands_english_en_5.5.0_3.0_1725493732264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spark_name_georgian_tonga_tonga_islands_english_en_5.5.0_3.0_1725493732264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("spark_name_georgian_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("spark_name_georgian_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spark_name_georgian_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|300.4 MB|
+
+## References
+
+https://huggingface.co/ihebaker10/spark-name-ka-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_en.md b/docs/_posts/ahmedlone127/2024-09-04-splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_en.md
new file mode 100644
index 00000000000000..ff995439ff8910
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated DistilBertEmbeddings from vocab-transformers
+author: John Snow Labs
+name: splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated` is a English model originally trained by vocab-transformers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_en_5.5.0_3.0_1725418805925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_en_5.5.0_3.0_1725418805925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|905.9 MB|
+
+## References
+
+https://huggingface.co/vocab-transformers/splade_100k-msmarco-distilbert-word2vec256k-MLM_785k_emb_updated
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline_en.md
new file mode 100644
index 00000000000000..8a2ea861464cbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline pipeline DistilBertEmbeddings from vocab-transformers
+author: John Snow Labs
+name: splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline` is a English model originally trained by vocab-transformers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline_en_5.5.0_3.0_1725418849709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline_en_5.5.0_3.0_1725418849709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|splade_100k_msmarco_distilbert_word2vec256k_mlm_785k_emb_updated_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|906.0 MB|
+
+## References
+
+https://huggingface.co/vocab-transformers/splade_100k-msmarco-distilbert-word2vec256k-MLM_785k_emb_updated
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-squad_qa_model_mrsteveme_en.md b/docs/_posts/ahmedlone127/2024-09-04-squad_qa_model_mrsteveme_en.md
new file mode 100644
index 00000000000000..a5a3ac3d2af4cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-squad_qa_model_mrsteveme_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English squad_qa_model_mrsteveme DistilBertForQuestionAnswering from Mrsteveme
+author: John Snow Labs
+name: squad_qa_model_mrsteveme
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squad_qa_model_mrsteveme` is a English model originally trained by Mrsteveme.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squad_qa_model_mrsteveme_en_5.5.0_3.0_1725465289145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squad_qa_model_mrsteveme_en_5.5.0_3.0_1725465289145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("squad_qa_model_mrsteveme","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("squad_qa_model_mrsteveme", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squad_qa_model_mrsteveme|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Mrsteveme/squad_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-squad_qa_model_mrsteveme_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-squad_qa_model_mrsteveme_pipeline_en.md
new file mode 100644
index 00000000000000..749654382943b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-squad_qa_model_mrsteveme_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English squad_qa_model_mrsteveme_pipeline pipeline DistilBertForQuestionAnswering from Mrsteveme
+author: John Snow Labs
+name: squad_qa_model_mrsteveme_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squad_qa_model_mrsteveme_pipeline` is a English model originally trained by Mrsteveme.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squad_qa_model_mrsteveme_pipeline_en_5.5.0_3.0_1725465305574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squad_qa_model_mrsteveme_pipeline_en_5.5.0_3.0_1725465305574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("squad_qa_model_mrsteveme_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("squad_qa_model_mrsteveme_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squad_qa_model_mrsteveme_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Mrsteveme/squad_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-startup_score_en.md b/docs/_posts/ahmedlone127/2024-09-04-startup_score_en.md
new file mode 100644
index 00000000000000..f6a7d8e5fce3f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-startup_score_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English startup_score AlbertForSequenceClassification from k011
+author: John Snow Labs
+name: startup_score
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`startup_score` is a English model originally trained by k011.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/startup_score_en_5.5.0_3.0_1725464666407.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/startup_score_en_5.5.0_3.0_1725464666407.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("startup_score","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("startup_score", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|startup_score|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/k011/startup-score
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-startup_score_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-startup_score_pipeline_en.md
new file mode 100644
index 00000000000000..8b17fb514856af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-startup_score_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English startup_score_pipeline pipeline AlbertForSequenceClassification from k011
+author: John Snow Labs
+name: startup_score_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`startup_score_pipeline` is a English model originally trained by k011.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/startup_score_pipeline_en_5.5.0_3.0_1725464668721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/startup_score_pipeline_en_5.5.0_3.0_1725464668721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("startup_score_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("startup_score_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|startup_score_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/k011/startup-score
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-stt_best_en.md b/docs/_posts/ahmedlone127/2024-09-04-stt_best_en.md
new file mode 100644
index 00000000000000..2451f732c2496f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-stt_best_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English stt_best WhisperForCTC from benghoula
+author: John Snow Labs
+name: stt_best
+date: 2024-09-04
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stt_best` is a English model originally trained by benghoula.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stt_best_en_5.5.0_3.0_1725427027662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stt_best_en_5.5.0_3.0_1725427027662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("stt_best","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("stt_best", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stt_best|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/benghoula/stt_best
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-summfinfr_en.md b/docs/_posts/ahmedlone127/2024-09-04-summfinfr_en.md
new file mode 100644
index 00000000000000..22b3b2d6ada713
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-summfinfr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English summfinfr CamemBertEmbeddings from Ghani-25
+author: John Snow Labs
+name: summfinfr
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summfinfr` is a English model originally trained by Ghani-25.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summfinfr_en_5.5.0_3.0_1725443127270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summfinfr_en_5.5.0_3.0_1725443127270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("summfinfr","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("summfinfr","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summfinfr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Ghani-25/SummFinFR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-summfinfr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-summfinfr_pipeline_en.md
new file mode 100644
index 00000000000000..68e2cde49eda97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-summfinfr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English summfinfr_pipeline pipeline CamemBertEmbeddings from Ghani-25
+author: John Snow Labs
+name: summfinfr_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summfinfr_pipeline` is a English model originally trained by Ghani-25.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summfinfr_pipeline_en_5.5.0_3.0_1725443147537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summfinfr_pipeline_en_5.5.0_3.0_1725443147537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("summfinfr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("summfinfr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summfinfr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Ghani-25/SummFinFR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tara_roberta_base_persian_farsi_qa_fa.md b/docs/_posts/ahmedlone127/2024-09-04-tara_roberta_base_persian_farsi_qa_fa.md
new file mode 100644
index 00000000000000..710f919e3e4c9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tara_roberta_base_persian_farsi_qa_fa.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Persian tara_roberta_base_persian_farsi_qa RoBertaForQuestionAnswering from hosseinhimself
+author: John Snow Labs
+name: tara_roberta_base_persian_farsi_qa
+date: 2024-09-04
+tags: [fa, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tara_roberta_base_persian_farsi_qa` is a Persian model originally trained by hosseinhimself.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tara_roberta_base_persian_farsi_qa_fa_5.5.0_3.0_1725450747219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tara_roberta_base_persian_farsi_qa_fa_5.5.0_3.0_1725450747219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("tara_roberta_base_persian_farsi_qa","fa") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("tara_roberta_base_persian_farsi_qa", "fa")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tara_roberta_base_persian_farsi_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/hosseinhimself/tara-roberta-base-fa-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test3_en.md b/docs/_posts/ahmedlone127/2024-09-04-test3_en.md
new file mode 100644
index 00000000000000..11c45c57411e48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test3 DistilBertForTokenClassification from yam1ke
+author: John Snow Labs
+name: test3
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test3` is a English model originally trained by yam1ke.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test3_en_5.5.0_3.0_1725460349207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test3_en_5.5.0_3.0_1725460349207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("test3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("test3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yam1ke/test3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-test4_pipeline_en.md
new file mode 100644
index 00000000000000..34c7ab80462b8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test4_pipeline pipeline CamemBertEmbeddings from gilangcy
+author: John Snow Labs
+name: test4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test4_pipeline` is a English model originally trained by gilangcy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test4_pipeline_en_5.5.0_3.0_1725408604935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test4_pipeline_en_5.5.0_3.0_1725408604935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/gilangcy/test4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test_dynamic_pipeline_lysandre_en.md b/docs/_posts/ahmedlone127/2024-09-04-test_dynamic_pipeline_lysandre_en.md
new file mode 100644
index 00000000000000..b63be3814cba36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test_dynamic_pipeline_lysandre_en.md
@@ -0,0 +1,66 @@
+---
+layout: model
+title: English test_dynamic_pipeline_lysandre pipeline BertForSequenceClassification from lysandre
+author: John Snow Labs
+name: test_dynamic_pipeline_lysandre
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_dynamic_pipeline_lysandre` is a English model originally trained by lysandre.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_dynamic_pipeline_lysandre_en_5.5.0_3.0_1725433478986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_dynamic_pipeline_lysandre_en_5.5.0_3.0_1725433478986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_dynamic_pipeline_lysandre", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_dynamic_pipeline_lysandre", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_dynamic_pipeline_lysandre|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|361.3 KB|
+
+## References
+
+https://huggingface.co/lysandre/test-dynamic-pipeline
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test_dynamic_pipeline_lysandre_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-test_dynamic_pipeline_lysandre_pipeline_en.md
new file mode 100644
index 00000000000000..7461fe0bdb9e30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test_dynamic_pipeline_lysandre_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_dynamic_pipeline_lysandre_pipeline pipeline BertForSequenceClassification from lysandre
+author: John Snow Labs
+name: test_dynamic_pipeline_lysandre_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_dynamic_pipeline_lysandre_pipeline` is a English model originally trained by lysandre.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_dynamic_pipeline_lysandre_pipeline_en_5.5.0_3.0_1725433479405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_dynamic_pipeline_lysandre_pipeline_en_5.5.0_3.0_1725433479405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_dynamic_pipeline_lysandre_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_dynamic_pipeline_lysandre_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_dynamic_pipeline_lysandre_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|384.0 KB|
+
+## References
+
+https://huggingface.co/lysandre/test-dynamic-pipeline
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test_model_en.md b/docs/_posts/ahmedlone127/2024-09-04-test_model_en.md
new file mode 100644
index 00000000000000..21960ba895444d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_model DistilBertForTokenClassification from natalierobbins
+author: John Snow Labs
+name: test_model
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model` is a English model originally trained by natalierobbins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_en_5.5.0_3.0_1725492553150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_en_5.5.0_3.0_1725492553150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("test_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("test_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/natalierobbins/test_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test_model_gilangcy_en.md b/docs/_posts/ahmedlone127/2024-09-04-test_model_gilangcy_en.md
new file mode 100644
index 00000000000000..1950f828906ad3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test_model_gilangcy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_model_gilangcy CamemBertEmbeddings from gilangcy
+author: John Snow Labs
+name: test_model_gilangcy
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_gilangcy` is a English model originally trained by gilangcy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_gilangcy_en_5.5.0_3.0_1725409044361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_gilangcy_en_5.5.0_3.0_1725409044361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("test_model_gilangcy","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("test_model_gilangcy","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_gilangcy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/gilangcy/Test_Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test_model_gilangcy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-test_model_gilangcy_pipeline_en.md
new file mode 100644
index 00000000000000..ad06af342265e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test_model_gilangcy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_model_gilangcy_pipeline pipeline CamemBertEmbeddings from gilangcy
+author: John Snow Labs
+name: test_model_gilangcy_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_gilangcy_pipeline` is a English model originally trained by gilangcy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_gilangcy_pipeline_en_5.5.0_3.0_1725409121723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_gilangcy_pipeline_en_5.5.0_3.0_1725409121723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_model_gilangcy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_model_gilangcy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_gilangcy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/gilangcy/Test_Model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test_trainer_en.md b/docs/_posts/ahmedlone127/2024-09-04-test_trainer_en.md
new file mode 100644
index 00000000000000..76c2efacf6d8d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test_trainer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_trainer RoBertaForQuestionAnswering from Mahdi721
+author: John Snow Labs
+name: test_trainer
+date: 2024-09-04
+tags: [roberta, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_trainer` is a English model originally trained by Mahdi721.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_en_5.5.0_3.0_1725480726189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_en_5.5.0_3.0_1725480726189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("test_trainer","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering  
+    .pretrained("test_trainer", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_trainer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|389.7 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/Mahdi721/test-trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-thesis_clip_geoloc_continent_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-thesis_clip_geoloc_continent_pipeline_en.md
new file mode 100644
index 00000000000000..49ff92b24db39f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-thesis_clip_geoloc_continent_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English thesis_clip_geoloc_continent_pipeline pipeline CLIPForZeroShotClassification from jrheiner
+author: John Snow Labs
+name: thesis_clip_geoloc_continent_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thesis_clip_geoloc_continent_pipeline` is a English model originally trained by jrheiner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thesis_clip_geoloc_continent_pipeline_en_5.5.0_3.0_1725455403380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thesis_clip_geoloc_continent_pipeline_en_5.5.0_3.0_1725455403380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("thesis_clip_geoloc_continent_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("thesis_clip_geoloc_continent_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|thesis_clip_geoloc_continent_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/jrheiner/thesis-clip-geoloc-continent
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tibetan_roberta_s_e3_en.md b/docs/_posts/ahmedlone127/2024-09-04-tibetan_roberta_s_e3_en.md
new file mode 100644
index 00000000000000..18f6e4a6db8e6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tibetan_roberta_s_e3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tibetan_roberta_s_e3 RoBertaEmbeddings from spsither
+author: John Snow Labs
+name: tibetan_roberta_s_e3
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tibetan_roberta_s_e3` is a English model originally trained by spsither.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tibetan_roberta_s_e3_en_5.5.0_3.0_1725412168353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tibetan_roberta_s_e3_en_5.5.0_3.0_1725412168353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("tibetan_roberta_s_e3","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("tibetan_roberta_s_e3","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tibetan_roberta_s_e3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|311.4 MB|
+
+## References
+
+https://huggingface.co/spsither/tibetan_RoBERTa_S_e3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tibetan_roberta_s_e3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-tibetan_roberta_s_e3_pipeline_en.md
new file mode 100644
index 00000000000000..f5c06228a7ea40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tibetan_roberta_s_e3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tibetan_roberta_s_e3_pipeline pipeline RoBertaEmbeddings from spsither
+author: John Snow Labs
+name: tibetan_roberta_s_e3_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tibetan_roberta_s_e3_pipeline` is a English model originally trained by spsither.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tibetan_roberta_s_e3_pipeline_en_5.5.0_3.0_1725412184438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tibetan_roberta_s_e3_pipeline_en_5.5.0_3.0_1725412184438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tibetan_roberta_s_e3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tibetan_roberta_s_e3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tibetan_roberta_s_e3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.4 MB|
+
+## References
+
+https://huggingface.co/spsither/tibetan_RoBERTa_S_e3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tiny_distilroberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-04-tiny_distilroberta_base_en.md
new file mode 100644
index 00000000000000..7d42d8bf64ec9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tiny_distilroberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tiny_distilroberta_base RoBertaEmbeddings from sshleifer
+author: John Snow Labs
+name: tiny_distilroberta_base
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_distilroberta_base` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_distilroberta_base_en_5.5.0_3.0_1725412411058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_distilroberta_base_en_5.5.0_3.0_1725412411058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("tiny_distilroberta_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("tiny_distilroberta_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_distilroberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.5 MB|
+
+## References
+
+https://huggingface.co/sshleifer/tiny-distilroberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tiny_distilroberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-tiny_distilroberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..d51018255b83d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tiny_distilroberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tiny_distilroberta_base_pipeline pipeline RoBertaEmbeddings from sshleifer
+author: John Snow Labs
+name: tiny_distilroberta_base_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_distilroberta_base_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_distilroberta_base_pipeline_en_5.5.0_3.0_1725412418415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_distilroberta_base_pipeline_en_5.5.0_3.0_1725412418415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tiny_distilroberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tiny_distilroberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_distilroberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 MB|
+
+## References
+
+https://huggingface.co/sshleifer/tiny-distilroberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tiny_random_bertfortokenclassification_ydshieh_en.md b/docs/_posts/ahmedlone127/2024-09-04-tiny_random_bertfortokenclassification_ydshieh_en.md
new file mode 100644
index 00000000000000..89b7dc2d2b1c3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tiny_random_bertfortokenclassification_ydshieh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tiny_random_bertfortokenclassification_ydshieh BertForTokenClassification from ydshieh
+author: John Snow Labs
+name: tiny_random_bertfortokenclassification_ydshieh
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_bertfortokenclassification_ydshieh` is a English model originally trained by ydshieh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_bertfortokenclassification_ydshieh_en_5.5.0_3.0_1725477872654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_bertfortokenclassification_ydshieh_en_5.5.0_3.0_1725477872654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("tiny_random_bertfortokenclassification_ydshieh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("tiny_random_bertfortokenclassification_ydshieh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_random_bertfortokenclassification_ydshieh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|357.2 KB|
+
+## References
+
+https://huggingface.co/ydshieh/tiny-random-BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline_en.md
new file mode 100644
index 00000000000000..4494e595c1102f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline pipeline CLIPForZeroShotClassification from wkcn
+author: John Snow Labs
+name: tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline` is a English model originally trained by wkcn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline_en_5.5.0_3.0_1725492113220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline_en_5.5.0_3.0_1725492113220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tinyclip_vit_39m_16_text_19m_yfcc15m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|200.2 MB|
+
+## References
+
+https://huggingface.co/wkcn/TinyCLIP-ViT-39M-16-Text-19M-YFCC15M
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tinyroberta_squad2_finetuned_emrqa_msquad_en.md b/docs/_posts/ahmedlone127/2024-09-04-tinyroberta_squad2_finetuned_emrqa_msquad_en.md
new file mode 100644
index 00000000000000..49a34fcfbcd6f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tinyroberta_squad2_finetuned_emrqa_msquad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tinyroberta_squad2_finetuned_emrqa_msquad RoBertaForQuestionAnswering from Eladio
+author: John Snow Labs
+name: tinyroberta_squad2_finetuned_emrqa_msquad
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinyroberta_squad2_finetuned_emrqa_msquad` is a English model originally trained by Eladio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_finetuned_emrqa_msquad_en_5.5.0_3.0_1725483526359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinyroberta_squad2_finetuned_emrqa_msquad_en_5.5.0_3.0_1725483526359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("tinyroberta_squad2_finetuned_emrqa_msquad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("tinyroberta_squad2_finetuned_emrqa_msquad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tinyroberta_squad2_finetuned_emrqa_msquad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|306.9 MB|
+
+## References
+
+https://huggingface.co/Eladio/tinyroberta-squad2-finetuned-emrqa-msquad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tofu_forget05_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-04-tofu_forget05_classifier_en.md
new file mode 100644
index 00000000000000..0ce1c8e6784d9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tofu_forget05_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tofu_forget05_classifier RoBertaForSequenceClassification from chrisliu298
+author: John Snow Labs
+name: tofu_forget05_classifier
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tofu_forget05_classifier` is a English model originally trained by chrisliu298.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tofu_forget05_classifier_en_5.5.0_3.0_1725452499034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tofu_forget05_classifier_en_5.5.0_3.0_1725452499034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("tofu_forget05_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("tofu_forget05_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tofu_forget05_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|433.0 MB|
+
+## References
+
+https://huggingface.co/chrisliu298/tofu_forget05_classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tofu_forget05_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-tofu_forget05_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..cca8901e82f85a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tofu_forget05_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tofu_forget05_classifier_pipeline pipeline RoBertaForSequenceClassification from chrisliu298
+author: John Snow Labs
+name: tofu_forget05_classifier_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tofu_forget05_classifier_pipeline` is a English model originally trained by chrisliu298.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tofu_forget05_classifier_pipeline_en_5.5.0_3.0_1725452522342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tofu_forget05_classifier_pipeline_en_5.5.0_3.0_1725452522342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tofu_forget05_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tofu_forget05_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tofu_forget05_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|433.0 MB|
+
+## References
+
+https://huggingface.co/chrisliu298/tofu_forget05_classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tonga_tonga_islands_classifier_v1_en.md b/docs/_posts/ahmedlone127/2024-09-04-tonga_tonga_islands_classifier_v1_en.md
new file mode 100644
index 00000000000000..3f0c8759f6b226
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tonga_tonga_islands_classifier_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tonga_tonga_islands_classifier_v1 MPNetEmbeddings from futuredatascience
+author: John Snow Labs
+name: tonga_tonga_islands_classifier_v1
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tonga_tonga_islands_classifier_v1` is a English model originally trained by futuredatascience.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tonga_tonga_islands_classifier_v1_en_5.5.0_3.0_1725470077672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tonga_tonga_islands_classifier_v1_en_5.5.0_3.0_1725470077672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("tonga_tonga_islands_classifier_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("tonga_tonga_islands_classifier_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tonga_tonga_islands_classifier_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/futuredatascience/to-classifier-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tonga_tonga_islands_classifier_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-tonga_tonga_islands_classifier_v1_pipeline_en.md
new file mode 100644
index 00000000000000..828aebd7028124
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tonga_tonga_islands_classifier_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tonga_tonga_islands_classifier_v1_pipeline pipeline MPNetEmbeddings from futuredatascience
+author: John Snow Labs
+name: tonga_tonga_islands_classifier_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tonga_tonga_islands_classifier_v1_pipeline` is a English model originally trained by futuredatascience.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tonga_tonga_islands_classifier_v1_pipeline_en_5.5.0_3.0_1725470097455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tonga_tonga_islands_classifier_v1_pipeline_en_5.5.0_3.0_1725470097455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tonga_tonga_islands_classifier_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tonga_tonga_islands_classifier_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tonga_tonga_islands_classifier_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/futuredatascience/to-classifier-v1
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tos_roberta_en.md b/docs/_posts/ahmedlone127/2024-09-04-tos_roberta_en.md
new file mode 100644
index 00000000000000..4bda77c73498b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tos_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tos_roberta RoBertaForSequenceClassification from CodeHima
+author: John Snow Labs
+name: tos_roberta
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tos_roberta` is a English model originally trained by CodeHima.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tos_roberta_en_5.5.0_3.0_1725485962900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tos_roberta_en_5.5.0_3.0_1725485962900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("tos_roberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("tos_roberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tos_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CodeHima/Tos-Roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tos_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-tos_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..31874b0df4f5df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tos_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tos_roberta_pipeline pipeline RoBertaForSequenceClassification from CodeHima
+author: John Snow Labs
+name: tos_roberta_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tos_roberta_pipeline` is a English model originally trained by CodeHima.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tos_roberta_pipeline_en_5.5.0_3.0_1725486042959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tos_roberta_pipeline_en_5.5.0_3.0_1725486042959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tos_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tos_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tos_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CodeHima/Tos-Roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-trained_model_mzhao39_en.md b/docs/_posts/ahmedlone127/2024-09-04-trained_model_mzhao39_en.md
new file mode 100644
index 00000000000000..ce94ebd8c1a5d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-trained_model_mzhao39_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trained_model_mzhao39 BertForTokenClassification from mzhao39
+author: John Snow Labs
+name: trained_model_mzhao39
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_model_mzhao39` is a English model originally trained by mzhao39.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_model_mzhao39_en_5.5.0_3.0_1725477776479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_model_mzhao39_en_5.5.0_3.0_1725477776479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("trained_model_mzhao39","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("trained_model_mzhao39", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_model_mzhao39|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/mzhao39/trained_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-translation_autoevaluate_en.md b/docs/_posts/ahmedlone127/2024-09-04-translation_autoevaluate_en.md
new file mode 100644
index 00000000000000..d37c57c8c87fac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-translation_autoevaluate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translation_autoevaluate MarianTransformer from autoevaluate
+author: John Snow Labs
+name: translation_autoevaluate
+date: 2024-09-04
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_autoevaluate` is a English model originally trained by autoevaluate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_autoevaluate_en_5.5.0_3.0_1725494037615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_autoevaluate_en_5.5.0_3.0_1725494037615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translation_autoevaluate","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translation_autoevaluate","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_autoevaluate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/autoevaluate/translation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_20epoch_en.md b/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_20epoch_en.md
new file mode 100644
index 00000000000000..8962809e135789
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_20epoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trust_merged_dataset_mdeberta_v3_20epoch DeBertaForSequenceClassification from luisespinosa
+author: John Snow Labs
+name: trust_merged_dataset_mdeberta_v3_20epoch
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trust_merged_dataset_mdeberta_v3_20epoch` is a English model originally trained by luisespinosa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trust_merged_dataset_mdeberta_v3_20epoch_en_5.5.0_3.0_1725439481701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trust_merged_dataset_mdeberta_v3_20epoch_en_5.5.0_3.0_1725439481701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("trust_merged_dataset_mdeberta_v3_20epoch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("trust_merged_dataset_mdeberta_v3_20epoch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trust_merged_dataset_mdeberta_v3_20epoch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|822.8 MB|
+
+## References
+
+https://huggingface.co/luisespinosa/trust-merged_dataset_mdeberta-v3_20epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_20epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_20epoch_pipeline_en.md
new file mode 100644
index 00000000000000..90a65ee683740f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_20epoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trust_merged_dataset_mdeberta_v3_20epoch_pipeline pipeline DeBertaForSequenceClassification from luisespinosa
+author: John Snow Labs
+name: trust_merged_dataset_mdeberta_v3_20epoch_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trust_merged_dataset_mdeberta_v3_20epoch_pipeline` is a English model originally trained by luisespinosa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trust_merged_dataset_mdeberta_v3_20epoch_pipeline_en_5.5.0_3.0_1725439615080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trust_merged_dataset_mdeberta_v3_20epoch_pipeline_en_5.5.0_3.0_1725439615080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trust_merged_dataset_mdeberta_v3_20epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trust_merged_dataset_mdeberta_v3_20epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trust_merged_dataset_mdeberta_v3_20epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|822.8 MB|
+
+## References
+
+https://huggingface.co/luisespinosa/trust-merged_dataset_mdeberta-v3_20epoch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-trustpilot_roberta_gender_en.md b/docs/_posts/ahmedlone127/2024-09-04-trustpilot_roberta_gender_en.md
new file mode 100644
index 00000000000000..c05427e53f605b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-trustpilot_roberta_gender_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trustpilot_roberta_gender RoBertaForSequenceClassification from riken01
+author: John Snow Labs
+name: trustpilot_roberta_gender
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trustpilot_roberta_gender` is a English model originally trained by riken01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trustpilot_roberta_gender_en_5.5.0_3.0_1725484975923.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trustpilot_roberta_gender_en_5.5.0_3.0_1725484975923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("trustpilot_roberta_gender","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("trustpilot_roberta_gender", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trustpilot_roberta_gender|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|452.7 MB|
+
+## References
+
+https://huggingface.co/riken01/trustpilot-roberta-gender
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-trustpilot_roberta_gender_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-trustpilot_roberta_gender_pipeline_en.md
new file mode 100644
index 00000000000000..abf86a5c264a57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-trustpilot_roberta_gender_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trustpilot_roberta_gender_pipeline pipeline RoBertaForSequenceClassification from riken01
+author: John Snow Labs
+name: trustpilot_roberta_gender_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trustpilot_roberta_gender_pipeline` is a English model originally trained by riken01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trustpilot_roberta_gender_pipeline_en_5.5.0_3.0_1725485004814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trustpilot_roberta_gender_pipeline_en_5.5.0_3.0_1725485004814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trustpilot_roberta_gender_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trustpilot_roberta_gender_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trustpilot_roberta_gender_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|452.7 MB|
+
+## References
+
+https://huggingface.co/riken01/trustpilot-roberta-gender
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tunlangmodel_test1_17_ar.md b/docs/_posts/ahmedlone127/2024-09-04-tunlangmodel_test1_17_ar.md
new file mode 100644
index 00000000000000..326a6ffdf415c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tunlangmodel_test1_17_ar.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Arabic tunlangmodel_test1_17 WhisperForCTC from Arbi-Houssem
+author: John Snow Labs
+name: tunlangmodel_test1_17
+date: 2024-09-04
+tags: [ar, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tunlangmodel_test1_17` is a Arabic model originally trained by Arbi-Houssem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tunlangmodel_test1_17_ar_5.5.0_3.0_1725430409048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tunlangmodel_test1_17_ar_5.5.0_3.0_1725430409048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("tunlangmodel_test1_17","ar") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("tunlangmodel_test1_17", "ar")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tunlangmodel_test1_17|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Arbi-Houssem/TunLangModel_test1.17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tunlangmodel_test1_17_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-tunlangmodel_test1_17_pipeline_ar.md
new file mode 100644
index 00000000000000..9f97e27ec06af6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tunlangmodel_test1_17_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic tunlangmodel_test1_17_pipeline pipeline WhisperForCTC from Arbi-Houssem
+author: John Snow Labs
+name: tunlangmodel_test1_17_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tunlangmodel_test1_17_pipeline` is a Arabic model originally trained by Arbi-Houssem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tunlangmodel_test1_17_pipeline_ar_5.5.0_3.0_1725430498195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tunlangmodel_test1_17_pipeline_ar_5.5.0_3.0_1725430498195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tunlangmodel_test1_17_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tunlangmodel_test1_17_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tunlangmodel_test1_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Arbi-Houssem/TunLangModel_test1.17
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-tupy_bert_large_binary_classifier_pt.md b/docs/_posts/ahmedlone127/2024-09-04-tupy_bert_large_binary_classifier_pt.md
new file mode 100644
index 00000000000000..9f07ccad683ea2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-tupy_bert_large_binary_classifier_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese tupy_bert_large_binary_classifier BertForSequenceClassification from Silly-Machine
+author: John Snow Labs
+name: tupy_bert_large_binary_classifier
+date: 2024-09-04
+tags: [pt, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tupy_bert_large_binary_classifier` is a Portuguese model originally trained by Silly-Machine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tupy_bert_large_binary_classifier_pt_5.5.0_3.0_1725432599606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tupy_bert_large_binary_classifier_pt_5.5.0_3.0_1725432599606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("tupy_bert_large_binary_classifier","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("tupy_bert_large_binary_classifier", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tupy_bert_large_binary_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|pt|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Silly-Machine/TuPy-Bert-Large-Binary-Classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-turkish_base_bert_punctuation_correction_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-04-turkish_base_bert_punctuation_correction_pipeline_tr.md
new file mode 100644
index 00000000000000..79ef6f7a90106d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-turkish_base_bert_punctuation_correction_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish turkish_base_bert_punctuation_correction_pipeline pipeline BertForTokenClassification from ytu-ce-cosmos
+author: John Snow Labs
+name: turkish_base_bert_punctuation_correction_pipeline
+date: 2024-09-04
+tags: [tr, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_base_bert_punctuation_correction_pipeline` is a Turkish model originally trained by ytu-ce-cosmos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_base_bert_punctuation_correction_pipeline_tr_5.5.0_3.0_1725449819772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_base_bert_punctuation_correction_pipeline_tr_5.5.0_3.0_1725449819772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkish_base_bert_punctuation_correction_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_base_bert_punctuation_correction_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_base_bert_punctuation_correction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|413.1 MB|
+
+## References
+
+https://huggingface.co/ytu-ce-cosmos/turkish-base-bert-punctuation-correction
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-turkish_base_bert_punctuation_correction_tr.md b/docs/_posts/ahmedlone127/2024-09-04-turkish_base_bert_punctuation_correction_tr.md
new file mode 100644
index 00000000000000..4a347e02d7989f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-turkish_base_bert_punctuation_correction_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish turkish_base_bert_punctuation_correction BertForTokenClassification from ytu-ce-cosmos
+author: John Snow Labs
+name: turkish_base_bert_punctuation_correction
+date: 2024-09-04
+tags: [tr, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_base_bert_punctuation_correction` is a Turkish model originally trained by ytu-ce-cosmos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_base_bert_punctuation_correction_tr_5.5.0_3.0_1725449799352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_base_bert_punctuation_correction_tr_5.5.0_3.0_1725449799352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("turkish_base_bert_punctuation_correction","tr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("turkish_base_bert_punctuation_correction", "tr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_base_bert_punctuation_correction|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|tr|
+|Size:|413.1 MB|
+
+## References
+
+https://huggingface.co/ytu-ce-cosmos/turkish-base-bert-punctuation-correction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-twitter_comment_roberta_base_indonesian_smsa_en.md b/docs/_posts/ahmedlone127/2024-09-04-twitter_comment_roberta_base_indonesian_smsa_en.md
new file mode 100644
index 00000000000000..b292bce88ba8a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-twitter_comment_roberta_base_indonesian_smsa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_comment_roberta_base_indonesian_smsa RoBertaForSequenceClassification from databoks-irfan
+author: John Snow Labs
+name: twitter_comment_roberta_base_indonesian_smsa
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_comment_roberta_base_indonesian_smsa` is a English model originally trained by databoks-irfan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_comment_roberta_base_indonesian_smsa_en_5.5.0_3.0_1725485281090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_comment_roberta_base_indonesian_smsa_en_5.5.0_3.0_1725485281090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("twitter_comment_roberta_base_indonesian_smsa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_comment_roberta_base_indonesian_smsa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_comment_roberta_base_indonesian_smsa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|473.2 MB|
+
+## References
+
+https://huggingface.co/databoks-irfan/twitter-comment-roberta-base-indonesian-smsa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-twitter_paraphrase_embeddings_en.md b/docs/_posts/ahmedlone127/2024-09-04-twitter_paraphrase_embeddings_en.md
new file mode 100644
index 00000000000000..ac04dde6374d90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-twitter_paraphrase_embeddings_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English twitter_paraphrase_embeddings MPNetEmbeddings from mspy
+author: John Snow Labs
+name: twitter_paraphrase_embeddings
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_paraphrase_embeddings` is a English model originally trained by mspy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_paraphrase_embeddings_en_5.5.0_3.0_1725470745421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_paraphrase_embeddings_en_5.5.0_3.0_1725470745421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("twitter_paraphrase_embeddings","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("twitter_paraphrase_embeddings","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_paraphrase_embeddings|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/mspy/twitter-paraphrase-embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_emotion_latest_en.md b/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_emotion_latest_en.md
new file mode 100644
index 00000000000000..98536cd189d3dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_emotion_latest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_large_emotion_latest RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_large_emotion_latest
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_emotion_latest` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_emotion_latest_en_5.5.0_3.0_1725452890223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_emotion_latest_en_5.5.0_3.0_1725452890223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("twitter_roberta_large_emotion_latest","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_large_emotion_latest", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_large_emotion_latest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-large-emotion-latest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_emotion_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_emotion_latest_pipeline_en.md
new file mode 100644
index 00000000000000..18c330415e6478
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_emotion_latest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_large_emotion_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_large_emotion_latest_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_emotion_latest_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_emotion_latest_pipeline_en_5.5.0_3.0_1725452954302.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_emotion_latest_pipeline_en_5.5.0_3.0_1725452954302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_large_emotion_latest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_large_emotion_latest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_large_emotion_latest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-large-emotion-latest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_hate_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_hate_latest_pipeline_en.md
new file mode 100644
index 00000000000000..c17b86826bf33f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-twitter_roberta_large_hate_latest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_large_hate_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_large_hate_latest_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_large_hate_latest_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_hate_latest_pipeline_en_5.5.0_3.0_1725486328608.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_large_hate_latest_pipeline_en_5.5.0_3.0_1725486328608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_large_hate_latest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_large_hate_latest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_large_hate_latest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-large-hate-latest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-twitter_xlm_roberta_base_sentiment_mrredborne_en.md b/docs/_posts/ahmedlone127/2024-09-04-twitter_xlm_roberta_base_sentiment_mrredborne_en.md
new file mode 100644
index 00000000000000..d284d5a0a6334a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-twitter_xlm_roberta_base_sentiment_mrredborne_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_mrredborne XlmRoBertaForSequenceClassification from Mrredborne
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_mrredborne
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_mrredborne` is a English model originally trained by Mrredborne.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_mrredborne_en_5.5.0_3.0_1725411611070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_mrredborne_en_5.5.0_3.0_1725411611070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_mrredborne","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_mrredborne", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_mrredborne|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Mrredborne/twitter-xlm-roberta-base-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-twitter_xlm_roberta_base_sentiment_mrredborne_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-twitter_xlm_roberta_base_sentiment_mrredborne_pipeline_en.md
new file mode 100644
index 00000000000000..f4f065fff45047
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-twitter_xlm_roberta_base_sentiment_mrredborne_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_mrredborne_pipeline pipeline XlmRoBertaForSequenceClassification from Mrredborne
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_mrredborne_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_mrredborne_pipeline` is a English model originally trained by Mrredborne.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_mrredborne_pipeline_en_5.5.0_3.0_1725411663825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_mrredborne_pipeline_en_5.5.0_3.0_1725411663825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_xlm_roberta_base_sentiment_mrredborne_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_xlm_roberta_base_sentiment_mrredborne_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_mrredborne_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Mrredborne/twitter-xlm-roberta-base-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-umberto_fine_tuned_docclass_punjabi_eastern_en.md b/docs/_posts/ahmedlone127/2024-09-04-umberto_fine_tuned_docclass_punjabi_eastern_en.md
new file mode 100644
index 00000000000000..f9af189d68dbb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-umberto_fine_tuned_docclass_punjabi_eastern_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English umberto_fine_tuned_docclass_punjabi_eastern CamemBertForSequenceClassification from colinglab
+author: John Snow Labs
+name: umberto_fine_tuned_docclass_punjabi_eastern
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`umberto_fine_tuned_docclass_punjabi_eastern` is a English model originally trained by colinglab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/umberto_fine_tuned_docclass_punjabi_eastern_en_5.5.0_3.0_1725466412620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/umberto_fine_tuned_docclass_punjabi_eastern_en_5.5.0_3.0_1725466412620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("umberto_fine_tuned_docclass_punjabi_eastern","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("umberto_fine_tuned_docclass_punjabi_eastern", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|umberto_fine_tuned_docclass_punjabi_eastern|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.6 MB|
+
+## References
+
+https://huggingface.co/colinglab/UMBERTO_fine-tuned_DocClass_PA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-unibert_distilbert_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-unibert_distilbert_1_en.md
new file mode 100644
index 00000000000000..0c9df334f4fb78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-unibert_distilbert_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English unibert_distilbert_1 DistilBertForTokenClassification from dbala02
+author: John Snow Labs
+name: unibert_distilbert_1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unibert_distilbert_1` is a English model originally trained by dbala02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unibert_distilbert_1_en_5.5.0_3.0_1725460652870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unibert_distilbert_1_en_5.5.0_3.0_1725460652870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("unibert_distilbert_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("unibert_distilbert_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|unibert_distilbert_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/dbala02/uniBERT.distilBERT.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-unibert_distilbert_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-unibert_distilbert_1_pipeline_en.md
new file mode 100644
index 00000000000000..56bf425beeadbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-unibert_distilbert_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English unibert_distilbert_1_pipeline pipeline DistilBertForTokenClassification from dbala02
+author: John Snow Labs
+name: unibert_distilbert_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unibert_distilbert_1_pipeline` is a English model originally trained by dbala02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unibert_distilbert_1_pipeline_en_5.5.0_3.0_1725460664712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unibert_distilbert_1_pipeline_en_5.5.0_3.0_1725460664712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("unibert_distilbert_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("unibert_distilbert_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|unibert_distilbert_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/dbala02/uniBERT.distilBERT.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch12_en.md b/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch12_en.md
new file mode 100644
index 00000000000000..9e3ccec1032d2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch12_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English uniir_sf_vit_large_patch14_336_epoch12 CLIPForZeroShotClassification from lsr42
+author: John Snow Labs
+name: uniir_sf_vit_large_patch14_336_epoch12
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uniir_sf_vit_large_patch14_336_epoch12` is a English model originally trained by lsr42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uniir_sf_vit_large_patch14_336_epoch12_en_5.5.0_3.0_1725456734358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uniir_sf_vit_large_patch14_336_epoch12_en_5.5.0_3.0_1725456734358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("uniir_sf_vit_large_patch14_336_epoch12","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("uniir_sf_vit_large_patch14_336_epoch12","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uniir_sf_vit_large_patch14_336_epoch12|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/lsr42/uniir-sf-vit-large-patch14-336-epoch12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch12_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch12_pipeline_en.md
new file mode 100644
index 00000000000000..0cc0a5417d8501
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch12_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English uniir_sf_vit_large_patch14_336_epoch12_pipeline pipeline CLIPForZeroShotClassification from lsr42
+author: John Snow Labs
+name: uniir_sf_vit_large_patch14_336_epoch12_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uniir_sf_vit_large_patch14_336_epoch12_pipeline` is a English model originally trained by lsr42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uniir_sf_vit_large_patch14_336_epoch12_pipeline_en_5.5.0_3.0_1725456809721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uniir_sf_vit_large_patch14_336_epoch12_pipeline_en_5.5.0_3.0_1725456809721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uniir_sf_vit_large_patch14_336_epoch12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uniir_sf_vit_large_patch14_336_epoch12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uniir_sf_vit_large_patch14_336_epoch12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/lsr42/uniir-sf-vit-large-patch14-336-epoch12
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch16_en.md b/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch16_en.md
new file mode 100644
index 00000000000000..570ae6c2c3e0d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch16_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English uniir_sf_vit_large_patch14_336_epoch16 CLIPForZeroShotClassification from lsr42
+author: John Snow Labs
+name: uniir_sf_vit_large_patch14_336_epoch16
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uniir_sf_vit_large_patch14_336_epoch16` is a English model originally trained by lsr42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uniir_sf_vit_large_patch14_336_epoch16_en_5.5.0_3.0_1725455888320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uniir_sf_vit_large_patch14_336_epoch16_en_5.5.0_3.0_1725455888320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("uniir_sf_vit_large_patch14_336_epoch16","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("uniir_sf_vit_large_patch14_336_epoch16","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uniir_sf_vit_large_patch14_336_epoch16|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/lsr42/uniir-sf-vit-large-patch14-336-epoch16
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch16_pipeline_en.md
new file mode 100644
index 00000000000000..089d571e8f357c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-uniir_sf_vit_large_patch14_336_epoch16_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English uniir_sf_vit_large_patch14_336_epoch16_pipeline pipeline CLIPForZeroShotClassification from lsr42
+author: John Snow Labs
+name: uniir_sf_vit_large_patch14_336_epoch16_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uniir_sf_vit_large_patch14_336_epoch16_pipeline` is a English model originally trained by lsr42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uniir_sf_vit_large_patch14_336_epoch16_pipeline_en_5.5.0_3.0_1725455963052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uniir_sf_vit_large_patch14_336_epoch16_pipeline_en_5.5.0_3.0_1725455963052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uniir_sf_vit_large_patch14_336_epoch16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uniir_sf_vit_large_patch14_336_epoch16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uniir_sf_vit_large_patch14_336_epoch16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/lsr42/uniir-sf-vit-large-patch14-336-epoch16
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline_uz.md b/docs/_posts/ahmedlone127/2024-09-04-uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline_uz.md
new file mode 100644
index 00000000000000..40a2e546b98cbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline_uz.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Uzbek uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline pipeline RoBertaForQuestionAnswering from med-alex
+author: John Snow Labs
+name: uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline
+date: 2024-09-04
+tags: [uz, open_source, pipeline, onnx]
+task: Question Answering
+language: uz
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline` is a Uzbek model originally trained by med-alex.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline_uz_5.5.0_3.0_1725478894582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline_uz_5.5.0_3.0_1725478894582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline", lang = "uz")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline", lang = "uz")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|uz|
+|Size:|311.9 MB|
+
+## References
+
+https://huggingface.co/med-alex/uzn-roberta-base-ft-qa-tr-mt-to-uzn
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_uz.md b/docs/_posts/ahmedlone127/2024-09-04-uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_uz.md
new file mode 100644
index 00000000000000..cb33aac2510cd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_uz.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Uzbek uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn RoBertaForQuestionAnswering from med-alex
+author: John Snow Labs
+name: uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn
+date: 2024-09-04
+tags: [uz, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: uz
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn` is a Uzbek model originally trained by med-alex.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_uz_5.5.0_3.0_1725478879170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn_uz_5.5.0_3.0_1725478879170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn","uz") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn", "uz")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uzn_roberta_base_ft_qa_turkish_maltese_tonga_tonga_islands_uzn|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|uz|
+|Size:|311.8 MB|
+
+## References
+
+https://huggingface.co/med-alex/uzn-roberta-base-ft-qa-tr-mt-to-uzn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-uztext_3gb_bpe_roberta_pipeline_uz.md b/docs/_posts/ahmedlone127/2024-09-04-uztext_3gb_bpe_roberta_pipeline_uz.md
new file mode 100644
index 00000000000000..0799429322e057
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-uztext_3gb_bpe_roberta_pipeline_uz.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Uzbek uztext_3gb_bpe_roberta_pipeline pipeline RoBertaEmbeddings from rifkat
+author: John Snow Labs
+name: uztext_3gb_bpe_roberta_pipeline
+date: 2024-09-04
+tags: [uz, open_source, pipeline, onnx]
+task: Embeddings
+language: uz
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uztext_3gb_bpe_roberta_pipeline` is a Uzbek model originally trained by rifkat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uztext_3gb_bpe_roberta_pipeline_uz_5.5.0_3.0_1725412775152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uztext_3gb_bpe_roberta_pipeline_uz_5.5.0_3.0_1725412775152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uztext_3gb_bpe_roberta_pipeline", lang = "uz")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uztext_3gb_bpe_roberta_pipeline", lang = "uz")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uztext_3gb_bpe_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|uz|
+|Size:|311.9 MB|
+
+## References
+
+https://huggingface.co/rifkat/uztext-3Gb-BPE-Roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-uztext_3gb_bpe_roberta_uz.md b/docs/_posts/ahmedlone127/2024-09-04-uztext_3gb_bpe_roberta_uz.md
new file mode 100644
index 00000000000000..eb62e464196d55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-uztext_3gb_bpe_roberta_uz.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Uzbek uztext_3gb_bpe_roberta RoBertaEmbeddings from rifkat
+author: John Snow Labs
+name: uztext_3gb_bpe_roberta
+date: 2024-09-04
+tags: [uz, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: uz
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uztext_3gb_bpe_roberta` is a Uzbek model originally trained by rifkat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uztext_3gb_bpe_roberta_uz_5.5.0_3.0_1725412757708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uztext_3gb_bpe_roberta_uz_5.5.0_3.0_1725412757708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("uztext_3gb_bpe_roberta","uz") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("uztext_3gb_bpe_roberta","uz") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uztext_3gb_bpe_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|uz|
+|Size:|311.8 MB|
+
+## References
+
+https://huggingface.co/rifkat/uztext-3Gb-BPE-Roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-v39_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-v39_pipeline_en.md
new file mode 100644
index 00000000000000..c36a4d3a90d47b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-v39_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English v39_pipeline pipeline AlbertForTokenClassification from LogicCrafters
+author: John Snow Labs
+name: v39_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`v39_pipeline` is a English model originally trained by LogicCrafters.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/v39_pipeline_en_5.5.0_3.0_1725487055053.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/v39_pipeline_en_5.5.0_3.0_1725487055053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("v39_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("v39_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|v39_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|771.1 MB|
+
+## References
+
+https://huggingface.co/LogicCrafters/v39
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-v51_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-v51_pipeline_en.md
new file mode 100644
index 00000000000000..9714c294b8ef4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-v51_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English v51_pipeline pipeline AlbertForTokenClassification from LogicCrafters
+author: John Snow Labs
+name: v51_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`v51_pipeline` is a English model originally trained by LogicCrafters.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/v51_pipeline_en_5.5.0_3.0_1725487294365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/v51_pipeline_en_5.5.0_3.0_1725487294365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("v51_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("v51_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|v51_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|393.2 MB|
+
+## References
+
+https://huggingface.co/LogicCrafters/v51
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-vir_pat_qa_en.md b/docs/_posts/ahmedlone127/2024-09-04-vir_pat_qa_en.md
new file mode 100644
index 00000000000000..4357e3f946b7ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-vir_pat_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vir_pat_qa RoBertaForQuestionAnswering from Mikelium5
+author: John Snow Labs
+name: vir_pat_qa
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vir_pat_qa` is a English model originally trained by Mikelium5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vir_pat_qa_en_5.5.0_3.0_1725483431929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vir_pat_qa_en_5.5.0_3.0_1725483431929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("vir_pat_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("vir_pat_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vir_pat_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|459.9 MB|
+
+## References
+
+https://huggingface.co/Mikelium5/VIR-PAT-QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-vispell_small_v1_vi.md b/docs/_posts/ahmedlone127/2024-09-04-vispell_small_v1_vi.md
new file mode 100644
index 00000000000000..b172244eb1b85e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-vispell_small_v1_vi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Vietnamese vispell_small_v1 MarianTransformer from ademax
+author: John Snow Labs
+name: vispell_small_v1
+date: 2024-09-04
+tags: [vi, open_source, onnx, translation, marian]
+task: Translation
+language: vi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vispell_small_v1` is a Vietnamese model originally trained by ademax.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vispell_small_v1_vi_5.5.0_3.0_1725493742011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vispell_small_v1_vi_5.5.0_3.0_1725493742011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("vispell_small_v1","vi") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("vispell_small_v1","vi") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vispell_small_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|vi|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ademax/vispell-small-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-wandss_bert_en.md b/docs/_posts/ahmedlone127/2024-09-04-wandss_bert_en.md
new file mode 100644
index 00000000000000..59c323b374847b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-wandss_bert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English wandss_bert MPNetEmbeddings from tubyneto
+author: John Snow Labs
+name: wandss_bert
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wandss_bert` is a English model originally trained by tubyneto.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wandss_bert_en_5.5.0_3.0_1725470518152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wandss_bert_en_5.5.0_3.0_1725470518152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("wandss_bert","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("wandss_bert","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wandss_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/tubyneto/wandss-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-wandss_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-wandss_bert_pipeline_en.md
new file mode 100644
index 00000000000000..76126658a1a37b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-wandss_bert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English wandss_bert_pipeline pipeline MPNetEmbeddings from tubyneto
+author: John Snow Labs
+name: wandss_bert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wandss_bert_pipeline` is a English model originally trained by tubyneto.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wandss_bert_pipeline_en_5.5.0_3.0_1725470539272.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wandss_bert_pipeline_en_5.5.0_3.0_1725470539272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("wandss_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("wandss_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wandss_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/tubyneto/wandss-bert
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-week5_eng_distilbert_base_multilingual_cased_finetuned_xx.md b/docs/_posts/ahmedlone127/2024-09-04-week5_eng_distilbert_base_multilingual_cased_finetuned_xx.md
new file mode 100644
index 00000000000000..61eb983fdacc60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-week5_eng_distilbert_base_multilingual_cased_finetuned_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual week5_eng_distilbert_base_multilingual_cased_finetuned DistilBertForTokenClassification from ensw
+author: John Snow Labs
+name: week5_eng_distilbert_base_multilingual_cased_finetuned
+date: 2024-09-04
+tags: [xx, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`week5_eng_distilbert_base_multilingual_cased_finetuned` is a Multilingual model originally trained by ensw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/week5_eng_distilbert_base_multilingual_cased_finetuned_xx_5.5.0_3.0_1725448459926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/week5_eng_distilbert_base_multilingual_cased_finetuned_xx_5.5.0_3.0_1725448459926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("week5_eng_distilbert_base_multilingual_cased_finetuned","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("week5_eng_distilbert_base_multilingual_cased_finetuned", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|week5_eng_distilbert_base_multilingual_cased_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/ensw/week5-eng-distilbert-base-multilingual-cased-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_asr_atc_v4_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_asr_atc_v4_en.md
new file mode 100644
index 00000000000000..86e344184cb2db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_asr_atc_v4_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_asr_atc_v4 WhisperForCTC from AshtonLKY
+author: John Snow Labs
+name: whisper_asr_atc_v4
+date: 2024-09-04
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_asr_atc_v4` is a English model originally trained by AshtonLKY.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_asr_atc_v4_en_5.5.0_3.0_1725427773461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_asr_atc_v4_en_5.5.0_3.0_1725427773461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_asr_atc_v4","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_asr_atc_v4", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_asr_atc_v4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/AshtonLKY/Whisper_ASR_ATC_v4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_asr_atc_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_asr_atc_v4_pipeline_en.md
new file mode 100644
index 00000000000000..3a99ded4b5a3ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_asr_atc_v4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_asr_atc_v4_pipeline pipeline WhisperForCTC from AshtonLKY
+author: John Snow Labs
+name: whisper_asr_atc_v4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_asr_atc_v4_pipeline` is a English model originally trained by AshtonLKY.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_asr_atc_v4_pipeline_en_5.5.0_3.0_1725427863575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_asr_atc_v4_pipeline_en_5.5.0_3.0_1725427863575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_asr_atc_v4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_asr_atc_v4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_asr_atc_v4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/AshtonLKY/Whisper_ASR_ATC_v4
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_base_vietnamese_finetuned_pipeline_vi.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_base_vietnamese_finetuned_pipeline_vi.md
new file mode 100644
index 00000000000000..0e2f4d72b451c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_base_vietnamese_finetuned_pipeline_vi.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Vietnamese whisper_base_vietnamese_finetuned_pipeline pipeline WhisperForCTC from hkab
+author: John Snow Labs
+name: whisper_base_vietnamese_finetuned_pipeline
+date: 2024-09-04
+tags: [vi, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: vi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_vietnamese_finetuned_pipeline` is a Vietnamese model originally trained by hkab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_vietnamese_finetuned_pipeline_vi_5.5.0_3.0_1725428780487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_vietnamese_finetuned_pipeline_vi_5.5.0_3.0_1725428780487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_base_vietnamese_finetuned_pipeline", lang = "vi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_base_vietnamese_finetuned_pipeline", lang = "vi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_vietnamese_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|vi|
+|Size:|644.8 MB|
+
+## References
+
+https://huggingface.co/hkab/whisper-base-vietnamese-finetuned
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_base_vietnamese_finetuned_vi.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_base_vietnamese_finetuned_vi.md
new file mode 100644
index 00000000000000..4388763726cffc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_base_vietnamese_finetuned_vi.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Vietnamese whisper_base_vietnamese_finetuned WhisperForCTC from hkab
+author: John Snow Labs
+name: whisper_base_vietnamese_finetuned
+date: 2024-09-04
+tags: [vi, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: vi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_vietnamese_finetuned` is a Vietnamese model originally trained by hkab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_vietnamese_finetuned_vi_5.5.0_3.0_1725428746572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_vietnamese_finetuned_vi_5.5.0_3.0_1725428746572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_base_vietnamese_finetuned","vi") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_base_vietnamese_finetuned", "vi")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_vietnamese_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|vi|
+|Size:|644.8 MB|
+
+## References
+
+https://huggingface.co/hkab/whisper-base-vietnamese-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_cantonese_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_cantonese_en.md
new file mode 100644
index 00000000000000..21a6954787f570
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_cantonese_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_cantonese WhisperForCTC from WayneLinn
+author: John Snow Labs
+name: whisper_cantonese
+date: 2024-09-04
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_cantonese` is a English model originally trained by WayneLinn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_cantonese_en_5.5.0_3.0_1725431316615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_cantonese_en_5.5.0_3.0_1725431316615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_cantonese","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_cantonese", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_cantonese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/WayneLinn/Whisper-Cantonese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_cantonese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_cantonese_pipeline_en.md
new file mode 100644
index 00000000000000..10f22f62eb571d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_cantonese_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_cantonese_pipeline pipeline WhisperForCTC from WayneLinn
+author: John Snow Labs
+name: whisper_cantonese_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_cantonese_pipeline` is a English model originally trained by WayneLinn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_cantonese_pipeline_en_5.5.0_3.0_1725431398381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_cantonese_pipeline_en_5.5.0_3.0_1725431398381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_cantonese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_cantonese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_cantonese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/WayneLinn/Whisper-Cantonese
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_enhanced_malayalam_hi.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_enhanced_malayalam_hi.md
new file mode 100644
index 00000000000000..f6a0b0e8488e35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_enhanced_malayalam_hi.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Hindi whisper_enhanced_malayalam WhisperForCTC from nurzhanit
+author: John Snow Labs
+name: whisper_enhanced_malayalam
+date: 2024-09-04
+tags: [hi, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_enhanced_malayalam` is a Hindi model originally trained by nurzhanit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_enhanced_malayalam_hi_5.5.0_3.0_1725426831982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_enhanced_malayalam_hi_5.5.0_3.0_1725426831982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_enhanced_malayalam","hi") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_enhanced_malayalam", "hi")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_enhanced_malayalam|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|hi|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/nurzhanit/whisper-enhanced-ml
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_enhanced_malayalam_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_enhanced_malayalam_pipeline_hi.md
new file mode 100644
index 00000000000000..80ac57cef73e31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_enhanced_malayalam_pipeline_hi.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hindi whisper_enhanced_malayalam_pipeline pipeline WhisperForCTC from nurzhanit
+author: John Snow Labs
+name: whisper_enhanced_malayalam_pipeline
+date: 2024-09-04
+tags: [hi, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_enhanced_malayalam_pipeline` is a Hindi model originally trained by nurzhanit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_enhanced_malayalam_pipeline_hi_5.5.0_3.0_1725426918379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_enhanced_malayalam_pipeline_hi_5.5.0_3.0_1725426918379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_enhanced_malayalam_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_enhanced_malayalam_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_enhanced_malayalam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/nurzhanit/whisper-enhanced-ml
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_hindi_small_vasista22_hi.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_hindi_small_vasista22_hi.md
new file mode 100644
index 00000000000000..cd06c1c95d4b77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_hindi_small_vasista22_hi.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Hindi whisper_hindi_small_vasista22 WhisperForCTC from vasista22
+author: John Snow Labs
+name: whisper_hindi_small_vasista22
+date: 2024-09-04
+tags: [hi, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_hindi_small_vasista22` is a Hindi model originally trained by vasista22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_hindi_small_vasista22_hi_5.5.0_3.0_1725427587031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_hindi_small_vasista22_hi_5.5.0_3.0_1725427587031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_hindi_small_vasista22","hi") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_hindi_small_vasista22", "hi")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_hindi_small_vasista22|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|hi|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/vasista22/whisper-hindi-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_hindi_small_vasista22_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_hindi_small_vasista22_pipeline_hi.md
new file mode 100644
index 00000000000000..de4b7c093acc45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_hindi_small_vasista22_pipeline_hi.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hindi whisper_hindi_small_vasista22_pipeline pipeline WhisperForCTC from vasista22
+author: John Snow Labs
+name: whisper_hindi_small_vasista22_pipeline
+date: 2024-09-04
+tags: [hi, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_hindi_small_vasista22_pipeline` is a Hindi model originally trained by vasista22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_hindi_small_vasista22_pipeline_hi_5.5.0_3.0_1725427673430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_hindi_small_vasista22_pipeline_hi_5.5.0_3.0_1725427673430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_hindi_small_vasista22_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_hindi_small_vasista22_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_hindi_small_vasista22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/vasista22/whisper-hindi-small
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_arabic_chuvash_11_ar.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_arabic_chuvash_11_ar.md
new file mode 100644
index 00000000000000..2c0b5543d50fc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_arabic_chuvash_11_ar.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Arabic whisper_small_arabic_chuvash_11 WhisperForCTC from mohammed
+author: John Snow Labs
+name: whisper_small_arabic_chuvash_11
+date: 2024-09-04
+tags: [ar, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_arabic_chuvash_11` is a Arabic model originally trained by mohammed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_chuvash_11_ar_5.5.0_3.0_1725431139114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_chuvash_11_ar_5.5.0_3.0_1725431139114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_arabic_chuvash_11","ar") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_arabic_chuvash_11", "ar")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_arabic_chuvash_11|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/mohammed/whisper-small-arabic-cv-11
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_arabic_chuvash_11_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_arabic_chuvash_11_pipeline_ar.md
new file mode 100644
index 00000000000000..9ef348a171511f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_arabic_chuvash_11_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic whisper_small_arabic_chuvash_11_pipeline pipeline WhisperForCTC from mohammed
+author: John Snow Labs
+name: whisper_small_arabic_chuvash_11_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_arabic_chuvash_11_pipeline` is a Arabic model originally trained by mohammed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_chuvash_11_pipeline_ar_5.5.0_3.0_1725431228403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_chuvash_11_pipeline_ar_5.5.0_3.0_1725431228403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_arabic_chuvash_11_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_arabic_chuvash_11_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_arabic_chuvash_11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/mohammed/whisper-small-arabic-cv-11
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_chinese_jun_han_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_chinese_jun_han_pipeline_zh.md
new file mode 100644
index 00000000000000..857880553c4702
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_chinese_jun_han_pipeline_zh.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Chinese whisper_small_chinese_jun_han_pipeline pipeline WhisperForCTC from jun-han
+author: John Snow Labs
+name: whisper_small_chinese_jun_han_pipeline
+date: 2024-09-04
+tags: [zh, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_chinese_jun_han_pipeline` is a Chinese model originally trained by jun-han.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_jun_han_pipeline_zh_5.5.0_3.0_1725430680551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_jun_han_pipeline_zh_5.5.0_3.0_1725430680551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_chinese_jun_han_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_chinese_jun_han_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_chinese_jun_han_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/jun-han/whisper-small-zh
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_chinese_jun_han_zh.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_chinese_jun_han_zh.md
new file mode 100644
index 00000000000000..91901a145885b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_chinese_jun_han_zh.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Chinese whisper_small_chinese_jun_han WhisperForCTC from jun-han
+author: John Snow Labs
+name: whisper_small_chinese_jun_han
+date: 2024-09-04
+tags: [zh, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_chinese_jun_han` is a Chinese model originally trained by jun-han.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_jun_han_zh_5.5.0_3.0_1725430588594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_jun_han_zh_5.5.0_3.0_1725430588594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_chinese_jun_han","zh") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_chinese_jun_han", "zh")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_chinese_jun_han|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|zh|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/jun-han/whisper-small-zh
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_ctejarat_fa.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_ctejarat_fa.md
new file mode 100644
index 00000000000000..9c196f517f6f6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_ctejarat_fa.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Persian whisper_small_ctejarat WhisperForCTC from makhataei
+author: John Snow Labs
+name: whisper_small_ctejarat
+date: 2024-09-04
+tags: [fa, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_ctejarat` is a Persian model originally trained by makhataei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_ctejarat_fa_5.5.0_3.0_1725426324736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_ctejarat_fa_5.5.0_3.0_1725426324736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_ctejarat","fa") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_ctejarat", "fa")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_ctejarat|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|fa|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/makhataei/Whisper-Small-Ctejarat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_ctejarat_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_ctejarat_pipeline_fa.md
new file mode 100644
index 00000000000000..0c3d74cc7edb11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_ctejarat_pipeline_fa.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Persian whisper_small_ctejarat_pipeline pipeline WhisperForCTC from makhataei
+author: John Snow Labs
+name: whisper_small_ctejarat_pipeline
+date: 2024-09-04
+tags: [fa, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_ctejarat_pipeline` is a Persian model originally trained by makhataei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_ctejarat_pipeline_fa_5.5.0_3.0_1725426413341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_ctejarat_pipeline_fa_5.5.0_3.0_1725426413341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_ctejarat_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_ctejarat_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_ctejarat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/makhataei/Whisper-Small-Ctejarat
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_cv18_hungarian_cleaned_hu.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_cv18_hungarian_cleaned_hu.md
new file mode 100644
index 00000000000000..504d32f565bbf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_cv18_hungarian_cleaned_hu.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Hungarian whisper_small_cv18_hungarian_cleaned WhisperForCTC from sarpba
+author: John Snow Labs
+name: whisper_small_cv18_hungarian_cleaned
+date: 2024-09-04
+tags: [hu, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: hu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_cv18_hungarian_cleaned` is a Hungarian model originally trained by sarpba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_cv18_hungarian_cleaned_hu_5.5.0_3.0_1725425719489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_cv18_hungarian_cleaned_hu_5.5.0_3.0_1725425719489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_cv18_hungarian_cleaned","hu") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_cv18_hungarian_cleaned", "hu")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_cv18_hungarian_cleaned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|hu|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/sarpba/whisper-small-cv18-hu-cleaned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_cv18_hungarian_cleaned_pipeline_hu.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_cv18_hungarian_cleaned_pipeline_hu.md
new file mode 100644
index 00000000000000..e989b4a046a945
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_cv18_hungarian_cleaned_pipeline_hu.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hungarian whisper_small_cv18_hungarian_cleaned_pipeline pipeline WhisperForCTC from sarpba
+author: John Snow Labs
+name: whisper_small_cv18_hungarian_cleaned_pipeline
+date: 2024-09-04
+tags: [hu, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: hu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_cv18_hungarian_cleaned_pipeline` is a Hungarian model originally trained by sarpba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_cv18_hungarian_cleaned_pipeline_hu_5.5.0_3.0_1725425805328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_cv18_hungarian_cleaned_pipeline_hu_5.5.0_3.0_1725425805328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_cv18_hungarian_cleaned_pipeline", lang = "hu")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_cv18_hungarian_cleaned_pipeline", lang = "hu")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_cv18_hungarian_cleaned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hu|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/sarpba/whisper-small-cv18-hu-cleaned
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_finetune_taiwanese_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_finetune_taiwanese_en.md
new file mode 100644
index 00000000000000..2fde35852f7608
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_finetune_taiwanese_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_small_finetune_taiwanese WhisperForCTC from Jackyhsien
+author: John Snow Labs
+name: whisper_small_finetune_taiwanese
+date: 2024-09-04
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_finetune_taiwanese` is a English model originally trained by Jackyhsien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_finetune_taiwanese_en_5.5.0_3.0_1725430111357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_finetune_taiwanese_en_5.5.0_3.0_1725430111357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_finetune_taiwanese","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_finetune_taiwanese", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_finetune_taiwanese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Jackyhsien/whisper-small-finetune-taiwanese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_hre4_4_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_hre4_4_en.md
new file mode 100644
index 00000000000000..7ec815b2147700
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_hre4_4_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_small_hre4_4 WhisperForCTC from ntviet
+author: John Snow Labs
+name: whisper_small_hre4_4
+date: 2024-09-04
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_hre4_4` is a English model originally trained by ntviet.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_hre4_4_en_5.5.0_3.0_1725430950756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_hre4_4_en_5.5.0_3.0_1725430950756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_hre4_4","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_hre4_4", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_hre4_4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/ntviet/whisper-small-hre4.4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_hre4_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_hre4_4_pipeline_en.md
new file mode 100644
index 00000000000000..6a90e7bbe31cd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_hre4_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_small_hre4_4_pipeline pipeline WhisperForCTC from ntviet
+author: John Snow Labs
+name: whisper_small_hre4_4_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_hre4_4_pipeline` is a English model originally trained by ntviet.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_hre4_4_pipeline_en_5.5.0_3.0_1725431047990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_hre4_4_pipeline_en_5.5.0_3.0_1725431047990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_hre4_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_hre4_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_hre4_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/ntviet/whisper-small-hre4.4
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_singlish_122k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_singlish_122k_pipeline_en.md
new file mode 100644
index 00000000000000..10f66836ca8a17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_singlish_122k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_small_singlish_122k_pipeline pipeline WhisperForCTC from jensenlwt
+author: John Snow Labs
+name: whisper_small_singlish_122k_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_singlish_122k_pipeline` is a English model originally trained by jensenlwt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_singlish_122k_pipeline_en_5.5.0_3.0_1725430331030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_singlish_122k_pipeline_en_5.5.0_3.0_1725430331030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_singlish_122k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_singlish_122k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_singlish_122k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/jensenlwt/whisper-small-singlish-122k
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_spanish_1k_steps_es.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_spanish_1k_steps_es.md
new file mode 100644
index 00000000000000..a1e0045b6f31cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_spanish_1k_steps_es.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Castilian, Spanish whisper_small_spanish_1k_steps WhisperForCTC from sanchit-gandhi
+author: John Snow Labs
+name: whisper_small_spanish_1k_steps
+date: 2024-09-04
+tags: [es, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_spanish_1k_steps` is a Castilian, Spanish model originally trained by sanchit-gandhi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_spanish_1k_steps_es_5.5.0_3.0_1725427410631.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_spanish_1k_steps_es_5.5.0_3.0_1725427410631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_spanish_1k_steps","es") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_spanish_1k_steps", "es")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_spanish_1k_steps|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|es|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/sanchit-gandhi/whisper-small-es-1k-steps
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_small_spanish_1k_steps_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_spanish_1k_steps_pipeline_es.md
new file mode 100644
index 00000000000000..41ead3e45f257c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_small_spanish_1k_steps_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish whisper_small_spanish_1k_steps_pipeline pipeline WhisperForCTC from sanchit-gandhi
+author: John Snow Labs
+name: whisper_small_spanish_1k_steps_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_spanish_1k_steps_pipeline` is a Castilian, Spanish model originally trained by sanchit-gandhi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_spanish_1k_steps_pipeline_es_5.5.0_3.0_1725427509538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_spanish_1k_steps_pipeline_es_5.5.0_3.0_1725427509538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_small_spanish_1k_steps_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_spanish_1k_steps_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_spanish_1k_steps_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/sanchit-gandhi/whisper-small-es-1k-steps
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_sudanese_dialect_small_ar.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_sudanese_dialect_small_ar.md
new file mode 100644
index 00000000000000..51a8c17d90e1b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_sudanese_dialect_small_ar.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Arabic whisper_sudanese_dialect_small WhisperForCTC from AymanMansour
+author: John Snow Labs
+name: whisper_sudanese_dialect_small
+date: 2024-09-04
+tags: [ar, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_sudanese_dialect_small` is a Arabic model originally trained by AymanMansour.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_sudanese_dialect_small_ar_5.5.0_3.0_1725426618060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_sudanese_dialect_small_ar_5.5.0_3.0_1725426618060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_sudanese_dialect_small","ar") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_sudanese_dialect_small", "ar")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_sudanese_dialect_small|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/AymanMansour/Whisper-Sudanese-Dialect-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_sudanese_dialect_small_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_sudanese_dialect_small_pipeline_ar.md
new file mode 100644
index 00000000000000..40844ab9b6fac0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_sudanese_dialect_small_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic whisper_sudanese_dialect_small_pipeline pipeline WhisperForCTC from AymanMansour
+author: John Snow Labs
+name: whisper_sudanese_dialect_small_pipeline
+date: 2024-09-04
+tags: [ar, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_sudanese_dialect_small_pipeline` is a Arabic model originally trained by AymanMansour.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_sudanese_dialect_small_pipeline_ar_5.5.0_3.0_1725426732197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_sudanese_dialect_small_pipeline_ar_5.5.0_3.0_1725426732197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_sudanese_dialect_small_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_sudanese_dialect_small_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_sudanese_dialect_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/AymanMansour/Whisper-Sudanese-Dialect-small
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_tamil_small_pipeline_ta.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_tamil_small_pipeline_ta.md
new file mode 100644
index 00000000000000..565d6d19b8e991
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_tamil_small_pipeline_ta.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Tamil whisper_tamil_small_pipeline pipeline WhisperForCTC from vasista22
+author: John Snow Labs
+name: whisper_tamil_small_pipeline
+date: 2024-09-04
+tags: [ta, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ta
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tamil_small_pipeline` is a Tamil model originally trained by vasista22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tamil_small_pipeline_ta_5.5.0_3.0_1725431039597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tamil_small_pipeline_ta_5.5.0_3.0_1725431039597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tamil_small_pipeline", lang = "ta")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tamil_small_pipeline", lang = "ta")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tamil_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ta|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/vasista22/whisper-tamil-small
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_tamil_small_ta.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_tamil_small_ta.md
new file mode 100644
index 00000000000000..4e2cc9be213f14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_tamil_small_ta.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Tamil whisper_tamil_small WhisperForCTC from vasista22
+author: John Snow Labs
+name: whisper_tamil_small
+date: 2024-09-04
+tags: [ta, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ta
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tamil_small` is a Tamil model originally trained by vasista22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tamil_small_ta_5.5.0_3.0_1725430941323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tamil_small_ta_5.5.0_3.0_1725430941323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tamil_small","ta") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tamil_small", "ta")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tamil_small|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ta|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/vasista22/whisper-tamil-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_cv16_hungarian_v3_hu.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_cv16_hungarian_v3_hu.md
new file mode 100644
index 00000000000000..57b7c5098cef06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_cv16_hungarian_v3_hu.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Hungarian whisper_tiny_cv16_hungarian_v3 WhisperForCTC from Hungarians
+author: John Snow Labs
+name: whisper_tiny_cv16_hungarian_v3
+date: 2024-09-04
+tags: [hu, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: hu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_cv16_hungarian_v3` is a Hungarian model originally trained by Hungarians.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_cv16_hungarian_v3_hu_5.5.0_3.0_1725427389916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_cv16_hungarian_v3_hu_5.5.0_3.0_1725427389916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_cv16_hungarian_v3","hu") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_cv16_hungarian_v3", "hu")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_cv16_hungarian_v3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|hu|
+|Size:|388.3 MB|
+
+## References
+
+https://huggingface.co/Hungarians/whisper-tiny-cv16-hu-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_cv16_hungarian_v3_pipeline_hu.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_cv16_hungarian_v3_pipeline_hu.md
new file mode 100644
index 00000000000000..7550a514cb7b5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_cv16_hungarian_v3_pipeline_hu.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hungarian whisper_tiny_cv16_hungarian_v3_pipeline pipeline WhisperForCTC from Hungarians
+author: John Snow Labs
+name: whisper_tiny_cv16_hungarian_v3_pipeline
+date: 2024-09-04
+tags: [hu, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: hu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_cv16_hungarian_v3_pipeline` is a Hungarian model originally trained by Hungarians.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_cv16_hungarian_v3_pipeline_hu_5.5.0_3.0_1725427411124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_cv16_hungarian_v3_pipeline_hu_5.5.0_3.0_1725427411124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tiny_cv16_hungarian_v3_pipeline", lang = "hu")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_cv16_hungarian_v3_pipeline", lang = "hu")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_cv16_hungarian_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hu|
+|Size:|388.3 MB|
+
+## References
+
+https://huggingface.co/Hungarians/whisper-tiny-cv16-hu-v3
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_english_tyocre_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_english_tyocre_pipeline_en.md
new file mode 100644
index 00000000000000..03055b5c486610
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_english_tyocre_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_tiny_english_tyocre_pipeline pipeline WhisperForCTC from TyoCre
+author: John Snow Labs
+name: whisper_tiny_english_tyocre_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_english_tyocre_pipeline` is a English model originally trained by TyoCre.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_english_tyocre_pipeline_en_5.5.0_3.0_1725425432385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_english_tyocre_pipeline_en_5.5.0_3.0_1725425432385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_tiny_english_tyocre_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_english_tyocre_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_english_tyocre_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|389.9 MB|
+
+## References
+
+https://huggingface.co/TyoCre/whisper-tiny-english
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_finetune_pooya_fallah_en.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_finetune_pooya_fallah_en.md
new file mode 100644
index 00000000000000..9236e88ee50bab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_tiny_finetune_pooya_fallah_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_tiny_finetune_pooya_fallah WhisperForCTC from Pooya-Fallah
+author: John Snow Labs
+name: whisper_tiny_finetune_pooya_fallah
+date: 2024-09-04
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_finetune_pooya_fallah` is a English model originally trained by Pooya-Fallah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_finetune_pooya_fallah_en_5.5.0_3.0_1725430757968.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_finetune_pooya_fallah_en_5.5.0_3.0_1725430757968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_finetune_pooya_fallah","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_finetune_pooya_fallah", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_finetune_pooya_fallah|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|393.9 MB|
+
+## References
+
+https://huggingface.co/Pooya-Fallah/whisper-tiny-finetune
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_uzbek_pipeline_uz.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_uzbek_pipeline_uz.md
new file mode 100644
index 00000000000000..6c0798e504a370
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_uzbek_pipeline_uz.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Uzbek whisper_uzbek_pipeline pipeline WhisperForCTC from Makhmud
+author: John Snow Labs
+name: whisper_uzbek_pipeline
+date: 2024-09-04
+tags: [uz, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: uz
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_uzbek_pipeline` is a Uzbek model originally trained by Makhmud.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_uzbek_pipeline_uz_5.5.0_3.0_1725430862352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_uzbek_pipeline_uz_5.5.0_3.0_1725430862352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("whisper_uzbek_pipeline", lang = "uz")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_uzbek_pipeline", lang = "uz")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_uzbek_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|uz|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Makhmud/whisper-uzbek
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-whisper_uzbek_uz.md b/docs/_posts/ahmedlone127/2024-09-04-whisper_uzbek_uz.md
new file mode 100644
index 00000000000000..9ee5dd1aebd16d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-whisper_uzbek_uz.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Uzbek whisper_uzbek WhisperForCTC from Makhmud
+author: John Snow Labs
+name: whisper_uzbek
+date: 2024-09-04
+tags: [uz, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: uz
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_uzbek` is a Uzbek model originally trained by Makhmud.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_uzbek_uz_5.5.0_3.0_1725430770768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_uzbek_uz_5.5.0_3.0_1725430770768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_uzbek","uz") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_uzbek", "uz")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_uzbek|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|uz|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Makhmud/whisper-uzbek
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_r_galen_pharmaconer_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_r_galen_pharmaconer_pipeline_es.md
new file mode 100644
index 00000000000000..0a81ea2c2f548f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_r_galen_pharmaconer_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish xlm_r_galen_pharmaconer_pipeline pipeline XlmRoBertaForTokenClassification from IIC
+author: John Snow Labs
+name: xlm_r_galen_pharmaconer_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_galen_pharmaconer_pipeline` is a Castilian, Spanish model originally trained by IIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_galen_pharmaconer_pipeline_es_5.5.0_3.0_1725424320729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_galen_pharmaconer_pipeline_es_5.5.0_3.0_1725424320729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_r_galen_pharmaconer_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_galen_pharmaconer_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_galen_pharmaconer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/IIC/XLM_R_Galen-pharmaconer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_r_with_transliteration_average_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_r_with_transliteration_average_en.md
new file mode 100644
index 00000000000000..d71e531c743aae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_r_with_transliteration_average_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_r_with_transliteration_average XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: xlm_r_with_transliteration_average
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_with_transliteration_average` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_with_transliteration_average_en_5.5.0_3.0_1725417723514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_with_transliteration_average_en_5.5.0_3.0_1725417723514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_r_with_transliteration_average","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_r_with_transliteration_average","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_with_transliteration_average|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|850.0 MB|
+
+## References
+
+https://huggingface.co/yihongLiu/xlm-r-with-transliteration-average
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_arlama_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_arlama_en.md
new file mode 100644
index 00000000000000..b69fed418eed29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_arlama_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_arlama XlmRoBertaEmbeddings from AfnanTS
+author: John Snow Labs
+name: xlm_roberta_base_arlama
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_arlama` is a English model originally trained by AfnanTS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_arlama_en_5.5.0_3.0_1725417164761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_arlama_en_5.5.0_3.0_1725417164761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_arlama","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_arlama","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_arlama|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/AfnanTS/xlm-roberta-base_ArLAMA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_arlama_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_arlama_pipeline_en.md
new file mode 100644
index 00000000000000..ec616599060967
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_arlama_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_arlama_pipeline pipeline XlmRoBertaEmbeddings from AfnanTS
+author: John Snow Labs
+name: xlm_roberta_base_arlama_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_arlama_pipeline` is a English model originally trained by AfnanTS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_arlama_pipeline_en_5.5.0_3.0_1725417219327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_arlama_pipeline_en_5.5.0_3.0_1725417219327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_arlama_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_arlama_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_arlama_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/AfnanTS/xlm-roberta-base_ArLAMA
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline_en.md
new file mode 100644
index 00000000000000..3aaf8d3759d67f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline_en_5.5.0_3.0_1725411411732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline_en_5.5.0_3.0_1725411411732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_balance_mixed_aug_replace_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|798.9 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Balance_Mixed-aug_replace_BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_amharic_pipeline_am.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_amharic_pipeline_am.md
new file mode 100644
index 00000000000000..53967c0241682b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_amharic_pipeline_am.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Amharic xlm_roberta_base_finetuned_amharic_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_amharic_pipeline
+date: 2024-09-04
+tags: [am, open_source, pipeline, onnx]
+task: Embeddings
+language: am
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_amharic_pipeline` is a Amharic model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_amharic_pipeline_am_5.5.0_3.0_1725416891066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_amharic_pipeline_am_5.5.0_3.0_1725416891066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_amharic_pipeline", lang = "am")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_amharic_pipeline", lang = "am")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_amharic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|am|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-amharic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_en.md
new file mode 100644
index 00000000000000..c5616c3aba3689
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2 XlmRoBertaForQuestionAnswering from jluckyboyj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2` is a English model originally trained by jluckyboyj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_en_5.5.0_3.0_1725482853315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_en_5.5.0_3.0_1725482853315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|853.1 MB|
+
+## References
+
+https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-augument-visquad2-15-3-2023-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline_en.md
new file mode 100644
index 00000000000000..1a352f78e41f46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline pipeline XlmRoBertaForQuestionAnswering from jluckyboyj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline` is a English model originally trained by jluckyboyj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline_en_5.5.0_3.0_1725482916515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline_en_5.5.0_3.0_1725482916515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.1 MB|
+
+## References
+
+https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-augument-visquad2-15-3-2023-2
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_marc_english_d4niel92_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_marc_english_d4niel92_en.md
new file mode 100644
index 00000000000000..68951bc1469b3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_marc_english_d4niel92_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_english_d4niel92 XlmRoBertaForSequenceClassification from d4niel92
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_english_d4niel92
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_d4niel92` is a English model originally trained by d4niel92.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_d4niel92_en_5.5.0_3.0_1725410828698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_d4niel92_en_5.5.0_3.0_1725410828698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_english_d4niel92","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_english_d4niel92", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_english_d4niel92|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|833.5 MB|
+
+## References
+
+https://huggingface.co/d4niel92/xlm-roberta-base-finetuned-marc-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline_en.md
new file mode 100644
index 00000000000000..909486d310655a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline pipeline XlmRoBertaForSequenceClassification from d4niel92
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline` is a English model originally trained by d4niel92.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline_en_5.5.0_3.0_1725410922466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline_en_5.5.0_3.0_1725410922466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_english_d4niel92_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.5 MB|
+
+## References
+
+https://huggingface.co/d4niel92/xlm-roberta-base-finetuned-marc-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_ner_spa_english_9_3k_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_ner_spa_english_9_3k_en.md
new file mode 100644
index 00000000000000..9a0d230fa8e971
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_ner_spa_english_9_3k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_ner_spa_english_9_3k XlmRoBertaForTokenClassification from gus07ven
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_ner_spa_english_9_3k
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_ner_spa_english_9_3k` is a English model originally trained by gus07ven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_spa_english_9_3k_en_5.5.0_3.0_1725436488781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_spa_english_9_3k_en_5.5.0_3.0_1725436488781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_ner_spa_english_9_3k","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_ner_spa_english_9_3k", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_ner_spa_english_9_3k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|856.8 MB|
+
+## References
+
+https://huggingface.co/gus07ven/xlm-roberta-base-finetuned-ner-spa-en-9-3k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline_en.md
new file mode 100644
index 00000000000000..cb38ff547e33a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline pipeline XlmRoBertaForTokenClassification from gus07ven
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline` is a English model originally trained by gus07ven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline_en_5.5.0_3.0_1725436559098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline_en_5.5.0_3.0_1725436559098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_ner_spa_english_9_3k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|856.8 MB|
+
+## References
+
+https://huggingface.co/gus07ven/xlm-roberta-base-finetuned-ner-spa-en-9-3k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_hiroki_rad_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_hiroki_rad_en.md
new file mode 100644
index 00000000000000..12ced6ade1acaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_hiroki_rad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_hiroki_rad XlmRoBertaForTokenClassification from hiroki-rad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_hiroki_rad
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_hiroki_rad` is a English model originally trained by hiroki-rad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_hiroki_rad_en_5.5.0_3.0_1725435949878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_hiroki_rad_en_5.5.0_3.0_1725435949878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_hiroki_rad","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_hiroki_rad", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_hiroki_rad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|859.8 MB|
+
+## References
+
+https://huggingface.co/hiroki-rad/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline_en.md
new file mode 100644
index 00000000000000..8c9aef92cbe436
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline pipeline XlmRoBertaForTokenClassification from hiroki-rad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline` is a English model originally trained by hiroki-rad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline_en_5.5.0_3.0_1725436022135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline_en_5.5.0_3.0_1725436022135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_hiroki_rad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|859.8 MB|
+
+## References
+
+https://huggingface.co/hiroki-rad/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_jjglilleberg_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_jjglilleberg_en.md
new file mode 100644
index 00000000000000..d2d2b2d1acd6ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_jjglilleberg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_jjglilleberg XlmRoBertaForTokenClassification from jjglilleberg
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_jjglilleberg
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_jjglilleberg` is a English model originally trained by jjglilleberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_jjglilleberg_en_5.5.0_3.0_1725423541502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_jjglilleberg_en_5.5.0_3.0_1725423541502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_jjglilleberg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_jjglilleberg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_jjglilleberg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/jjglilleberg/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline_en.md
new file mode 100644
index 00000000000000..afdd137a62a3b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline pipeline XlmRoBertaForTokenClassification from jjglilleberg
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline` is a English model originally trained by jjglilleberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline_en_5.5.0_3.0_1725423631208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline_en_5.5.0_3.0_1725423631208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_jjglilleberg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/jjglilleberg/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lortigas_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lortigas_en.md
new file mode 100644
index 00000000000000..33ebcd5f8c180c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lortigas_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_lortigas XlmRoBertaForTokenClassification from lortigas
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_lortigas
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_lortigas` is a English model originally trained by lortigas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_lortigas_en_5.5.0_3.0_1725424784017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_lortigas_en_5.5.0_3.0_1725424784017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_lortigas","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_lortigas", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_lortigas|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/lortigas/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lortigas_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lortigas_pipeline_en.md
new file mode 100644
index 00000000000000..4cf0725de2b639
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lortigas_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_lortigas_pipeline pipeline XlmRoBertaForTokenClassification from lortigas
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_lortigas_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_lortigas_pipeline` is a English model originally trained by lortigas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_lortigas_pipeline_en_5.5.0_3.0_1725424848828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_lortigas_pipeline_en_5.5.0_3.0_1725424848828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_lortigas_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_lortigas_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_lortigas_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/lortigas/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lsh231_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lsh231_en.md
new file mode 100644
index 00000000000000..53cd5761e6ef43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lsh231_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_lsh231 XlmRoBertaForTokenClassification from lsh231
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_lsh231
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_lsh231` is a English model originally trained by lsh231.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_lsh231_en_5.5.0_3.0_1725446064048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_lsh231_en_5.5.0_3.0_1725446064048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_lsh231","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_lsh231", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_lsh231|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/lsh231/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lsh231_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lsh231_pipeline_en.md
new file mode 100644
index 00000000000000..1bc5f7b839644a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_lsh231_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_lsh231_pipeline pipeline XlmRoBertaForTokenClassification from lsh231
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_lsh231_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_lsh231_pipeline` is a English model originally trained by lsh231.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_lsh231_pipeline_en_5.5.0_3.0_1725446148136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_lsh231_pipeline_en_5.5.0_3.0_1725446148136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_lsh231_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_lsh231_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_lsh231_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/lsh231/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_monkdalma_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_monkdalma_en.md
new file mode 100644
index 00000000000000..237686f8b3f55e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_monkdalma_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_monkdalma XlmRoBertaForTokenClassification from MonkDalma
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_monkdalma
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_monkdalma` is a English model originally trained by MonkDalma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_monkdalma_en_5.5.0_3.0_1725447196587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_monkdalma_en_5.5.0_3.0_1725447196587.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_monkdalma","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_monkdalma", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_monkdalma|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/MonkDalma/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_msrisrujan_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_msrisrujan_en.md
new file mode 100644
index 00000000000000..2f55c5caac04b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_msrisrujan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_msrisrujan XlmRoBertaForTokenClassification from Msrisrujan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_msrisrujan
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_msrisrujan` is a English model originally trained by Msrisrujan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_msrisrujan_en_5.5.0_3.0_1725447620788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_msrisrujan_en_5.5.0_3.0_1725447620788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_msrisrujan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_msrisrujan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_msrisrujan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.7 MB|
+
+## References
+
+https://huggingface.co/Msrisrujan/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline_en.md
new file mode 100644
index 00000000000000..e2d26475ce7857
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline pipeline XlmRoBertaForTokenClassification from Msrisrujan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline` is a English model originally trained by Msrisrujan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline_en_5.5.0_3.0_1725447687818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline_en_5.5.0_3.0_1725447687818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_msrisrujan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.8 MB|
+
+## References
+
+https://huggingface.co/Msrisrujan/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_paww_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_paww_en.md
new file mode 100644
index 00000000000000..d5b38138b8f9e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_paww_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_paww XlmRoBertaForTokenClassification from paww
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_paww
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_paww` is a English model originally trained by paww.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_paww_en_5.5.0_3.0_1725422629413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_paww_en_5.5.0_3.0_1725422629413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_paww","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_paww", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_paww|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/paww/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_paww_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_paww_pipeline_en.md
new file mode 100644
index 00000000000000..ea2b5bb3063c5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_all_paww_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_paww_pipeline pipeline XlmRoBertaForTokenClassification from paww
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_paww_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_paww_pipeline` is a English model originally trained by paww.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_paww_pipeline_en_5.5.0_3.0_1725422695863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_paww_pipeline_en_5.5.0_3.0_1725422695863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_paww_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_paww_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_paww_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/paww/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_arabic_bothaynah_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_arabic_bothaynah_en.md
new file mode 100644
index 00000000000000..89d42f30768440
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_arabic_bothaynah_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_bothaynah XlmRoBertaForTokenClassification from bothaynaH
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_bothaynah
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_bothaynah` is a English model originally trained by bothaynaH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_bothaynah_en_5.5.0_3.0_1725446911082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_bothaynah_en_5.5.0_3.0_1725446911082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_bothaynah","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_bothaynah", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_bothaynah|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.6 MB|
+
+## References
+
+https://huggingface.co/bothaynaH/xlm-roberta-base-finetuned-panx-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline_en.md
new file mode 100644
index 00000000000000..12495dff5ef3d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline pipeline XlmRoBertaForTokenClassification from bothaynaH
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline` is a English model originally trained by bothaynaH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline_en_5.5.0_3.0_1725446981038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline_en_5.5.0_3.0_1725446981038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_bothaynah_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.7 MB|
+
+## References
+
+https://huggingface.co/bothaynaH/xlm-roberta-base-finetuned-panx-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_bluetree99_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_bluetree99_en.md
new file mode 100644
index 00000000000000..e22e0624891a89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_bluetree99_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_bluetree99 XlmRoBertaForTokenClassification from bluetree99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_bluetree99
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_bluetree99` is a English model originally trained by bluetree99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_bluetree99_en_5.5.0_3.0_1725436904373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_bluetree99_en_5.5.0_3.0_1725436904373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_bluetree99","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_bluetree99", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_bluetree99|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/bluetree99/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_fernweh23_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_fernweh23_en.md
new file mode 100644
index 00000000000000..715e75041bb99f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_fernweh23_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_fernweh23 XlmRoBertaForTokenClassification from Fernweh23
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_fernweh23
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_fernweh23` is a English model originally trained by Fernweh23.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_fernweh23_en_5.5.0_3.0_1725446682407.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_fernweh23_en_5.5.0_3.0_1725446682407.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_fernweh23","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_fernweh23", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_fernweh23|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Fernweh23/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline_en.md
new file mode 100644
index 00000000000000..aff855876c52e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline pipeline XlmRoBertaForTokenClassification from Fernweh23
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline` is a English model originally trained by Fernweh23.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline_en_5.5.0_3.0_1725446791498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline_en_5.5.0_3.0_1725446791498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_fernweh23_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Fernweh23/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_transformersbook_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_transformersbook_en.md
new file mode 100644
index 00000000000000..b1830099b61122
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_transformersbook_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_transformersbook XlmRoBertaForTokenClassification from transformersbook
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_transformersbook
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_transformersbook` is a English model originally trained by transformersbook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_transformersbook_en_5.5.0_3.0_1725424388970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_transformersbook_en_5.5.0_3.0_1725424388970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_transformersbook","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_transformersbook", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_transformersbook|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/transformersbook/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline_en.md
new file mode 100644
index 00000000000000..d7eada4a318b7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline pipeline XlmRoBertaForTokenClassification from transformersbook
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline` is a English model originally trained by transformersbook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline_en_5.5.0_3.0_1725424486743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline_en_5.5.0_3.0_1725424486743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_transformersbook_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/transformersbook/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_xrchen11_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_xrchen11_en.md
new file mode 100644
index 00000000000000..aa33101dee6107
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_xrchen11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_xrchen11 XlmRoBertaForTokenClassification from xrchen11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_xrchen11
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_xrchen11` is a English model originally trained by xrchen11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_xrchen11_en_5.5.0_3.0_1725422661755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_xrchen11_en_5.5.0_3.0_1725422661755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_xrchen11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_xrchen11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_xrchen11|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/xrchen11/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline_en.md
new file mode 100644
index 00000000000000..dbf953f6732035
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline pipeline XlmRoBertaForTokenClassification from xrchen11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline` is a English model originally trained by xrchen11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline_en_5.5.0_3.0_1725422770287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline_en_5.5.0_3.0_1725422770287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_xrchen11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/xrchen11/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_youngbeauty_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_youngbeauty_en.md
new file mode 100644
index 00000000000000..e8f85dc8dc6e6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_youngbeauty_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_youngbeauty XlmRoBertaForTokenClassification from YoungBeauty
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_youngbeauty
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_youngbeauty` is a English model originally trained by YoungBeauty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_youngbeauty_en_5.5.0_3.0_1725436120622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_youngbeauty_en_5.5.0_3.0_1725436120622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_youngbeauty","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_youngbeauty", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_youngbeauty|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/YoungBeauty/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline_en.md
new file mode 100644
index 00000000000000..5224f24029009a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline pipeline XlmRoBertaForTokenClassification from YoungBeauty
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline` is a English model originally trained by YoungBeauty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline_en_5.5.0_3.0_1725436216021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline_en_5.5.0_3.0_1725436216021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_youngbeauty_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/YoungBeauty/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_chaoli_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_chaoli_en.md
new file mode 100644
index 00000000000000..cc2450b51b7704
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_chaoli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_chaoli XlmRoBertaForTokenClassification from ChaoLi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_chaoli
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_chaoli` is a English model originally trained by ChaoLi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_chaoli_en_5.5.0_3.0_1725446260028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_chaoli_en_5.5.0_3.0_1725446260028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_chaoli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_chaoli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_chaoli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/ChaoLi/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_handun_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_handun_pipeline_en.md
new file mode 100644
index 00000000000000..784a9d9b7fd64d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_handun_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_handun_pipeline pipeline XlmRoBertaForTokenClassification from Handun
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_handun_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_handun_pipeline` is a English model originally trained by Handun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_handun_pipeline_en_5.5.0_3.0_1725445835149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_handun_pipeline_en_5.5.0_3.0_1725445835149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_handun_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_handun_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_handun_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/Handun/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_lortigas_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_lortigas_en.md
new file mode 100644
index 00000000000000..fdac198df37e14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_lortigas_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_lortigas XlmRoBertaForTokenClassification from lortigas
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_lortigas
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_lortigas` is a English model originally trained by lortigas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_lortigas_en_5.5.0_3.0_1725424124122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_lortigas_en_5.5.0_3.0_1725424124122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_lortigas","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_lortigas", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_lortigas|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/lortigas/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_lortigas_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_lortigas_pipeline_en.md
new file mode 100644
index 00000000000000..3c623695d3e774
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_lortigas_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_lortigas_pipeline pipeline XlmRoBertaForTokenClassification from lortigas
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_lortigas_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_lortigas_pipeline` is a English model originally trained by lortigas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_lortigas_pipeline_en_5.5.0_3.0_1725424205237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_lortigas_pipeline_en_5.5.0_3.0_1725424205237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_lortigas_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_lortigas_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_lortigas_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/lortigas/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_malduwais_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_malduwais_pipeline_en.md
new file mode 100644
index 00000000000000..2b38b2b784da1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_french_malduwais_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_malduwais_pipeline pipeline XlmRoBertaForTokenClassification from malduwais
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_malduwais_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_malduwais_pipeline` is a English model originally trained by malduwais.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_malduwais_pipeline_en_5.5.0_3.0_1725424288373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_malduwais_pipeline_en_5.5.0_3.0_1725424288373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_malduwais_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_malduwais_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_malduwais_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|845.1 MB|
+
+## References
+
+https://huggingface.co/malduwais/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_adsjklfsd_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_adsjklfsd_en.md
new file mode 100644
index 00000000000000..c9ae216300b7c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_adsjklfsd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_adsjklfsd XlmRoBertaForTokenClassification from adsjklfsd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_adsjklfsd
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_adsjklfsd` is a English model originally trained by adsjklfsd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_adsjklfsd_en_5.5.0_3.0_1725437006645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_adsjklfsd_en_5.5.0_3.0_1725437006645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_adsjklfsd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_adsjklfsd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_adsjklfsd|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/adsjklfsd/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline_en.md
new file mode 100644
index 00000000000000..9c30426dc9e7c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline pipeline XlmRoBertaForTokenClassification from adsjklfsd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline` is a English model originally trained by adsjklfsd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline_en_5.5.0_3.0_1725437077202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline_en_5.5.0_3.0_1725437077202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_adsjklfsd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/adsjklfsd/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_andreaschandra_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_andreaschandra_en.md
new file mode 100644
index 00000000000000..fbfae7bd2229a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_andreaschandra_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_andreaschandra XlmRoBertaForTokenClassification from andreaschandra
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_andreaschandra
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_andreaschandra` is a English model originally trained by andreaschandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_andreaschandra_en_5.5.0_3.0_1725422680525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_andreaschandra_en_5.5.0_3.0_1725422680525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_andreaschandra","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_andreaschandra", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_andreaschandra|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/andreaschandra/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline_en.md
new file mode 100644
index 00000000000000..9792c444c129c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline pipeline XlmRoBertaForTokenClassification from andreaschandra
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline` is a English model originally trained by andreaschandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline_en_5.5.0_3.0_1725422751515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline_en_5.5.0_3.0_1725422751515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_andreaschandra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/andreaschandra/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_bessho_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_bessho_pipeline_en.md
new file mode 100644
index 00000000000000..af13340ef7b801
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_bessho_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_bessho_pipeline pipeline XlmRoBertaForTokenClassification from bessho
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_bessho_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_bessho_pipeline` is a English model originally trained by bessho.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bessho_pipeline_en_5.5.0_3.0_1725436678492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bessho_pipeline_en_5.5.0_3.0_1725436678492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_bessho_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_bessho_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_bessho_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/bessho/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_blanche_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_blanche_pipeline_en.md
new file mode 100644
index 00000000000000..4b83f1e66e600c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_blanche_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_blanche_pipeline pipeline XlmRoBertaForTokenClassification from Blanche
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_blanche_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_blanche_pipeline` is a English model originally trained by Blanche.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_blanche_pipeline_en_5.5.0_3.0_1725447202109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_blanche_pipeline_en_5.5.0_3.0_1725447202109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_blanche_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_blanche_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_blanche_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|815.0 MB|
+
+## References
+
+https://huggingface.co/Blanche/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_dream100_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_dream100_en.md
new file mode 100644
index 00000000000000..a10fd6bd7d5695
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_dream100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_dream100 XlmRoBertaForTokenClassification from Dream100
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_dream100
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_dream100` is a English model originally trained by Dream100.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dream100_en_5.5.0_3.0_1725436487249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dream100_en_5.5.0_3.0_1725436487249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_dream100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_dream100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_dream100|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Dream100/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_dream100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_dream100_pipeline_en.md
new file mode 100644
index 00000000000000..b85734f65009e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_dream100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_dream100_pipeline pipeline XlmRoBertaForTokenClassification from Dream100
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_dream100_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_dream100_pipeline` is a English model originally trained by Dream100.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dream100_pipeline_en_5.5.0_3.0_1725436564660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dream100_pipeline_en_5.5.0_3.0_1725436564660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_dream100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_dream100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_dream100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Dream100/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_edmon02_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_edmon02_en.md
new file mode 100644
index 00000000000000..b5ab72c2d7fc78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_edmon02_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_edmon02 XlmRoBertaForTokenClassification from Edmon02
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_edmon02
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_edmon02` is a English model originally trained by Edmon02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_edmon02_en_5.5.0_3.0_1725446367874.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_edmon02_en_5.5.0_3.0_1725446367874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_edmon02","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_edmon02", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_edmon02|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Edmon02/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_edmon02_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_edmon02_pipeline_en.md
new file mode 100644
index 00000000000000..19be55a4465962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_edmon02_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_edmon02_pipeline pipeline XlmRoBertaForTokenClassification from Edmon02
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_edmon02_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_edmon02_pipeline` is a English model originally trained by Edmon02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_edmon02_pipeline_en_5.5.0_3.0_1725446436354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_edmon02_pipeline_en_5.5.0_3.0_1725446436354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_edmon02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_edmon02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_edmon02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Edmon02/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_lsh231_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_lsh231_en.md
new file mode 100644
index 00000000000000..4779af7aa66ae3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_lsh231_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_lsh231 XlmRoBertaForTokenClassification from lsh231
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_lsh231
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_lsh231` is a English model originally trained by lsh231.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_lsh231_en_5.5.0_3.0_1725436892677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_lsh231_en_5.5.0_3.0_1725436892677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_lsh231","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_lsh231", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_lsh231|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/lsh231/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline_en.md
new file mode 100644
index 00000000000000..e9cd3957e7c146
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline pipeline XlmRoBertaForTokenClassification from lsh231
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline` is a English model originally trained by lsh231.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline_en_5.5.0_3.0_1725436980288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline_en_5.5.0_3.0_1725436980288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_lsh231_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/lsh231/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_nrazavi_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_nrazavi_en.md
new file mode 100644
index 00000000000000..18804fb5ef1fcf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_nrazavi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_nrazavi XlmRoBertaForTokenClassification from nrazavi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_nrazavi
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_nrazavi` is a English model originally trained by nrazavi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nrazavi_en_5.5.0_3.0_1725447666936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nrazavi_en_5.5.0_3.0_1725447666936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_nrazavi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_nrazavi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_nrazavi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/nrazavi/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline_en.md
new file mode 100644
index 00000000000000..b31d344931ce8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline pipeline XlmRoBertaForTokenClassification from nrazavi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline` is a English model originally trained by nrazavi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline_en_5.5.0_3.0_1725447733372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline_en_5.5.0_3.0_1725447733372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_nrazavi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/nrazavi/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_sungwoo1_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_sungwoo1_en.md
new file mode 100644
index 00000000000000..f0ea4437dfc7bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_sungwoo1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_sungwoo1 XlmRoBertaForTokenClassification from sungwoo1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_sungwoo1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_sungwoo1` is a English model originally trained by sungwoo1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_sungwoo1_en_5.5.0_3.0_1725446768035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_sungwoo1_en_5.5.0_3.0_1725446768035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_sungwoo1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_sungwoo1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_sungwoo1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/sungwoo1/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline_en.md
new file mode 100644
index 00000000000000..35ffe3148d7cac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline pipeline XlmRoBertaForTokenClassification from sungwoo1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline` is a English model originally trained by sungwoo1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline_en_5.5.0_3.0_1725446836185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline_en_5.5.0_3.0_1725446836185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_sungwoo1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/sungwoo1/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline_en.md
new file mode 100644
index 00000000000000..b73f0b4ec5d266
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline pipeline XlmRoBertaForTokenClassification from team-nave
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline` is a English model originally trained by team-nave.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline_en_5.5.0_3.0_1725436167812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline_en_5.5.0_3.0_1725436167812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_team_nave_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|857.0 MB|
+
+## References
+
+https://huggingface.co/team-nave/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_joanna684_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_joanna684_en.md
new file mode 100644
index 00000000000000..d21f5ed0c54fd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_joanna684_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_joanna684 XlmRoBertaForTokenClassification from Joanna684
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_joanna684
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_joanna684` is a English model originally trained by Joanna684.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_joanna684_en_5.5.0_3.0_1725447060358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_joanna684_en_5.5.0_3.0_1725447060358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_joanna684","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_joanna684", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_joanna684|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Joanna684/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_joanna684_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_joanna684_pipeline_en.md
new file mode 100644
index 00000000000000..dc94353f4d0104
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_joanna684_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_joanna684_pipeline pipeline XlmRoBertaForTokenClassification from Joanna684
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_joanna684_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_joanna684_pipeline` is a English model originally trained by Joanna684.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_joanna684_pipeline_en_5.5.0_3.0_1725447128805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_joanna684_pipeline_en_5.5.0_3.0_1725447128805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_joanna684_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_joanna684_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_joanna684_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Joanna684/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_junf1122_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_junf1122_en.md
new file mode 100644
index 00000000000000..071221d39fa7cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_junf1122_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_junf1122 XlmRoBertaForTokenClassification from JunF1122
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_junf1122
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_junf1122` is a English model originally trained by JunF1122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_junf1122_en_5.5.0_3.0_1725447873045.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_junf1122_en_5.5.0_3.0_1725447873045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_junf1122","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_junf1122", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_junf1122|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/JunF1122/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_malduwais_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_malduwais_pipeline_en.md
new file mode 100644
index 00000000000000..db596ea4fb5e30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_malduwais_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_malduwais_pipeline pipeline XlmRoBertaForTokenClassification from malduwais
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_malduwais_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_malduwais_pipeline` is a English model originally trained by malduwais.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_malduwais_pipeline_en_5.5.0_3.0_1725423847297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_malduwais_pipeline_en_5.5.0_3.0_1725423847297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_malduwais_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_malduwais_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_malduwais_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|832.4 MB|
+
+## References
+
+https://huggingface.co/malduwais/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_occupy1_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_occupy1_en.md
new file mode 100644
index 00000000000000..be76e5e7982cb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_occupy1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_occupy1 XlmRoBertaForTokenClassification from occupy1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_occupy1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_occupy1` is a English model originally trained by occupy1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_occupy1_en_5.5.0_3.0_1725437664377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_occupy1_en_5.5.0_3.0_1725437664377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_occupy1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_occupy1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_occupy1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/occupy1/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_occupy1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_occupy1_pipeline_en.md
new file mode 100644
index 00000000000000..e8c513468c5070
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_occupy1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_occupy1_pipeline pipeline XlmRoBertaForTokenClassification from occupy1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_occupy1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_occupy1_pipeline` is a English model originally trained by occupy1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_occupy1_pipeline_en_5.5.0_3.0_1725437750929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_occupy1_pipeline_en_5.5.0_3.0_1725437750929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_occupy1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_occupy1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_occupy1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/occupy1/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_sbpark_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_sbpark_pipeline_en.md
new file mode 100644
index 00000000000000..635fc3a1a7eb21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_sbpark_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sbpark_pipeline pipeline XlmRoBertaForTokenClassification from sbpark
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sbpark_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sbpark_pipeline` is a English model originally trained by sbpark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sbpark_pipeline_en_5.5.0_3.0_1725447780415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sbpark_pipeline_en_5.5.0_3.0_1725447780415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sbpark_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sbpark_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sbpark_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/sbpark/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_songys_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_songys_en.md
new file mode 100644
index 00000000000000..9632638670e2b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_songys_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_songys XlmRoBertaForTokenClassification from songys
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_songys
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_songys` is a English model originally trained by songys.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_songys_en_5.5.0_3.0_1725436225938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_songys_en_5.5.0_3.0_1725436225938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_songys","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_songys", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_songys|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.2 MB|
+
+## References
+
+https://huggingface.co/songys/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_sponomary_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_sponomary_pipeline_en.md
new file mode 100644
index 00000000000000..fa9092eb99a04a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_sponomary_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sponomary_pipeline pipeline XlmRoBertaForTokenClassification from sponomary
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sponomary_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sponomary_pipeline` is a English model originally trained by sponomary.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sponomary_pipeline_en_5.5.0_3.0_1725446219129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sponomary_pipeline_en_5.5.0_3.0_1725446219129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sponomary_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sponomary_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sponomary_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/sponomary/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_szogi_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_szogi_en.md
new file mode 100644
index 00000000000000..03f33c5d60196e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_szogi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_szogi XlmRoBertaForTokenClassification from szogi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_szogi
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_szogi` is a English model originally trained by szogi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_szogi_en_5.5.0_3.0_1725447539358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_szogi_en_5.5.0_3.0_1725447539358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_szogi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_szogi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_szogi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/szogi/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_takehirako_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_takehirako_en.md
new file mode 100644
index 00000000000000..fa44c55d3aa183
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_takehirako_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_takehirako XlmRoBertaForTokenClassification from TakeHirako
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_takehirako
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_takehirako` is a English model originally trained by TakeHirako.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_takehirako_en_5.5.0_3.0_1725437205424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_takehirako_en_5.5.0_3.0_1725437205424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_takehirako","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_takehirako", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_takehirako|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/TakeHirako/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_takehirako_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_takehirako_pipeline_en.md
new file mode 100644
index 00000000000000..0d4b2b68bcd168
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_takehirako_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_takehirako_pipeline pipeline XlmRoBertaForTokenClassification from TakeHirako
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_takehirako_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_takehirako_pipeline` is a English model originally trained by TakeHirako.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_takehirako_pipeline_en_5.5.0_3.0_1725437274747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_takehirako_pipeline_en_5.5.0_3.0_1725437274747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_takehirako_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_takehirako_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_takehirako_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/TakeHirako/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_andreaschandra_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_andreaschandra_en.md
new file mode 100644
index 00000000000000..a87d3d8f423546
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_andreaschandra_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_andreaschandra XlmRoBertaForTokenClassification from andreaschandra
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_andreaschandra
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_andreaschandra` is a English model originally trained by andreaschandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_andreaschandra_en_5.5.0_3.0_1725424667485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_andreaschandra_en_5.5.0_3.0_1725424667485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_andreaschandra","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_andreaschandra", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_andreaschandra|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/andreaschandra/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline_en.md
new file mode 100644
index 00000000000000..5cd215db9acf28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline pipeline XlmRoBertaForTokenClassification from andreaschandra
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline` is a English model originally trained by andreaschandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline_en_5.5.0_3.0_1725424756109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline_en_5.5.0_3.0_1725424756109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_andreaschandra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/andreaschandra/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline_en.md
new file mode 100644
index 00000000000000..e8f7cfce628369
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline pipeline XlmRoBertaForTokenClassification from cj-mills
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline` is a English model originally trained by cj-mills.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline_en_5.5.0_3.0_1725447451953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline_en_5.5.0_3.0_1725447451953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_cj_mills_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.8 MB|
+
+## References
+
+https://huggingface.co/cj-mills/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cogsci13_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cogsci13_en.md
new file mode 100644
index 00000000000000..c19430099f4f32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cogsci13_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_cogsci13 XlmRoBertaForTokenClassification from cogsci13
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_cogsci13
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_cogsci13` is a English model originally trained by cogsci13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cogsci13_en_5.5.0_3.0_1725423277633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cogsci13_en_5.5.0_3.0_1725423277633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_cogsci13","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_cogsci13", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_cogsci13|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/cogsci13/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline_en.md
new file mode 100644
index 00000000000000..1ce3554b744e1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline pipeline XlmRoBertaForTokenClassification from cogsci13
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline` is a English model originally trained by cogsci13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline_en_5.5.0_3.0_1725423377373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline_en_5.5.0_3.0_1725423377373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_cogsci13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/cogsci13/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_noveled_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_noveled_en.md
new file mode 100644
index 00000000000000..3df7447dca0cc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_noveled_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_noveled XlmRoBertaForTokenClassification from Noveled
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_noveled
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_noveled` is a English model originally trained by Noveled.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_noveled_en_5.5.0_3.0_1725422938574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_noveled_en_5.5.0_3.0_1725422938574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_noveled","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_noveled", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_noveled|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/Noveled/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_noveled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_noveled_pipeline_en.md
new file mode 100644
index 00000000000000..f1ba17ed3e8f43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_noveled_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_noveled_pipeline pipeline XlmRoBertaForTokenClassification from Noveled
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_noveled_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_noveled_pipeline` is a English model originally trained by Noveled.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_noveled_pipeline_en_5.5.0_3.0_1725423039113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_noveled_pipeline_en_5.5.0_3.0_1725423039113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_noveled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_noveled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_noveled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/Noveled/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_royam0820_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_royam0820_en.md
new file mode 100644
index 00000000000000..a455ff097996db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_royam0820_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_royam0820 XlmRoBertaForTokenClassification from royam0820
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_royam0820
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_royam0820` is a English model originally trained by royam0820.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_royam0820_en_5.5.0_3.0_1725422618399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_royam0820_en_5.5.0_3.0_1725422618399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_royam0820","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_royam0820", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_royam0820|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/royam0820/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline_en.md
new file mode 100644
index 00000000000000..90fca1146eda02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline pipeline XlmRoBertaForTokenClassification from royam0820
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline` is a English model originally trained by royam0820.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline_en_5.5.0_3.0_1725422707990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline_en_5.5.0_3.0_1725422707990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_royam0820_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.7 MB|
+
+## References
+
+https://huggingface.co/royam0820/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_sponomary_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_sponomary_en.md
new file mode 100644
index 00000000000000..0d332a0015674a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_sponomary_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_sponomary XlmRoBertaForTokenClassification from sponomary
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_sponomary
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_sponomary` is a English model originally trained by sponomary.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_sponomary_en_5.5.0_3.0_1725437072737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_sponomary_en_5.5.0_3.0_1725437072737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_sponomary","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_sponomary", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_sponomary|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/sponomary/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_youngbeauty_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_youngbeauty_en.md
new file mode 100644
index 00000000000000..957fa47a5155eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_youngbeauty_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_youngbeauty XlmRoBertaForTokenClassification from YoungBeauty
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_youngbeauty
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_youngbeauty` is a English model originally trained by YoungBeauty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_youngbeauty_en_5.5.0_3.0_1725437599916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_youngbeauty_en_5.5.0_3.0_1725437599916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_youngbeauty","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_youngbeauty", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_youngbeauty|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/YoungBeauty/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline_en.md
new file mode 100644
index 00000000000000..7fa15efd7f1893
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline pipeline XlmRoBertaForTokenClassification from YoungBeauty
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline` is a English model originally trained by YoungBeauty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline_en_5.5.0_3.0_1725437689025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline_en_5.5.0_3.0_1725437689025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_youngbeauty_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/YoungBeauty/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_marathi_marh_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_marathi_marh_en.md
new file mode 100644
index 00000000000000..2ae88298a7530c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_marathi_marh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_marathi_marh XlmRoBertaForTokenClassification from neelrr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_marathi_marh
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_marathi_marh` is a English model originally trained by neelrr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_marathi_marh_en_5.5.0_3.0_1725437860216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_marathi_marh_en_5.5.0_3.0_1725437860216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_marathi_marh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_marathi_marh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_marathi_marh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|834.7 MB|
+
+## References
+
+https://huggingface.co/neelrr/xlm-roberta-base-finetuned-panx-mr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_marathi_marh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_marathi_marh_pipeline_en.md
new file mode 100644
index 00000000000000..b22c4f4e05dab9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_marathi_marh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_marathi_marh_pipeline pipeline XlmRoBertaForTokenClassification from neelrr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_marathi_marh_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_marathi_marh_pipeline` is a English model originally trained by neelrr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_marathi_marh_pipeline_en_5.5.0_3.0_1725437939137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_marathi_marh_pipeline_en_5.5.0_3.0_1725437939137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_marathi_marh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_marathi_marh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_marathi_marh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|834.8 MB|
+
+## References
+
+https://huggingface.co/neelrr/xlm-roberta-base-finetuned-panx-mr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_squadv2_quocviethere_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_squadv2_quocviethere_en.md
new file mode 100644
index 00000000000000..5894cc1e61629d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_squadv2_quocviethere_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_squadv2_quocviethere XlmRoBertaForQuestionAnswering from quocviethere
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_squadv2_quocviethere
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_squadv2_quocviethere` is a English model originally trained by quocviethere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squadv2_quocviethere_en_5.5.0_3.0_1725482226284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squadv2_quocviethere_en_5.5.0_3.0_1725482226284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_squadv2_quocviethere","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_squadv2_quocviethere", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_squadv2_quocviethere|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|839.8 MB|
+
+## References
+
+https://huggingface.co/quocviethere/xlm-roberta-base-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline_en.md
new file mode 100644
index 00000000000000..fa6d483c90675a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline pipeline XlmRoBertaForQuestionAnswering from quocviethere
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline` is a English model originally trained by quocviethere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline_en_5.5.0_3.0_1725482332945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline_en_5.5.0_3.0_1725482332945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_squadv2_quocviethere_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|839.8 MB|
+
+## References
+
+https://huggingface.co/quocviethere/xlm-roberta-base-finetuned-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_en.md
new file mode 100644
index 00000000000000..70af788f19f699
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_ft_udpos213_top4lang_southern_sotho XlmRoBertaForTokenClassification from iceman2434
+author: John Snow Labs
+name: xlm_roberta_base_ft_udpos213_top4lang_southern_sotho
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ft_udpos213_top4lang_southern_sotho` is a English model originally trained by iceman2434.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_en_5.5.0_3.0_1725446740180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_en_5.5.0_3.0_1725446740180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_ft_udpos213_top4lang_southern_sotho","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_ft_udpos213_top4lang_southern_sotho", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ft_udpos213_top4lang_southern_sotho|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|792.8 MB|
+
+## References
+
+https://huggingface.co/iceman2434/xlm-roberta-base_ft_udpos213-top4lang-st
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline_en.md
new file mode 100644
index 00000000000000..639ee14db92a46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline pipeline XlmRoBertaForTokenClassification from iceman2434
+author: John Snow Labs
+name: xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline` is a English model originally trained by iceman2434.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline_en_5.5.0_3.0_1725446876116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline_en_5.5.0_3.0_1725446876116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ft_udpos213_top4lang_southern_sotho_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|792.8 MB|
+
+## References
+
+https://huggingface.co/iceman2434/xlm-roberta-base_ft_udpos213-top4lang-st
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train_en.md
new file mode 100644
index 00000000000000..a0dc32c243fe8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train_en_5.5.0_3.0_1725410557335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train_en_5.5.0_3.0_1725410557335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr0_0001_seed42_kinyarwanda_amh_eng_train|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|819.9 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr0.0001_seed42_kin-amh-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ner_augmentation_xx.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ner_augmentation_xx.md
new file mode 100644
index 00000000000000..dd54e1e699b29b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ner_augmentation_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual xlm_roberta_base_ner_augmentation XlmRoBertaForTokenClassification from rollerhafeezh-amikom
+author: John Snow Labs
+name: xlm_roberta_base_ner_augmentation
+date: 2024-09-04
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ner_augmentation` is a Multilingual model originally trained by rollerhafeezh-amikom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ner_augmentation_xx_5.5.0_3.0_1725447441445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ner_augmentation_xx_5.5.0_3.0_1725447441445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_ner_augmentation","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_ner_augmentation", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ner_augmentation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|850.0 MB|
+
+## References
+
+https://huggingface.co/rollerhafeezh-amikom/xlm-roberta-base-ner-augmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ner_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ner_pipeline_xx.md
new file mode 100644
index 00000000000000..88979494434db0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_ner_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlm_roberta_base_ner_pipeline pipeline XlmRoBertaForTokenClassification from orgcatorg
+author: John Snow Labs
+name: xlm_roberta_base_ner_pipeline
+date: 2024-09-04
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ner_pipeline` is a Multilingual model originally trained by orgcatorg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ner_pipeline_xx_5.5.0_3.0_1725423998693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ner_pipeline_xx_5.5.0_3.0_1725423998693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_ner_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_ner_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|869.0 MB|
+
+## References
+
+https://huggingface.co/orgcatorg/xlm-roberta-base-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline_en.md
new file mode 100644
index 00000000000000..145946e0857640
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline pipeline XlmRoBertaForSequenceClassification from sismetanin
+author: John Snow Labs
+name: xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline` is a English model originally trained by sismetanin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline_en_5.5.0_3.0_1725411179343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline_en_5.5.0_3.0_1725411179343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_russian_sentiment_sentirueval2016_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|797.1 MB|
+
+## References
+
+https://huggingface.co/sismetanin/xlm_roberta_base-ru-sentiment-sentirueval2016
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline_en.md
new file mode 100644
index 00000000000000..168a4d8193def6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline pipeline XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline_en_5.5.0_3.0_1725410254995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline_en_5.5.0_3.0_1725410254995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_tweet_sentiment_portuguese_trimmed_portuguese_15000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|358.2 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-roberta-base-tweet-sentiment-pt-trimmed-pt-15000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline_en.md
new file mode 100644
index 00000000000000..f95d946f2c6a06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline pipeline XlmRoBertaForSequenceClassification from Karim-Gamal
+author: John Snow Labs
+name: xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline` is a English model originally trained by Karim-Gamal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline_en_5.5.0_3.0_1725410678315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline_en_5.5.0_3.0_1725410678315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_finetuned_emojis_2_client_toxic_fedavg_iid_fed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Karim-Gamal/XLM-Roberta-finetuned-emojis-2-client-toxic-FedAvg-IID-Fed
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline_en.md
new file mode 100644
index 00000000000000..e3a7284cd74dac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline pipeline XlmRoBertaForQuestionAnswering from rizquuula
+author: John Snow Labs
+name: xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline` is a English model originally trained by rizquuula.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline_en_5.5.0_3.0_1725483153773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline_en_5.5.0_3.0_1725483153773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|818.0 MB|
+
+## References
+
+https://huggingface.co/rizquuula/XLM-RoBERTa-IndoSQuADv2_1693993923-8-2e-06-0.01-5
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_markussagen_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_markussagen_en.md
new file mode 100644
index 00000000000000..269960af6944bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_markussagen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_longformer_base_4096_markussagen XlmRoBertaEmbeddings from markussagen
+author: John Snow Labs
+name: xlm_roberta_longformer_base_4096_markussagen
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_longformer_base_4096_markussagen` is a English model originally trained by markussagen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_markussagen_en_5.5.0_3.0_1725417410437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_markussagen_en_5.5.0_3.0_1725417410437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_longformer_base_4096_markussagen","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_longformer_base_4096_markussagen","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_longformer_base_4096_markussagen|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/markussagen/xlm-roberta-longformer-base-4096
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_markussagen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_markussagen_pipeline_en.md
new file mode 100644
index 00000000000000..47227958935bff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_markussagen_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_longformer_base_4096_markussagen_pipeline pipeline XlmRoBertaEmbeddings from markussagen
+author: John Snow Labs
+name: xlm_roberta_longformer_base_4096_markussagen_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_longformer_base_4096_markussagen_pipeline` is a English model originally trained by markussagen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_markussagen_pipeline_en_5.5.0_3.0_1725417472323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_markussagen_pipeline_en_5.5.0_3.0_1725417472323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_longformer_base_4096_markussagen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_longformer_base_4096_markussagen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_longformer_base_4096_markussagen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/markussagen/xlm-roberta-longformer-base-4096
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_peltarion_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_peltarion_en.md
new file mode 100644
index 00000000000000..838dc43f1eeb05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_peltarion_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_longformer_base_4096_peltarion XlmRoBertaEmbeddings from Peltarion
+author: John Snow Labs
+name: xlm_roberta_longformer_base_4096_peltarion
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_longformer_base_4096_peltarion` is a English model originally trained by Peltarion.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_peltarion_en_5.5.0_3.0_1725416985297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_peltarion_en_5.5.0_3.0_1725416985297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_longformer_base_4096_peltarion","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_longformer_base_4096_peltarion","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_longformer_base_4096_peltarion|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Peltarion/xlm-roberta-longformer-base-4096
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_peltarion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_peltarion_pipeline_en.md
new file mode 100644
index 00000000000000..7e577bbc64294f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_longformer_base_4096_peltarion_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_longformer_base_4096_peltarion_pipeline pipeline XlmRoBertaEmbeddings from Peltarion
+author: John Snow Labs
+name: xlm_roberta_longformer_base_4096_peltarion_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_longformer_base_4096_peltarion_pipeline` is a English model originally trained by Peltarion.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_peltarion_pipeline_en_5.5.0_3.0_1725417041984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_peltarion_pipeline_en_5.5.0_3.0_1725417041984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_longformer_base_4096_peltarion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_longformer_base_4096_peltarion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_longformer_base_4096_peltarion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Peltarion/xlm-roberta-longformer-base-4096
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_en.md
new file mode 100644
index 00000000000000..c0c8c770931f4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from teacookies)
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465517
+date: 2024-09-04
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-base-squad2-24465517` is a English model originally trained by `teacookies`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_en_5.5.0_3.0_1725481887609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_en_5.5.0_3.0_1725481887609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465517","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465517","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.xlm_roberta.base_24465517.by_teacookies").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465517|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|887.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465517
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_finetuned_chaii_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_finetuned_chaii_en.md
new file mode 100644
index 00000000000000..1a6b489002ee8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_finetuned_chaii_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from tyqiangz)
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_finetuned_chaii
+date: 2024-09-04
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-chaii` is a English model originally trained by `tyqiangz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_finetuned_chaii_en_5.5.0_3.0_1725482017312.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_finetuned_chaii_en_5.5.0_3.0_1725482017312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_finetuned_chaii","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_xlm_roberta_base_finetuned_chaii","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.chaii.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_finetuned_chaii|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|861.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/tyqiangz/xlm-roberta-base-finetuned-chaii
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_spanish_es.md
new file mode 100644
index 00000000000000..c5bc17667cad89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_spanish_es.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: Spanish XlmRoBertaForQuestionAnswering (from bhavikardeshna)
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_spanish
+date: 2024-09-04
+tags: [es, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-spanish` is a Spanish model originally trained by `bhavikardeshna`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_spanish_es_5.5.0_3.0_1725481705874.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_spanish_es_5.5.0_3.0_1725481705874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_xlm_roberta_base_spanish","es") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_xlm_roberta_base_spanish","es")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("es.answer_question.xlm_roberta.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|883.0 MB|
+
+## References
+
+References
+
+- https://huggingface.co/bhavikardeshna/xlm-roberta-base-spanish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..f437c562755607
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_xlm_roberta_base_spanish_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish xlm_roberta_qa_xlm_roberta_base_spanish_pipeline pipeline XlmRoBertaForQuestionAnswering from bhavikardeshna
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_spanish_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_spanish_pipeline` is a Castilian, Spanish model originally trained by bhavikardeshna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_spanish_pipeline_es_5.5.0_3.0_1725481766438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_spanish_pipeline_es_5.5.0_3.0_1725481766438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|883.0 MB|
+
+## References
+
+https://huggingface.co/bhavikardeshna/xlm-roberta-base-spanish
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmindic_base_uniscript_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-04-xlmindic_base_uniscript_pipeline_xx.md
new file mode 100644
index 00000000000000..d7d3bed07a5727
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmindic_base_uniscript_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmindic_base_uniscript_pipeline pipeline AlbertEmbeddings from ibraheemmoosa
+author: John Snow Labs
+name: xlmindic_base_uniscript_pipeline
+date: 2024-09-04
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmindic_base_uniscript_pipeline` is a Multilingual model originally trained by ibraheemmoosa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmindic_base_uniscript_pipeline_xx_5.5.0_3.0_1725435287525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmindic_base_uniscript_pipeline_xx_5.5.0_3.0_1725435287525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmindic_base_uniscript_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmindic_base_uniscript_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmindic_base_uniscript_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|51.7 MB|
+
+## References
+
+https://huggingface.co/ibraheemmoosa/xlmindic-base-uniscript
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmindic_base_uniscript_xx.md b/docs/_posts/ahmedlone127/2024-09-04-xlmindic_base_uniscript_xx.md
new file mode 100644
index 00000000000000..4322c2e619b20e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmindic_base_uniscript_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual xlmindic_base_uniscript AlbertEmbeddings from ibraheemmoosa
+author: John Snow Labs
+name: xlmindic_base_uniscript
+date: 2024-09-04
+tags: [xx, open_source, onnx, embeddings, albert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmindic_base_uniscript` is a Multilingual model originally trained by ibraheemmoosa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmindic_base_uniscript_xx_5.5.0_3.0_1725435284700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmindic_base_uniscript_xx_5.5.0_3.0_1725435284700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = AlbertEmbeddings.pretrained("xlmindic_base_uniscript","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = AlbertEmbeddings.pretrained("xlmindic_base_uniscript","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmindic_base_uniscript|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[albert]|
+|Language:|xx|
+|Size:|51.7 MB|
+
+## References
+
+https://huggingface.co/ibraheemmoosa/xlmindic-base-uniscript
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_all_shuffled_1986_test1000_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_all_shuffled_1986_test1000_en.md
new file mode 100644
index 00000000000000..dfa8565130c9c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_all_shuffled_1986_test1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_english_chinese_all_shuffled_1986_test1000 XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_english_chinese_all_shuffled_1986_test1000
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_english_chinese_all_shuffled_1986_test1000` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_all_shuffled_1986_test1000_en_5.5.0_3.0_1725411794220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_all_shuffled_1986_test1000_en_5.5.0_3.0_1725411794220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_english_chinese_all_shuffled_1986_test1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_english_chinese_all_shuffled_1986_test1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_english_chinese_all_shuffled_1986_test1000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|828.3 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-en-zh-all_shuffled-1986-test1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_all_shuffled_1986_test1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_all_shuffled_1986_test1000_pipeline_en.md
new file mode 100644
index 00000000000000..d862bf97d2be42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_all_shuffled_1986_test1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_english_chinese_all_shuffled_1986_test1000_pipeline pipeline XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_english_chinese_all_shuffled_1986_test1000_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_english_chinese_all_shuffled_1986_test1000_pipeline` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_all_shuffled_1986_test1000_pipeline_en_5.5.0_3.0_1725411907961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_all_shuffled_1986_test1000_pipeline_en_5.5.0_3.0_1725411907961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_english_chinese_all_shuffled_1986_test1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_english_chinese_all_shuffled_1986_test1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_english_chinese_all_shuffled_1986_test1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.4 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-en-zh-all_shuffled-1986-test1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline_en.md
new file mode 100644
index 00000000000000..81715fffa61dbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline pipeline XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline_en_5.5.0_3.0_1725410612503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline_en_5.5.0_3.0_1725410612503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_english_chinese_norwegian_shuffled_orig_test1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.0 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-en-zh-no_shuffled-orig-test1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmr_romanian_english_all_shuffled_1985_test1000_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmr_romanian_english_all_shuffled_1985_test1000_en.md
new file mode 100644
index 00000000000000..223504e520e52f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmr_romanian_english_all_shuffled_1985_test1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_romanian_english_all_shuffled_1985_test1000 XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_romanian_english_all_shuffled_1985_test1000
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_romanian_english_all_shuffled_1985_test1000` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_romanian_english_all_shuffled_1985_test1000_en_5.5.0_3.0_1725410655707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_romanian_english_all_shuffled_1985_test1000_en_5.5.0_3.0_1725410655707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_romanian_english_all_shuffled_1985_test1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_romanian_english_all_shuffled_1985_test1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_romanian_english_all_shuffled_1985_test1000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|820.3 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-ro-en-all_shuffled-1985-test1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmr_romanian_english_all_shuffled_1985_test1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmr_romanian_english_all_shuffled_1985_test1000_pipeline_en.md
new file mode 100644
index 00000000000000..f3b694cff8bab5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmr_romanian_english_all_shuffled_1985_test1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_romanian_english_all_shuffled_1985_test1000_pipeline pipeline XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_romanian_english_all_shuffled_1985_test1000_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_romanian_english_all_shuffled_1985_test1000_pipeline` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_romanian_english_all_shuffled_1985_test1000_pipeline_en_5.5.0_3.0_1725410776181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_romanian_english_all_shuffled_1985_test1000_pipeline_en_5.5.0_3.0_1725410776181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_romanian_english_all_shuffled_1985_test1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_romanian_english_all_shuffled_1985_test1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_romanian_english_all_shuffled_1985_test1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|820.3 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-ro-en-all_shuffled-1985-test1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_arrandi_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_arrandi_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..585a4b060ebee2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_arrandi_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from arrandi)
+author: John Snow Labs
+name: xlmroberta_ner_arrandi_base_finetuned_panx
+date: 2024-09-04
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `arrandi`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_arrandi_base_finetuned_panx_de_5.5.0_3.0_1725423406223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_arrandi_base_finetuned_panx_de_5.5.0_3.0_1725423406223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_arrandi_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_arrandi_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_arrandi").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_arrandi_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/arrandi/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_arrandi_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_arrandi_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..255400d4c13c68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_arrandi_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_arrandi_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from arrandi
+author: John Snow Labs
+name: xlmroberta_ner_arrandi_base_finetuned_panx_pipeline
+date: 2024-09-04
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_arrandi_base_finetuned_panx_pipeline` is a German model originally trained by arrandi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_arrandi_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725423481574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_arrandi_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725423481574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_arrandi_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_arrandi_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_arrandi_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/arrandi/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_ner_luo.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_ner_luo.md
new file mode 100644
index 00000000000000..a1db16a34ab11f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_ner_luo.md
@@ -0,0 +1,115 @@
+---
+layout: model
+title: Luo (Kenya and Tanzania) XLMRobertaForTokenClassification Base Cased model (from mbeukman)
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_ner
+date: 2024-09-04
+tags: [luo, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: luo
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-ner-luo` is a Luo (Kenya and Tanzania) model originally trained by `mbeukman`.
+
+## Predicted Entities
+
+`DATE`, `PER`, `ORG`, `LOC`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_ner_luo_5.5.0_3.0_1725424704547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_ner_luo_5.5.0_3.0_1725424704547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_ner","luo") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_ner","luo")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("luo.ner.xlmr_roberta.base_finetuned_ner.by_mbeukman").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|luo|
+|Size:|771.9 MB|
+
+## References
+
+References
+
+- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-ner-luo
+- https://arxiv.org/abs/2103.11811
+- https://github.com/Michael-Beukman/NERTransfer
+- https://github.com/masakhane-io/masakhane-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_ner_pipeline_luo.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_ner_pipeline_luo.md
new file mode 100644
index 00000000000000..63970f530f4f72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_ner_pipeline_luo.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Dholuo, Luo (Kenya and Tanzania) xlmroberta_ner_base_finetuned_ner_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_ner_pipeline
+date: 2024-09-04
+tags: [luo, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: luo
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_ner_pipeline` is a Dholuo, Luo (Kenya and Tanzania) model originally trained by mbeukman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_ner_pipeline_luo_5.5.0_3.0_1725424848423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_ner_pipeline_luo_5.5.0_3.0_1725424848423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_ner_pipeline", lang = "luo")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_ner_pipeline", lang = "luo")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|luo|
+|Size:|771.9 MB|
+
+## References
+
+https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-ner-luo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline_wo.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline_wo.md
new file mode 100644
index 00000000000000..07d4cc129b996d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline_wo.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Wolof xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline
+date: 2024-09-04
+tags: [wo, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: wo
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline` is a Wolof model originally trained by mbeukman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline_wo_5.5.0_3.0_1725423619872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline_wo_5.5.0_3.0_1725423619872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline", lang = "wo")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline", lang = "wo")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|wo|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-wolof-finetuned-ner-wolof
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_wo.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_wo.md
new file mode 100644
index 00000000000000..89e569577856ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_wo.md
@@ -0,0 +1,115 @@
+---
+layout: model
+title: Wolof XLMRobertaForTokenClassification Base Cased model (from mbeukman)
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof
+date: 2024-09-04
+tags: [wo, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: wo
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-wolof-finetuned-ner-wolof` is a Wolof model originally trained by `mbeukman`.
+
+## Predicted Entities
+
+`DATE`, `PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_wo_5.5.0_3.0_1725423563497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof_wo_5.5.0_3.0_1725423563497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof","wo") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof","wo")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("wo.ner.xlmr_roberta.base_finetuned_wolof.by_mbeukman").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_wolof_finetuned_ner_wolof|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|wo|
+|Size:|1.0 GB|
+
+## References
+
+References
+
+- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-wolof-finetuned-ner-wolof
+- https://arxiv.org/abs/2103.11811
+- https://github.com/Michael-Beukman/NERTransfer
+- https://github.com/masakhane-io/masakhane-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_jasonyim2_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_jasonyim2_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..dd8d2741807acb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_jasonyim2_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from jasonyim2)
+author: John Snow Labs
+name: xlmroberta_ner_jasonyim2_base_finetuned_panx
+date: 2024-09-04
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `jasonyim2`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jasonyim2_base_finetuned_panx_de_5.5.0_3.0_1725423912509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jasonyim2_base_finetuned_panx_de_5.5.0_3.0_1725423912509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jasonyim2_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_jasonyim2_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_jasonyim2").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_jasonyim2_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/jasonyim2/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..5b100a59ae411f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from jasonyim2
+author: John Snow Labs
+name: xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline
+date: 2024-09-04
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline` is a German model originally trained by jasonyim2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725423989597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725423989597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_jasonyim2_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.4 MB|
+
+## References
+
+https://huggingface.co/jasonyim2/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_leixu_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_leixu_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..906d621b90f9ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_leixu_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from leixu)
+author: John Snow Labs
+name: xlmroberta_ner_leixu_base_finetuned_panx
+date: 2024-09-04
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `leixu`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_leixu_base_finetuned_panx_de_5.5.0_3.0_1725424500637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_leixu_base_finetuned_panx_de_5.5.0_3.0_1725424500637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_leixu_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_leixu_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_leixu").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_leixu_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/leixu/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_leixu_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_leixu_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..b2303f78a9417e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_leixu_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_leixu_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from leixu
+author: John Snow Labs
+name: xlmroberta_ner_leixu_base_finetuned_panx_pipeline
+date: 2024-09-04
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_leixu_base_finetuned_panx_pipeline` is a German model originally trained by leixu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_leixu_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725424574902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_leixu_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725424574902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_leixu_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_leixu_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_leixu_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/leixu/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_all_english_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_all_english_en.md
new file mode 100644
index 00000000000000..ba1975d2d8535b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_all_english_en.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: English XLMRobertaForTokenClassification Base Cased model (from asahi417)
+author: John Snow Labs
+name: xlmroberta_ner_tner_base_all_english
+date: 2024-09-04
+tags: [en, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tner-xlm-roberta-base-all-english` is a English model originally trained by `asahi417`.
+
+## Predicted Entities
+
+`time`, `corporation`, `ordinal number`, `cardinal number`, `rna`, `geopolitical area`, `protein`, `product`, `percent`, `dna`, `disease`, `cell line`, `law`, `other`, `date`, `chemical`, `event`, `work of art`, `cell type`, `location`, `language`, `quantity`, `facility`, `organization`, `group`, `money`, `person`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_all_english_en_5.5.0_3.0_1725423404347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_all_english_en_5.5.0_3.0_1725423404347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_tner_base_all_english","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_tner_base_all_english","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.ner.xlmr_roberta.tner.base.by_asahi417").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_tner_base_all_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/asahi417/tner-xlm-roberta-base-all-english
+- https://github.com/asahi417/tner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_all_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_all_english_pipeline_en.md
new file mode 100644
index 00000000000000..f8c6d77ddd918a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_all_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmroberta_ner_tner_base_all_english_pipeline pipeline XlmRoBertaForTokenClassification from asahi417
+author: John Snow Labs
+name: xlmroberta_ner_tner_base_all_english_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_tner_base_all_english_pipeline` is a English model originally trained by asahi417.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_all_english_pipeline_en_5.5.0_3.0_1725423538262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_all_english_pipeline_en_5.5.0_3.0_1725423538262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_tner_base_all_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_tner_base_all_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_tner_base_all_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/asahi417/tner-xlm-roberta-base-all-english
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_conll2003_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_conll2003_en.md
new file mode 100644
index 00000000000000..c41f3fde0b301d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_conll2003_en.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: English XLMRobertaForTokenClassification Base Cased model (from tner)
+author: John Snow Labs
+name: xlmroberta_ner_tner_base_conll2003
+date: 2024-09-04
+tags: [en, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-conll2003` is a English model originally trained by `tner`.
+
+## Predicted Entities
+
+`other`, `person`, `location`, `organization`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_conll2003_en_5.5.0_3.0_1725424901457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_conll2003_en_5.5.0_3.0_1725424901457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_tner_base_conll2003","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_tner_base_conll2003","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.ner.xlmr_roberta.conll.base").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_tner_base_conll2003|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|792.1 MB|
+
+## References
+
+References
+
+- https://huggingface.co/tner/xlm-roberta-base-conll2003
+- https://github.com/asahi417/tner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_conll2003_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_conll2003_pipeline_en.md
new file mode 100644
index 00000000000000..efa056465d130c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_tner_base_conll2003_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmroberta_ner_tner_base_conll2003_pipeline pipeline XlmRoBertaForTokenClassification from tner
+author: John Snow Labs
+name: xlmroberta_ner_tner_base_conll2003_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_tner_base_conll2003_pipeline` is a English model originally trained by tner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_conll2003_pipeline_en_5.5.0_3.0_1725425033567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_conll2003_pipeline_en_5.5.0_3.0_1725425033567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_tner_base_conll2003_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_tner_base_conll2003_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_tner_base_conll2003_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|792.1 MB|
+
+## References
+
+https://huggingface.co/tner/xlm-roberta-base-conll2003
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline_am.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline_am.md
new file mode 100644
index 00000000000000..78cd06a4d7b4d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline_am.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Amharic xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline
+date: 2024-09-04
+tags: [am, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: am
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline` is a Amharic model originally trained by mbeukman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline_am_5.5.0_3.0_1725423118224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline_am_5.5.0_3.0_1725423118224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline", lang = "am")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline", lang = "am")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|am|
+|Size:|772.3 MB|
+
+## References
+
+https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-ner-amharic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_ner_hrl_nl.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_ner_hrl_nl.md
new file mode 100644
index 00000000000000..ecb08dfc4f42c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_ner_hrl_nl.md
@@ -0,0 +1,117 @@
+---
+layout: model
+title: Dutch Named Entity Recognition (from Davlan)
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_ner_hrl
+date: 2024-09-04
+tags: [xlm_roberta, ner, token_classification, nl, open_source, onnx]
+task: Named Entity Recognition
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Named Entity Recognition model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-ner-hrl` is a Dutch model orginally trained by `Davlan`.
+
+## Predicted Entities
+
+`PER`, `ORG`, `LOC`, `DATE`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_ner_hrl_nl_5.5.0_3.0_1725423110289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_ner_hrl_nl_5.5.0_3.0_1725423110289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_ner_hrl","nl") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["Ik hou van Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_ner_hrl","nl") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("Ik hou van Spark NLP").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("nl.ner.xlmr_roberta.base").predict("""Ik hou van Spark NLP""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_ner_hrl|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|nl|
+|Size:|855.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Davlan/xlm-roberta-base-ner-hrl
+- https://camel.abudhabi.nyu.edu/anercorp/
+- https://www.clips.uantwerpen.be/conll2003/ner/
+- https://www.clips.uantwerpen.be/conll2003/ner/
+- https://www.clips.uantwerpen.be/conll2002/ner/
+- https:
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline_nl.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline_nl.md
new file mode 100644
index 00000000000000..deec994240d247
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline_nl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Dutch, Flemish xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline pipeline XlmRoBertaForTokenClassification from Davlan
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline
+date: 2024-09-04
+tags: [nl, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline` is a Dutch, Flemish model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline_nl_5.5.0_3.0_1725423222842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline_nl_5.5.0_3.0_1725423222842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_ner_hrl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|855.3 MB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-ner-hrl
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline_en.md
new file mode 100644
index 00000000000000..0e992baf11cd36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline` is a English model originally trained by utahnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725468439189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725468439189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_polarity_microsoft_deberta_v3_base_seed_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|666.1 MB|
+
+## References
+
+https://huggingface.co/utahnlp/yelp_polarity_microsoft_deberta-v3-base_seed-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-4_epoch_en.md b/docs/_posts/ahmedlone127/2024-09-05-4_epoch_en.md
new file mode 100644
index 00000000000000..45b0911570d508
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-4_epoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 4_epoch DistilBertForTokenClassification from Gkumi
+author: John Snow Labs
+name: 4_epoch
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`4_epoch` is a English model originally trained by Gkumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/4_epoch_en_5.5.0_3.0_1725506574342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/4_epoch_en_5.5.0_3.0_1725506574342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("4_epoch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("4_epoch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|4_epoch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Gkumi/4-epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-address_extraction_ner_en.md b/docs/_posts/ahmedlone127/2024-09-05-address_extraction_ner_en.md
new file mode 100644
index 00000000000000..a99f8a40ea4f51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-address_extraction_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English address_extraction_ner DistilBertForTokenClassification from kulkarni-harsh
+author: John Snow Labs
+name: address_extraction_ner
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`address_extraction_ner` is a English model originally trained by kulkarni-harsh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/address_extraction_ner_en_5.5.0_3.0_1725495538706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/address_extraction_ner_en_5.5.0_3.0_1725495538706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("address_extraction_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("address_extraction_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|address_extraction_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/kulkarni-harsh/address-extraction-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-adp_model_en.md b/docs/_posts/ahmedlone127/2024-09-05-adp_model_en.md
new file mode 100644
index 00000000000000..9eabdd0da33797
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-adp_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English adp_model DistilBertForSequenceClassification from bitdribble
+author: John Snow Labs
+name: adp_model
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adp_model` is a English model originally trained by bitdribble.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adp_model_en_5.5.0_3.0_1725506982988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adp_model_en_5.5.0_3.0_1725506982988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("adp_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("adp_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adp_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/bitdribble/adp_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ae_detection_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-05-ae_detection_distilbert_en.md
new file mode 100644
index 00000000000000..a0785f5365fda7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ae_detection_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ae_detection_distilbert DistilBertForTokenClassification from merlynjoseph
+author: John Snow Labs
+name: ae_detection_distilbert
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ae_detection_distilbert` is a English model originally trained by merlynjoseph.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ae_detection_distilbert_en_5.5.0_3.0_1725518554948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ae_detection_distilbert_en_5.5.0_3.0_1725518554948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ae_detection_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ae_detection_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ae_detection_distilbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/merlynjoseph/AE-detection-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-afro_xlmr_base_finetuned_kintweetsc_en.md b/docs/_posts/ahmedlone127/2024-09-05-afro_xlmr_base_finetuned_kintweetsc_en.md
new file mode 100644
index 00000000000000..b156b82cdf109f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-afro_xlmr_base_finetuned_kintweetsc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afro_xlmr_base_finetuned_kintweetsc XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: afro_xlmr_base_finetuned_kintweetsc
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_base_finetuned_kintweetsc` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_finetuned_kintweetsc_en_5.5.0_3.0_1725509206107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_finetuned_kintweetsc_en_5.5.0_3.0_1725509206107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_base_finetuned_kintweetsc","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_base_finetuned_kintweetsc","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_base_finetuned_kintweetsc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-base-finetuned-kintweetsC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-afro_xlmr_base_finetuned_kintweetsd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-afro_xlmr_base_finetuned_kintweetsd_pipeline_en.md
new file mode 100644
index 00000000000000..5ee06cc32c8c6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-afro_xlmr_base_finetuned_kintweetsd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afro_xlmr_base_finetuned_kintweetsd_pipeline pipeline XlmRoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: afro_xlmr_base_finetuned_kintweetsd_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_base_finetuned_kintweetsd_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_finetuned_kintweetsd_pipeline_en_5.5.0_3.0_1725509647439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_finetuned_kintweetsd_pipeline_en_5.5.0_3.0_1725509647439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afro_xlmr_base_finetuned_kintweetsd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afro_xlmr_base_finetuned_kintweetsd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_base_finetuned_kintweetsd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-base-finetuned-kintweetsD
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-aift_model_en.md b/docs/_posts/ahmedlone127/2024-09-05-aift_model_en.md
new file mode 100644
index 00000000000000..b63bf460583a12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-aift_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English aift_model DistilBertForSequenceClassification from Cielciel
+author: John Snow Labs
+name: aift_model
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aift_model` is a English model originally trained by Cielciel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aift_model_en_5.5.0_3.0_1725507647209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aift_model_en_5.5.0_3.0_1725507647209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("aift_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("aift_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aift_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Cielciel/aift-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-albert_base_v2_ner_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-05-albert_base_v2_ner_finetuned_en.md
new file mode 100644
index 00000000000000..beca3f8b97a4f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-albert_base_v2_ner_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_ner_finetuned AlbertForTokenClassification from retr00h
+author: John Snow Labs
+name: albert_base_v2_ner_finetuned
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, albert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_ner_finetuned` is a English model originally trained by retr00h.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_ner_finetuned_en_5.5.0_3.0_1725503665299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_ner_finetuned_en_5.5.0_3.0_1725503665299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = AlbertForTokenClassification.pretrained("albert_base_v2_ner_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = AlbertForTokenClassification.pretrained("albert_base_v2_ner_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_ner_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|42.3 MB|
+
+## References
+
+https://huggingface.co/retr00h/albert-base-v2-NER-FINETUNED
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-albert_base_v2_ner_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-albert_base_v2_ner_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..3e707ea05737e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-albert_base_v2_ner_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_v2_ner_finetuned_pipeline pipeline AlbertForTokenClassification from retr00h
+author: John Snow Labs
+name: albert_base_v2_ner_finetuned_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_ner_finetuned_pipeline` is a English model originally trained by retr00h.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_ner_finetuned_pipeline_en_5.5.0_3.0_1725503667722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_ner_finetuned_pipeline_en_5.5.0_3.0_1725503667722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_v2_ner_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_v2_ner_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_ner_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.3 MB|
+
+## References
+
+https://huggingface.co/retr00h/albert-base-v2-NER-FINETUNED
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-albert_emotion_sangmitra_06_en.md b/docs/_posts/ahmedlone127/2024-09-05-albert_emotion_sangmitra_06_en.md
new file mode 100644
index 00000000000000..ba3f3f9b5d1090
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-albert_emotion_sangmitra_06_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_emotion_sangmitra_06 AlbertForSequenceClassification from Sangmitra-06
+author: John Snow Labs
+name: albert_emotion_sangmitra_06
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_emotion_sangmitra_06` is a English model originally trained by Sangmitra-06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_emotion_sangmitra_06_en_5.5.0_3.0_1725510042699.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_emotion_sangmitra_06_en_5.5.0_3.0_1725510042699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_emotion_sangmitra_06","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_emotion_sangmitra_06", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_emotion_sangmitra_06|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/Sangmitra-06/Albert_emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-albert_emotion_sangmitra_06_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-albert_emotion_sangmitra_06_pipeline_en.md
new file mode 100644
index 00000000000000..d229e5fc4d64df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-albert_emotion_sangmitra_06_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_emotion_sangmitra_06_pipeline pipeline AlbertForSequenceClassification from Sangmitra-06
+author: John Snow Labs
+name: albert_emotion_sangmitra_06_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_emotion_sangmitra_06_pipeline` is a English model originally trained by Sangmitra-06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_emotion_sangmitra_06_pipeline_en_5.5.0_3.0_1725510045087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_emotion_sangmitra_06_pipeline_en_5.5.0_3.0_1725510045087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_emotion_sangmitra_06_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_emotion_sangmitra_06_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_emotion_sangmitra_06_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.3 MB|
+
+## References
+
+https://huggingface.co/Sangmitra-06/Albert_emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-albert_persian_farsi_zwnj_base_v2_ner_fa.md b/docs/_posts/ahmedlone127/2024-09-05-albert_persian_farsi_zwnj_base_v2_ner_fa.md
new file mode 100644
index 00000000000000..57de69496cedad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-albert_persian_farsi_zwnj_base_v2_ner_fa.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: Persian albert_persian_farsi_zwnj_base_v2_ner AlbertForTokenClassification from HooshvareLab
+author: John Snow Labs
+name: albert_persian_farsi_zwnj_base_v2_ner
+date: 2024-09-05
+tags: [albert, fa, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_persian_farsi_zwnj_base_v2_ner` is a Persian model originally trained by HooshvareLab.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_zwnj_base_v2_ner_fa_5.5.0_3.0_1725511383644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_zwnj_base_v2_ner_fa_5.5.0_3.0_1725511383644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+sequenceClassifier = AlbertForTokenClassification.pretrained("albert_persian_farsi_zwnj_base_v2_ner","fa") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([document_assembler, sequenceClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val sequenceClassifier = AlbertForTokenClassification  
+    .pretrained("albert_persian_farsi_zwnj_base_v2_ner", "fa")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, sequenceClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_persian_farsi_zwnj_base_v2_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|fa|
+|Size:|41.9 MB|
+
+## References
+
+References
+
+https://huggingface.co/HooshvareLab/albert-fa-zwnj-base-v2-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-albert_persian_farsi_zwnj_base_v2_ner_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-05-albert_persian_farsi_zwnj_base_v2_ner_pipeline_fa.md
new file mode 100644
index 00000000000000..c45874c3b6c25e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-albert_persian_farsi_zwnj_base_v2_ner_pipeline_fa.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Persian albert_persian_farsi_zwnj_base_v2_ner_pipeline pipeline BertForTokenClassification from HooshvareLab
+author: John Snow Labs
+name: albert_persian_farsi_zwnj_base_v2_ner_pipeline
+date: 2024-09-05
+tags: [fa, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_persian_farsi_zwnj_base_v2_ner_pipeline` is a Persian model originally trained by HooshvareLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_zwnj_base_v2_ner_pipeline_fa_5.5.0_3.0_1725511386044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_persian_farsi_zwnj_base_v2_ner_pipeline_fa_5.5.0_3.0_1725511386044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_persian_farsi_zwnj_base_v2_ner_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_persian_farsi_zwnj_base_v2_ner_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_persian_farsi_zwnj_base_v2_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|41.9 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/albert-fa-zwnj-base-v2-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-albert_xxlarge_v2_disaster_twitter_v2_en.md b/docs/_posts/ahmedlone127/2024-09-05-albert_xxlarge_v2_disaster_twitter_v2_en.md
new file mode 100644
index 00000000000000..d02454a58d9012
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-albert_xxlarge_v2_disaster_twitter_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_xxlarge_v2_disaster_twitter_v2 AlbertForSequenceClassification from JiaJiaCen
+author: John Snow Labs
+name: albert_xxlarge_v2_disaster_twitter_v2
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_xxlarge_v2_disaster_twitter_v2` is a English model originally trained by JiaJiaCen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_xxlarge_v2_disaster_twitter_v2_en_5.5.0_3.0_1725510330673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_xxlarge_v2_disaster_twitter_v2_en_5.5.0_3.0_1725510330673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_xxlarge_v2_disaster_twitter_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_xxlarge_v2_disaster_twitter_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_xxlarge_v2_disaster_twitter_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|833.9 MB|
+
+## References
+
+https://huggingface.co/JiaJiaCen/albert-xxlarge-v2-disaster-twitter-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-albert_xxlarge_v2_disaster_twitter_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-albert_xxlarge_v2_disaster_twitter_v2_pipeline_en.md
new file mode 100644
index 00000000000000..26b51ba03d81e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-albert_xxlarge_v2_disaster_twitter_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_xxlarge_v2_disaster_twitter_v2_pipeline pipeline AlbertForSequenceClassification from JiaJiaCen
+author: John Snow Labs
+name: albert_xxlarge_v2_disaster_twitter_v2_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_xxlarge_v2_disaster_twitter_v2_pipeline` is a English model originally trained by JiaJiaCen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_xxlarge_v2_disaster_twitter_v2_pipeline_en_5.5.0_3.0_1725510369771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_xxlarge_v2_disaster_twitter_v2_pipeline_en_5.5.0_3.0_1725510369771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_xxlarge_v2_disaster_twitter_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_xxlarge_v2_disaster_twitter_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_xxlarge_v2_disaster_twitter_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.9 MB|
+
+## References
+
+https://huggingface.co/JiaJiaCen/albert-xxlarge-v2-disaster-twitter-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-arabic_ner_ace_ar.md b/docs/_posts/ahmedlone127/2024-09-05-arabic_ner_ace_ar.md
new file mode 100644
index 00000000000000..b00322b7a048bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-arabic_ner_ace_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic arabic_ner_ace BertForTokenClassification from ychenNLP
+author: John Snow Labs
+name: arabic_ner_ace
+date: 2024-09-05
+tags: [ar, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_ner_ace` is a Arabic model originally trained by ychenNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabic_ner_ace_ar_5.5.0_3.0_1725510939060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_ner_ace_ar_5.5.0_3.0_1725510939060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("arabic_ner_ace","ar") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("arabic_ner_ace", "ar")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabic_ner_ace|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ar|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/ychenNLP/arabic-ner-ace
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-autofill_ner_en.md b/docs/_posts/ahmedlone127/2024-09-05-autofill_ner_en.md
new file mode 100644
index 00000000000000..ab064af1b19304
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-autofill_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autofill_ner DistilBertForTokenClassification from gouravchat
+author: John Snow Labs
+name: autofill_ner
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autofill_ner` is a English model originally trained by gouravchat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autofill_ner_en_5.5.0_3.0_1725500904831.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autofill_ner_en_5.5.0_3.0_1725500904831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("autofill_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("autofill_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autofill_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gouravchat/autofill-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-b_base_x2_en.md b/docs/_posts/ahmedlone127/2024-09-05-b_base_x2_en.md
new file mode 100644
index 00000000000000..19fc5c828e0859
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-b_base_x2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English b_base_x2 AlbertForSequenceClassification from damgomz
+author: John Snow Labs
+name: b_base_x2
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`b_base_x2` is a English model originally trained by damgomz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/b_base_x2_en_5.5.0_3.0_1725510228572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/b_base_x2_en_5.5.0_3.0_1725510228572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("b_base_x2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("b_base_x2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|b_base_x2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|70.7 MB|
+
+## References
+
+https://huggingface.co/damgomz/B_base_x2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-b_base_x2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-b_base_x2_pipeline_en.md
new file mode 100644
index 00000000000000..6bb597f5a8a7b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-b_base_x2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English b_base_x2_pipeline pipeline AlbertForSequenceClassification from damgomz
+author: John Snow Labs
+name: b_base_x2_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`b_base_x2_pipeline` is a English model originally trained by damgomz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/b_base_x2_pipeline_en_5.5.0_3.0_1725510232448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/b_base_x2_pipeline_en_5.5.0_3.0_1725510232448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("b_base_x2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("b_base_x2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|b_base_x2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|70.8 MB|
+
+## References
+
+https://huggingface.co/damgomz/B_base_x2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bangla_twoclass_sentiment_analyzer_en.md b/docs/_posts/ahmedlone127/2024-09-05-bangla_twoclass_sentiment_analyzer_en.md
new file mode 100644
index 00000000000000..3ef7d238095bcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bangla_twoclass_sentiment_analyzer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bangla_twoclass_sentiment_analyzer XlmRoBertaForSequenceClassification from Arunavaonly
+author: John Snow Labs
+name: bangla_twoclass_sentiment_analyzer
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bangla_twoclass_sentiment_analyzer` is a English model originally trained by Arunavaonly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bangla_twoclass_sentiment_analyzer_en_5.5.0_3.0_1725515101061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bangla_twoclass_sentiment_analyzer_en_5.5.0_3.0_1725515101061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bangla_twoclass_sentiment_analyzer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bangla_twoclass_sentiment_analyzer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bangla_twoclass_sentiment_analyzer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|812.7 MB|
+
+## References
+
+https://huggingface.co/Arunavaonly/Bangla-twoclass-Sentiment-Analyzer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bengali_multi_bn.md b/docs/_posts/ahmedlone127/2024-09-05-bengali_multi_bn.md
new file mode 100644
index 00000000000000..e49080e206cf59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bengali_multi_bn.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Bengali bengali_multi XlmRoBertaForQuestionAnswering from simoneZethof
+author: John Snow Labs
+name: bengali_multi
+date: 2024-09-05
+tags: [bn, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: bn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bengali_multi` is a Bengali model originally trained by simoneZethof.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bengali_multi_bn_5.5.0_3.0_1725499859379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bengali_multi_bn_5.5.0_3.0_1725499859379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("bengali_multi","bn") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("bengali_multi", "bn")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bengali_multi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|bn|
+|Size:|836.9 MB|
+
+## References
+
+https://huggingface.co/simoneZethof/Bengali_multi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bengali_multi_pipeline_bn.md b/docs/_posts/ahmedlone127/2024-09-05-bengali_multi_pipeline_bn.md
new file mode 100644
index 00000000000000..68a6cd076a285f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bengali_multi_pipeline_bn.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Bengali bengali_multi_pipeline pipeline XlmRoBertaForQuestionAnswering from simoneZethof
+author: John Snow Labs
+name: bengali_multi_pipeline
+date: 2024-09-05
+tags: [bn, open_source, pipeline, onnx]
+task: Question Answering
+language: bn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bengali_multi_pipeline` is a Bengali model originally trained by simoneZethof.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bengali_multi_pipeline_bn_5.5.0_3.0_1725499930112.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bengali_multi_pipeline_bn_5.5.0_3.0_1725499930112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bengali_multi_pipeline", lang = "bn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bengali_multi_pipeline", lang = "bn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bengali_multi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bn|
+|Size:|836.9 MB|
+
+## References
+
+https://huggingface.co/simoneZethof/Bengali_multi
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bent_pubmedbert_ner_gene_en.md b/docs/_posts/ahmedlone127/2024-09-05-bent_pubmedbert_ner_gene_en.md
new file mode 100644
index 00000000000000..dedb8c76d1329e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bent_pubmedbert_ner_gene_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English bent_pubmedbert_ner_gene BertForTokenClassification from pruas
+author: John Snow Labs
+name: bent_pubmedbert_ner_gene
+date: 2024-09-05
+tags: [bert, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bent_pubmedbert_ner_gene` is a English model originally trained by pruas.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bent_pubmedbert_ner_gene_en_5.5.0_3.0_1725516000741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bent_pubmedbert_ner_gene_en_5.5.0_3.0_1725516000741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = BertForTokenClassification.pretrained("bent_pubmedbert_ner_gene","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = BertForTokenClassification  
+    .pretrained("bent_pubmedbert_ner_gene", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bent_pubmedbert_ner_gene|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|260.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/pruas/BENT-PubMedBERT-NER-Gene
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bent_pubmedbert_ner_gene_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bent_pubmedbert_ner_gene_pipeline_en.md
new file mode 100644
index 00000000000000..a6f75e3004266f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bent_pubmedbert_ner_gene_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bent_pubmedbert_ner_gene_pipeline pipeline BertForTokenClassification from sbarnettGE
+author: John Snow Labs
+name: bent_pubmedbert_ner_gene_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bent_pubmedbert_ner_gene_pipeline` is a English model originally trained by sbarnettGE.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bent_pubmedbert_ner_gene_pipeline_en_5.5.0_3.0_1725516080454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bent_pubmedbert_ner_gene_pipeline_en_5.5.0_3.0_1725516080454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bent_pubmedbert_ner_gene_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bent_pubmedbert_ner_gene_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bent_pubmedbert_ner_gene_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|260.0 MB|
+
+## References
+
+https://huggingface.co/sbarnettGE/BENT-PubMedBERT-NER-Gene
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_base_german_uncased_dbmdz_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-05-bert_base_german_uncased_dbmdz_pipeline_de.md
new file mode 100644
index 00000000000000..4d5c44d48c3765
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_base_german_uncased_dbmdz_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German bert_base_german_uncased_dbmdz_pipeline pipeline BertEmbeddings from dbmdz
+author: John Snow Labs
+name: bert_base_german_uncased_dbmdz_pipeline
+date: 2024-09-05
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_uncased_dbmdz_pipeline` is a German model originally trained by dbmdz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_uncased_dbmdz_pipeline_de_5.5.0_3.0_1725519656772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_uncased_dbmdz_pipeline_de_5.5.0_3.0_1725519656772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_german_uncased_dbmdz_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_german_uncased_dbmdz_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_uncased_dbmdz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/dbmdz/bert-base-german-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_base_multilingual_cased_finetuned_ner_harem_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-05-bert_base_multilingual_cased_finetuned_ner_harem_pipeline_xx.md
new file mode 100644
index 00000000000000..145dd664fbdd2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_base_multilingual_cased_finetuned_ner_harem_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_finetuned_ner_harem_pipeline pipeline BertForTokenClassification from GuiTap
+author: John Snow Labs
+name: bert_base_multilingual_cased_finetuned_ner_harem_pipeline
+date: 2024-09-05
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_ner_harem_pipeline` is a Multilingual model originally trained by GuiTap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_ner_harem_pipeline_xx_5.5.0_3.0_1725515897119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_ner_harem_pipeline_xx_5.5.0_3.0_1725515897119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_ner_harem_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_ner_harem_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_finetuned_ner_harem_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/GuiTap/bert-base-multilingual-cased-finetuned-ner-harem
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_based_turkish_ner_wikiann_tr.md b/docs/_posts/ahmedlone127/2024-09-05-bert_based_turkish_ner_wikiann_tr.md
new file mode 100644
index 00000000000000..ab1223436b09ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_based_turkish_ner_wikiann_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish bert_based_turkish_ner_wikiann BertForTokenClassification from Gorengoz
+author: John Snow Labs
+name: bert_based_turkish_ner_wikiann
+date: 2024-09-05
+tags: [tr, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_based_turkish_ner_wikiann` is a Turkish model originally trained by Gorengoz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_based_turkish_ner_wikiann_tr_5.5.0_3.0_1725511667643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_based_turkish_ner_wikiann_tr_5.5.0_3.0_1725511667643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_based_turkish_ner_wikiann","tr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_based_turkish_ner_wikiann", "tr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_based_turkish_ner_wikiann|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|tr|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/Gorengoz/bert-based-Turkish-NER-wikiann
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_emotion_gyvertc_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_emotion_gyvertc_en.md
new file mode 100644
index 00000000000000..b66cff7732c72b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_emotion_gyvertc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_emotion_gyvertc DistilBertForSequenceClassification from GyverTc
+author: John Snow Labs
+name: bert_emotion_gyvertc
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_emotion_gyvertc` is a English model originally trained by GyverTc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_emotion_gyvertc_en_5.5.0_3.0_1725507099181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_emotion_gyvertc_en_5.5.0_3.0_1725507099181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_emotion_gyvertc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_emotion_gyvertc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_emotion_gyvertc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/GyverTc/bert-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_emotion_gyvertc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_emotion_gyvertc_pipeline_en.md
new file mode 100644
index 00000000000000..b7d0d26f839d4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_emotion_gyvertc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_emotion_gyvertc_pipeline pipeline DistilBertForSequenceClassification from GyverTc
+author: John Snow Labs
+name: bert_emotion_gyvertc_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_emotion_gyvertc_pipeline` is a English model originally trained by GyverTc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_emotion_gyvertc_pipeline_en_5.5.0_3.0_1725507111011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_emotion_gyvertc_pipeline_en_5.5.0_3.0_1725507111011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_emotion_gyvertc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_emotion_gyvertc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_emotion_gyvertc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/GyverTc/bert-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_clinical_plncmm_large_25_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_clinical_plncmm_large_25_en.md
new file mode 100644
index 00000000000000..3379b9517b7a93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_clinical_plncmm_large_25_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_clinical_plncmm_large_25 BertForTokenClassification from crisU8
+author: John Snow Labs
+name: bert_finetuned_ner_clinical_plncmm_large_25
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_clinical_plncmm_large_25` is a English model originally trained by crisU8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_clinical_plncmm_large_25_en_5.5.0_3.0_1725511068891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_clinical_plncmm_large_25_en_5.5.0_3.0_1725511068891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_clinical_plncmm_large_25","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_clinical_plncmm_large_25", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_clinical_plncmm_large_25|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/crisU8/bert-finetuned-ner-clinical-plncmm-large-25
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_july_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_july_pipeline_en.md
new file mode 100644
index 00000000000000..0c2cf0ff2e7116
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_july_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_july_pipeline pipeline DistilBertForTokenClassification from Amhyr
+author: John Snow Labs
+name: bert_finetuned_ner_july_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_july_pipeline` is a English model originally trained by Amhyr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_july_pipeline_en_5.5.0_3.0_1725506552805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_july_pipeline_en_5.5.0_3.0_1725506552805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_july_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_july_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_july_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/Amhyr/bert-finetuned-ner_july
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_gemma_2_2b_italian_imdb_2bit_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_gemma_2_2b_italian_imdb_2bit_0_pipeline_en.md
new file mode 100644
index 00000000000000..8afd6d5f9a822b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_gemma_2_2b_italian_imdb_2bit_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_gemma_2_2b_italian_imdb_2bit_0_pipeline pipeline DistilBertForSequenceClassification from jvelja
+author: John Snow Labs
+name: bert_gemma_2_2b_italian_imdb_2bit_0_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_gemma_2_2b_italian_imdb_2bit_0_pipeline` is a English model originally trained by jvelja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_gemma_2_2b_italian_imdb_2bit_0_pipeline_en_5.5.0_3.0_1725507032805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_gemma_2_2b_italian_imdb_2bit_0_pipeline_en_5.5.0_3.0_1725507032805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_gemma_2_2b_italian_imdb_2bit_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_gemma_2_2b_italian_imdb_2bit_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_gemma_2_2b_italian_imdb_2bit_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jvelja/BERT_gemma-2-2b-it_imdb_2bit_0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_kor_base_ko.md b/docs/_posts/ahmedlone127/2024-09-05-bert_kor_base_ko.md
new file mode 100644
index 00000000000000..a600fee18de3c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_kor_base_ko.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Korean bert_kor_base BertEmbeddings from kykim
+author: John Snow Labs
+name: bert_kor_base
+date: 2024-09-05
+tags: [ko, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_kor_base` is a Korean model originally trained by kykim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_kor_base_ko_5.5.0_3.0_1725519472814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_kor_base_ko_5.5.0_3.0_1725519472814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_kor_base","ko") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_kor_base","ko") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_kor_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|ko|
+|Size:|441.2 MB|
+
+## References
+
+https://huggingface.co/kykim/bert-kor-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_kor_base_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-05-bert_kor_base_pipeline_ko.md
new file mode 100644
index 00000000000000..6e4d241662a1ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_kor_base_pipeline_ko.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Korean bert_kor_base_pipeline pipeline BertEmbeddings from kykim
+author: John Snow Labs
+name: bert_kor_base_pipeline
+date: 2024-09-05
+tags: [ko, open_source, pipeline, onnx]
+task: Embeddings
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_kor_base_pipeline` is a Korean model originally trained by kykim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_kor_base_pipeline_ko_5.5.0_3.0_1725519493705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_kor_base_pipeline_ko_5.5.0_3.0_1725519493705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_kor_base_pipeline", lang = "ko")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_kor_base_pipeline", lang = "ko")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_kor_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ko|
+|Size:|441.2 MB|
+
+## References
+
+https://huggingface.co/kykim/bert-kor-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-05-bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx.md
new file mode 100644
index 00000000000000..1dffe1ade14321
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline pipeline BertForTokenClassification from StivenLancheros
+author: John Snow Labs
+name: bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline
+date: 2024-09-05
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline` is a Multilingual model originally trained by StivenLancheros.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx_5.5.0_3.0_1725511073548.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline_xx_5.5.0_3.0_1725511073548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_biobert_base_cased_v1.2_finetuned_ner_craft_augmentedtransfer_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/StivenLancheros/biobert-base-cased-v1.2-finetuned-ner-CRAFT_AugmentedTransfer_EN
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_ner_rubertconv_toxic_editor_ru.md b/docs/_posts/ahmedlone127/2024-09-05-bert_ner_rubertconv_toxic_editor_ru.md
new file mode 100644
index 00000000000000..3842060004c3f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_ner_rubertconv_toxic_editor_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian bert_ner_rubertconv_toxic_editor BertForTokenClassification from IlyaGusev
+author: John Snow Labs
+name: bert_ner_rubertconv_toxic_editor
+date: 2024-09-05
+tags: [ru, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_rubertconv_toxic_editor` is a Russian model originally trained by IlyaGusev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_rubertconv_toxic_editor_ru_5.5.0_3.0_1725511141204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_rubertconv_toxic_editor_ru_5.5.0_3.0_1725511141204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_rubertconv_toxic_editor","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_rubertconv_toxic_editor", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_rubertconv_toxic_editor|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ru|
+|Size:|662.2 MB|
+
+## References
+
+https://huggingface.co/IlyaGusev/rubertconv_toxic_editor
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_reddit_ner_place_names_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_reddit_ner_place_names_en.md
new file mode 100644
index 00000000000000..56f9adbdc6d937
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_reddit_ner_place_names_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English BertForTokenClassification Cased model (from cjber)
+author: John Snow Labs
+name: bert_token_classifier_reddit_ner_place_names
+date: 2024-09-05
+tags: [en, open_source, bert, token_classification, ner, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `reddit-ner-place_names` is a English model originally trained by `cjber`.
+
+## Predicted Entities
+
+`location`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_reddit_ner_place_names_en_5.5.0_3.0_1725511609017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_reddit_ner_place_names_en_5.5.0_3.0_1725511609017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_reddit_ner_place_names","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_reddit_ner_place_names","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_reddit_ner_place_names|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/cjber/reddit-ner-place_names
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_uncased_keyword_discriminator_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_uncased_keyword_discriminator_en.md
new file mode 100644
index 00000000000000..cea2de40a6ddea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_uncased_keyword_discriminator_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English BertForTokenClassification Uncased model (from yanekyuk)
+author: John Snow Labs
+name: bert_token_classifier_uncased_keyword_discriminator
+date: 2024-09-05
+tags: [en, open_source, bert, token_classification, ner, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-uncased-keyword-discriminator` is a English model originally trained by `yanekyuk`.
+
+## Predicted Entities
+
+`ENT`, `CON`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_token_classifier_uncased_keyword_discriminator_en_5.5.0_3.0_1725511552240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_uncased_keyword_discriminator_en_5.5.0_3.0_1725511552240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_uncased_keyword_discriminator","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_uncased_keyword_discriminator","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_uncased_keyword_discriminator|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/yanekyuk/bert-uncased-keyword-discriminator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_9k_1k_e1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_9k_1k_e1_pipeline_en.md
new file mode 100644
index 00000000000000..996c06405bcee2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_9k_1k_e1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_citi_dataset_9k_1k_e1_pipeline pipeline BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_citi_dataset_9k_1k_e1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_citi_dataset_9k_1k_e1_pipeline` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_9k_1k_e1_pipeline_en_5.5.0_3.0_1725517330856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_9k_1k_e1_pipeline_en_5.5.0_3.0_1725517330856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_citi_dataset_9k_1k_e1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_citi_dataset_9k_1k_e1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_citi_dataset_9k_1k_e1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|391.7 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-citi-dataset-9k-1k-e1
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_detailed_9k_1_5k_e1_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_detailed_9k_1_5k_e1_en.md
new file mode 100644
index 00000000000000..f3de717b89e2a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_detailed_9k_1_5k_e1_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_citi_dataset_detailed_9k_1_5k_e1 BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_citi_dataset_detailed_9k_1_5k_e1
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_citi_dataset_detailed_9k_1_5k_e1` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_detailed_9k_1_5k_e1_en_5.5.0_3.0_1725517004720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_detailed_9k_1_5k_e1_en_5.5.0_3.0_1725517004720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_citi_dataset_detailed_9k_1_5k_e1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_citi_dataset_detailed_9k_1_5k_e1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_citi_dataset_detailed_9k_1_5k_e1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|391.6 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-citi-dataset-detailed-9k-1_5k-e1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline_en.md
new file mode 100644
index 00000000000000..7c99d05ca50d1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline pipeline BGEEmbeddings from MugheesAwan11
+author: John Snow Labs
+name: bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline` is a English model originally trained by MugheesAwan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline_en_5.5.0_3.0_1725517032454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline_en_5.5.0_3.0_1725517032454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_citi_dataset_detailed_9k_1_5k_e1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|391.6 MB|
+
+## References
+
+https://huggingface.co/MugheesAwan11/bge-base-citi-dataset-detailed-9k-1_5k-e1
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_adarshheg_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_adarshheg_en.md
new file mode 100644
index 00000000000000..586be2d124e781
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_adarshheg_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_adarshheg BGEEmbeddings from adarshheg
+author: John Snow Labs
+name: bge_base_financial_matryoshka_adarshheg
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_adarshheg` is a English model originally trained by adarshheg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_adarshheg_en_5.5.0_3.0_1725517486699.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_adarshheg_en_5.5.0_3.0_1725517486699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_adarshheg","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_adarshheg","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_adarshheg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|382.5 MB|
+
+## References
+
+https://huggingface.co/adarshheg/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_adarshheg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_adarshheg_pipeline_en.md
new file mode 100644
index 00000000000000..e52842b7fe698d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_adarshheg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_adarshheg_pipeline pipeline BGEEmbeddings from adarshheg
+author: John Snow Labs
+name: bge_base_financial_matryoshka_adarshheg_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_adarshheg_pipeline` is a English model originally trained by adarshheg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_adarshheg_pipeline_en_5.5.0_3.0_1725517514473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_adarshheg_pipeline_en_5.5.0_3.0_1725517514473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_adarshheg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_adarshheg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_adarshheg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|382.5 MB|
+
+## References
+
+https://huggingface.co/adarshheg/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_ethan_ky_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_ethan_ky_pipeline_en.md
new file mode 100644
index 00000000000000..b1689cc74b066f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_ethan_ky_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_ethan_ky_pipeline pipeline BGEEmbeddings from ethan-ky
+author: John Snow Labs
+name: bge_base_financial_matryoshka_ethan_ky_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_ethan_ky_pipeline` is a English model originally trained by ethan-ky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_ethan_ky_pipeline_en_5.5.0_3.0_1725517604889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_ethan_ky_pipeline_en_5.5.0_3.0_1725517604889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_ethan_ky_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_ethan_ky_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_ethan_ky_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|256.0 MB|
+
+## References
+
+https://huggingface.co/ethan-ky/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_uhoffmann_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_uhoffmann_en.md
new file mode 100644
index 00000000000000..432040f393f257
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_uhoffmann_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_uhoffmann BGEEmbeddings from uhoffmann
+author: John Snow Labs
+name: bge_base_financial_matryoshka_uhoffmann
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_uhoffmann` is a English model originally trained by uhoffmann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_uhoffmann_en_5.5.0_3.0_1725516861782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_uhoffmann_en_5.5.0_3.0_1725516861782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_uhoffmann","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_uhoffmann","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_uhoffmann|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/uhoffmann/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_uhoffmann_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_uhoffmann_pipeline_en.md
new file mode 100644
index 00000000000000..782bc6d0b52e66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_base_financial_matryoshka_uhoffmann_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_uhoffmann_pipeline pipeline BGEEmbeddings from uhoffmann
+author: John Snow Labs
+name: bge_base_financial_matryoshka_uhoffmann_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_uhoffmann_pipeline` is a English model originally trained by uhoffmann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_uhoffmann_pipeline_en_5.5.0_3.0_1725516887972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_uhoffmann_pipeline_en_5.5.0_3.0_1725516887972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_uhoffmann_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_uhoffmann_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_uhoffmann_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/uhoffmann/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_large_chinese_v1_6_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_large_chinese_v1_6_en.md
new file mode 100644
index 00000000000000..d40307a7b1d717
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_large_chinese_v1_6_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_large_chinese_v1_6 BGEEmbeddings from clinno
+author: John Snow Labs
+name: bge_large_chinese_v1_6
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_chinese_v1_6` is a English model originally trained by clinno.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_chinese_v1_6_en_5.5.0_3.0_1725516938853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_chinese_v1_6_en_5.5.0_3.0_1725516938853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_large_chinese_v1_6","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_large_chinese_v1_6","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_large_chinese_v1_6|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/clinno/bge-large-zh-v1.6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_large_english_world_news_osint_v1_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_large_english_world_news_osint_v1_en.md
new file mode 100644
index 00000000000000..100383ae844ca3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_large_english_world_news_osint_v1_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_large_english_world_news_osint_v1 BGEEmbeddings from jaschadub
+author: John Snow Labs
+name: bge_large_english_world_news_osint_v1
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_world_news_osint_v1` is a English model originally trained by jaschadub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_world_news_osint_v1_en_5.5.0_3.0_1725517661348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_world_news_osint_v1_en_5.5.0_3.0_1725517661348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_large_english_world_news_osint_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_large_english_world_news_osint_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_large_english_world_news_osint_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|795.1 MB|
+
+## References
+
+https://huggingface.co/jaschadub/bge-large-en-world-news-osint-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_large_english_world_news_osint_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_large_english_world_news_osint_v1_pipeline_en.md
new file mode 100644
index 00000000000000..5d51a2c0174fc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_large_english_world_news_osint_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_large_english_world_news_osint_v1_pipeline pipeline BGEEmbeddings from jaschadub
+author: John Snow Labs
+name: bge_large_english_world_news_osint_v1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_english_world_news_osint_v1_pipeline` is a English model originally trained by jaschadub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_english_world_news_osint_v1_pipeline_en_5.5.0_3.0_1725517890944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_english_world_news_osint_v1_pipeline_en_5.5.0_3.0_1725517890944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_large_english_world_news_osint_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_large_english_world_news_osint_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_large_english_world_news_osint_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.1 MB|
+
+## References
+
+https://huggingface.co/jaschadub/bge-large-en-world-news-osint-v1
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_micro_v2_esg_v2_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_micro_v2_esg_v2_en.md
new file mode 100644
index 00000000000000..b7de8d47003f52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_micro_v2_esg_v2_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_micro_v2_esg_v2 BGEEmbeddings from elsayovita
+author: John Snow Labs
+name: bge_micro_v2_esg_v2
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_micro_v2_esg_v2` is a English model originally trained by elsayovita.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_micro_v2_esg_v2_en_5.5.0_3.0_1725516827110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_micro_v2_esg_v2_en_5.5.0_3.0_1725516827110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_micro_v2_esg_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_micro_v2_esg_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_micro_v2_esg_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|55.4 MB|
+
+## References
+
+https://huggingface.co/elsayovita/bge-micro-v2-esg-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_small_bioasq_3epochs_batch32_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_small_bioasq_3epochs_batch32_en.md
new file mode 100644
index 00000000000000..78d7d9e0e506a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_small_bioasq_3epochs_batch32_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_bioasq_3epochs_batch32 BGEEmbeddings from juanpablomesa
+author: John Snow Labs
+name: bge_small_bioasq_3epochs_batch32
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_3epochs_batch32` is a English model originally trained by juanpablomesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_3epochs_batch32_en_5.5.0_3.0_1725517296545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_3epochs_batch32_en_5.5.0_3.0_1725517296545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_3epochs_batch32","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_3epochs_batch32","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_bioasq_3epochs_batch32|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|115.7 MB|
+
+## References
+
+https://huggingface.co/juanpablomesa/bge-small-bioasq-3epochs-batch32
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_small_english_v1_5_esg_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_small_english_v1_5_esg_en.md
new file mode 100644
index 00000000000000..35a4487e2db784
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_small_english_v1_5_esg_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_english_v1_5_esg BGEEmbeddings from elsayovita
+author: John Snow Labs
+name: bge_small_english_v1_5_esg
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_esg` is a English model originally trained by elsayovita.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_esg_en_5.5.0_3.0_1725517146412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_esg_en_5.5.0_3.0_1725517146412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_esg","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_esg","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_esg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|115.1 MB|
+
+## References
+
+https://huggingface.co/elsayovita/bge-small-en-v1.5-esg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bge_small_english_v1_5_esg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bge_small_english_v1_5_esg_pipeline_en.md
new file mode 100644
index 00000000000000..eb537e1b05f551
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bge_small_english_v1_5_esg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_english_v1_5_esg_pipeline pipeline BGEEmbeddings from elsayovita
+author: John Snow Labs
+name: bge_small_english_v1_5_esg_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_esg_pipeline` is a English model originally trained by elsayovita.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_esg_pipeline_en_5.5.0_3.0_1725517156329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_esg_pipeline_en_5.5.0_3.0_1725517156329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_english_v1_5_esg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_english_v1_5_esg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_esg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|115.1 MB|
+
+## References
+
+https://huggingface.co/elsayovita/bge-small-en-v1.5-esg
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_base_uncased_abstract_fulltext_en.md b/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_base_uncased_abstract_fulltext_en.md
new file mode 100644
index 00000000000000..8b07bb56e9669f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_base_uncased_abstract_fulltext_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biomednlp_biomedbert_base_uncased_abstract_fulltext BertEmbeddings from microsoft
+author: John Snow Labs
+name: biomednlp_biomedbert_base_uncased_abstract_fulltext
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_biomedbert_base_uncased_abstract_fulltext` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_base_uncased_abstract_fulltext_en_5.5.0_3.0_1725519536803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_base_uncased_abstract_fulltext_en_5.5.0_3.0_1725519536803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("biomednlp_biomedbert_base_uncased_abstract_fulltext","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("biomednlp_biomedbert_base_uncased_abstract_fulltext","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomednlp_biomedbert_base_uncased_abstract_fulltext|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en.md
new file mode 100644
index 00000000000000..815568e9460fa3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline pipeline BertEmbeddings from microsoft
+author: John Snow Labs
+name: biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en_5.5.0_3.0_1725519556350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline_en_5.5.0_3.0_1725519556350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomednlp_biomedbert_base_uncased_abstract_fulltext_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_large_uncased_abstract_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_large_uncased_abstract_pipeline_en.md
new file mode 100644
index 00000000000000..aa22750db5dcb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-biomednlp_biomedbert_large_uncased_abstract_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biomednlp_biomedbert_large_uncased_abstract_pipeline pipeline BertEmbeddings from microsoft
+author: John Snow Labs
+name: biomednlp_biomedbert_large_uncased_abstract_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_biomedbert_large_uncased_abstract_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_large_uncased_abstract_pipeline_en_5.5.0_3.0_1725520350012.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_biomedbert_large_uncased_abstract_pipeline_en_5.5.0_3.0_1725520350012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biomednlp_biomedbert_large_uncased_abstract_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biomednlp_biomedbert_large_uncased_abstract_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomednlp_biomedbert_large_uncased_abstract_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-large-uncased-abstract
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_ivanma1_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_ivanma1_en.md
new file mode 100644
index 00000000000000..54c600e4b17a31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_ivanma1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_ivanma1 DistilBertForSequenceClassification from ivanma1
+author: John Snow Labs
+name: burmese_awesome_model_ivanma1
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_ivanma1` is a English model originally trained by ivanma1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_ivanma1_en_5.5.0_3.0_1725507387403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_ivanma1_en_5.5.0_3.0_1725507387403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_ivanma1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_ivanma1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_ivanma1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ivanma1/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_ivanma1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_ivanma1_pipeline_en.md
new file mode 100644
index 00000000000000..363724ef4feadf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_ivanma1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_ivanma1_pipeline pipeline DistilBertForSequenceClassification from ivanma1
+author: John Snow Labs
+name: burmese_awesome_model_ivanma1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_ivanma1_pipeline` is a English model originally trained by ivanma1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_ivanma1_pipeline_en_5.5.0_3.0_1725507399241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_ivanma1_pipeline_en_5.5.0_3.0_1725507399241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_ivanma1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_ivanma1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_ivanma1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ivanma1/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_jasssz_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_jasssz_en.md
new file mode 100644
index 00000000000000..64de40f7e35c88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_jasssz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_jasssz DistilBertForSequenceClassification from JasssZ
+author: John Snow Labs
+name: burmese_awesome_model_jasssz
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_jasssz` is a English model originally trained by JasssZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jasssz_en_5.5.0_3.0_1725507527120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jasssz_en_5.5.0_3.0_1725507527120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_jasssz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_jasssz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_jasssz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JasssZ/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_lenatt_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_lenatt_en.md
new file mode 100644
index 00000000000000..b976f6b740e6fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_model_lenatt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_lenatt DistilBertForSequenceClassification from lenate
+author: John Snow Labs
+name: burmese_awesome_model_lenatt
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lenatt` is a English model originally trained by lenate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lenatt_en_5.5.0_3.0_1725507059886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lenatt_en_5.5.0_3.0_1725507059886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lenatt","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lenatt", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lenatt|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lenate/my_awesome_model_lenatt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_all_saviolation_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_all_saviolation_en.md
new file mode 100644
index 00000000000000..35a1e829b2cfaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_all_saviolation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_all_saviolation DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_all_saviolation
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_saviolation` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_saviolation_en_5.5.0_3.0_1725500607752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_saviolation_en_5.5.0_3.0_1725500607752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_saviolation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_saviolation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_all_saviolation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_SAviolation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_all_saviolation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_all_saviolation_pipeline_en.md
new file mode 100644
index 00000000000000..e60d35bab8749b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_all_saviolation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_all_saviolation_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_all_saviolation_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_saviolation_pipeline` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_saviolation_pipeline_en_5.5.0_3.0_1725500619961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_saviolation_pipeline_en_5.5.0_3.0_1725500619961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_all_saviolation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_all_saviolation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_all_saviolation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_SAviolation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_basirudin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_basirudin_pipeline_en.md
new file mode 100644
index 00000000000000..4998e1bec4b6d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_basirudin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_basirudin_pipeline pipeline DistilBertForTokenClassification from Basirudin
+author: John Snow Labs
+name: burmese_awesome_wnut_model_basirudin_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_basirudin_pipeline` is a English model originally trained by Basirudin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_basirudin_pipeline_en_5.5.0_3.0_1725518468280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_basirudin_pipeline_en_5.5.0_3.0_1725518468280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_basirudin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_basirudin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_basirudin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Basirudin/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_casual_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_casual_en.md
new file mode 100644
index 00000000000000..42394299ebe6a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_casual_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_casual DistilBertForTokenClassification from casual
+author: John Snow Labs
+name: burmese_awesome_wnut_model_casual
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_casual` is a English model originally trained by casual.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_casual_en_5.5.0_3.0_1725495539551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_casual_en_5.5.0_3.0_1725495539551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_casual","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_casual", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_casual|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/casual/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_donbasta_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_donbasta_en.md
new file mode 100644
index 00000000000000..147ff358a4fe73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_donbasta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_donbasta DistilBertForTokenClassification from donbasta
+author: John Snow Labs
+name: burmese_awesome_wnut_model_donbasta
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_donbasta` is a English model originally trained by donbasta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_donbasta_en_5.5.0_3.0_1725500739519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_donbasta_en_5.5.0_3.0_1725500739519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_donbasta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_donbasta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_donbasta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/donbasta/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_duggurani_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_duggurani_en.md
new file mode 100644
index 00000000000000..f38567408914cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_duggurani_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_duggurani DistilBertForTokenClassification from DugguRani
+author: John Snow Labs
+name: burmese_awesome_wnut_model_duggurani
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_duggurani` is a English model originally trained by DugguRani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_duggurani_en_5.5.0_3.0_1725496256855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_duggurani_en_5.5.0_3.0_1725496256855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_duggurani","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_duggurani", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_duggurani|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/DugguRani/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_fukada6280_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_fukada6280_en.md
new file mode 100644
index 00000000000000..0c4acf503e6ec7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_fukada6280_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_fukada6280 DistilBertForTokenClassification from fukada6280
+author: John Snow Labs
+name: burmese_awesome_wnut_model_fukada6280
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_fukada6280` is a English model originally trained by fukada6280.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_fukada6280_en_5.5.0_3.0_1725495725111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_fukada6280_en_5.5.0_3.0_1725495725111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_fukada6280","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_fukada6280", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_fukada6280|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/fukada6280/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_girsha_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_girsha_en.md
new file mode 100644
index 00000000000000..3115d38165138e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_girsha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_girsha DistilBertForTokenClassification from girsha
+author: John Snow Labs
+name: burmese_awesome_wnut_model_girsha
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_girsha` is a English model originally trained by girsha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_girsha_en_5.5.0_3.0_1725495539157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_girsha_en_5.5.0_3.0_1725495539157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_girsha","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_girsha", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_girsha|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/girsha/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_hina541_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_hina541_en.md
new file mode 100644
index 00000000000000..3fab73957072c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_hina541_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_hina541 DistilBertForTokenClassification from Hina541
+author: John Snow Labs
+name: burmese_awesome_wnut_model_hina541
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_hina541` is a English model originally trained by Hina541.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_hina541_en_5.5.0_3.0_1725496308724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_hina541_en_5.5.0_3.0_1725496308724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_hina541","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_hina541", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_hina541|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Hina541/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_hina541_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_hina541_pipeline_en.md
new file mode 100644
index 00000000000000..d176632d65650e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_hina541_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_hina541_pipeline pipeline DistilBertForTokenClassification from Hina541
+author: John Snow Labs
+name: burmese_awesome_wnut_model_hina541_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_hina541_pipeline` is a English model originally trained by Hina541.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_hina541_pipeline_en_5.5.0_3.0_1725496320077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_hina541_pipeline_en_5.5.0_3.0_1725496320077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_hina541_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_hina541_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_hina541_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Hina541/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_honganh_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_honganh_en.md
new file mode 100644
index 00000000000000..19423c91996980
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_honganh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_honganh DistilBertForTokenClassification from honganh
+author: John Snow Labs
+name: burmese_awesome_wnut_model_honganh
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_honganh` is a English model originally trained by honganh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_honganh_en_5.5.0_3.0_1725506275075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_honganh_en_5.5.0_3.0_1725506275075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_honganh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_honganh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_honganh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/honganh/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_jasonjche_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_jasonjche_en.md
new file mode 100644
index 00000000000000..a2c20ff851ef16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_jasonjche_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_jasonjche DistilBertForTokenClassification from jasonjche
+author: John Snow Labs
+name: burmese_awesome_wnut_model_jasonjche
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_jasonjche` is a English model originally trained by jasonjche.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jasonjche_en_5.5.0_3.0_1725506139856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jasonjche_en_5.5.0_3.0_1725506139856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_jasonjche","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_jasonjche", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_jasonjche|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jasonjche/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_laitrongduc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_laitrongduc_pipeline_en.md
new file mode 100644
index 00000000000000..57a10e508bc213
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_laitrongduc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_laitrongduc_pipeline pipeline DistilBertForTokenClassification from laitrongduc
+author: John Snow Labs
+name: burmese_awesome_wnut_model_laitrongduc_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_laitrongduc_pipeline` is a English model originally trained by laitrongduc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_laitrongduc_pipeline_en_5.5.0_3.0_1725496248347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_laitrongduc_pipeline_en_5.5.0_3.0_1725496248347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_laitrongduc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_laitrongduc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_laitrongduc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/laitrongduc/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_langchain12_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_langchain12_en.md
new file mode 100644
index 00000000000000..63538a4d158280
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_langchain12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_langchain12 DistilBertForTokenClassification from LangChain12
+author: John Snow Labs
+name: burmese_awesome_wnut_model_langchain12
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_langchain12` is a English model originally trained by LangChain12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_langchain12_en_5.5.0_3.0_1725518262997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_langchain12_en_5.5.0_3.0_1725518262997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_langchain12","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_langchain12", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_langchain12|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/LangChain12/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_lash_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_lash_pipeline_en.md
new file mode 100644
index 00000000000000..0ee48c524c0c8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_lash_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_lash_pipeline pipeline DistilBertForTokenClassification from lash
+author: John Snow Labs
+name: burmese_awesome_wnut_model_lash_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_lash_pipeline` is a English model originally trained by lash.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_lash_pipeline_en_5.5.0_3.0_1725500342001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_lash_pipeline_en_5.5.0_3.0_1725500342001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_lash_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_lash_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_lash_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/lash/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_manikanta_goli_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_manikanta_goli_en.md
new file mode 100644
index 00000000000000..aaf62c194c5c98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_manikanta_goli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_manikanta_goli DistilBertForTokenClassification from Manikanta-goli
+author: John Snow Labs
+name: burmese_awesome_wnut_model_manikanta_goli
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_manikanta_goli` is a English model originally trained by Manikanta-goli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_manikanta_goli_en_5.5.0_3.0_1725496091577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_manikanta_goli_en_5.5.0_3.0_1725496091577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_manikanta_goli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_manikanta_goli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_manikanta_goli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Manikanta-goli/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_manusj_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_manusj_en.md
new file mode 100644
index 00000000000000..c85075fafdd59a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_manusj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_manusj DistilBertForTokenClassification from Manusj
+author: John Snow Labs
+name: burmese_awesome_wnut_model_manusj
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_manusj` is a English model originally trained by Manusj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_manusj_en_5.5.0_3.0_1725495801762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_manusj_en_5.5.0_3.0_1725495801762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_manusj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_manusj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_manusj|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Manusj/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_osquery_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_osquery_en.md
new file mode 100644
index 00000000000000..460d0c3f1a1468
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_osquery_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_osquery DistilBertForTokenClassification from Osquery
+author: John Snow Labs
+name: burmese_awesome_wnut_model_osquery
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_osquery` is a English model originally trained by Osquery.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_osquery_en_5.5.0_3.0_1725500705997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_osquery_en_5.5.0_3.0_1725500705997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_osquery","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_osquery", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_osquery|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Osquery/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_osquery_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_osquery_pipeline_en.md
new file mode 100644
index 00000000000000..69177d5379f91b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_osquery_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_osquery_pipeline pipeline DistilBertForTokenClassification from Osquery
+author: John Snow Labs
+name: burmese_awesome_wnut_model_osquery_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_osquery_pipeline` is a English model originally trained by Osquery.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_osquery_pipeline_en_5.5.0_3.0_1725500717590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_osquery_pipeline_en_5.5.0_3.0_1725500717590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_osquery_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_osquery_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_osquery_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Osquery/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_saikatkumardey_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_saikatkumardey_en.md
new file mode 100644
index 00000000000000..25dec68fd5c7e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_saikatkumardey_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_saikatkumardey DistilBertForTokenClassification from saikatkumardey
+author: John Snow Labs
+name: burmese_awesome_wnut_model_saikatkumardey
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_saikatkumardey` is a English model originally trained by saikatkumardey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_saikatkumardey_en_5.5.0_3.0_1725518168146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_saikatkumardey_en_5.5.0_3.0_1725518168146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_saikatkumardey","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_saikatkumardey", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_saikatkumardey|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/saikatkumardey/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_thypogean_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_thypogean_pipeline_en.md
new file mode 100644
index 00000000000000..dae990998761dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_thypogean_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_thypogean_pipeline pipeline DistilBertForTokenClassification from thypogean
+author: John Snow Labs
+name: burmese_awesome_wnut_model_thypogean_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_thypogean_pipeline` is a English model originally trained by thypogean.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_thypogean_pipeline_en_5.5.0_3.0_1725518290355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_thypogean_pipeline_en_5.5.0_3.0_1725518290355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_thypogean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_thypogean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_thypogean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/thypogean/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_yuting27_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_yuting27_en.md
new file mode 100644
index 00000000000000..9cd90cf360abd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_yuting27_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_yuting27 DistilBertForTokenClassification from yuting27
+author: John Snow Labs
+name: burmese_awesome_wnut_model_yuting27
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_yuting27` is a English model originally trained by yuting27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_yuting27_en_5.5.0_3.0_1725518385164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_yuting27_en_5.5.0_3.0_1725518385164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_yuting27","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_yuting27", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_yuting27|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yuting27/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_place_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_place_en.md
new file mode 100644
index 00000000000000..5cff87cf584ffd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_place_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_place DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_place
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_place` is a English model originally trained by gonzalezrostani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_place_en_5.5.0_3.0_1725518089745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_place_en_5.5.0_3.0_1725518089745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_place","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_place", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_place|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_Place
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_ner_model_mundo_go_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_ner_model_mundo_go_en.md
new file mode 100644
index 00000000000000..ab1ef53c89db0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_ner_model_mundo_go_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ner_model_mundo_go DistilBertForTokenClassification from mundo-go
+author: John Snow Labs
+name: burmese_ner_model_mundo_go
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model_mundo_go` is a English model originally trained by mundo-go.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ner_model_mundo_go_en_5.5.0_3.0_1725518324411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_mundo_go_en_5.5.0_3.0_1725518324411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_ner_model_mundo_go","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_ner_model_mundo_go", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_model_mundo_go|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|621.2 MB|
+
+## References
+
+https://huggingface.co/mundo-go/my_ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-camelbert_msa_qalb14_ged_13_ar.md b/docs/_posts/ahmedlone127/2024-09-05-camelbert_msa_qalb14_ged_13_ar.md
new file mode 100644
index 00000000000000..711f1a4f3b8c56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-camelbert_msa_qalb14_ged_13_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic camelbert_msa_qalb14_ged_13 BertForTokenClassification from CAMeL-Lab
+author: John Snow Labs
+name: camelbert_msa_qalb14_ged_13
+date: 2024-09-05
+tags: [ar, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camelbert_msa_qalb14_ged_13` is a Arabic model originally trained by CAMeL-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camelbert_msa_qalb14_ged_13_ar_5.5.0_3.0_1725515901790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camelbert_msa_qalb14_ged_13_ar_5.5.0_3.0_1725515901790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("camelbert_msa_qalb14_ged_13","ar") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("camelbert_msa_qalb14_ged_13", "ar")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camelbert_msa_qalb14_ged_13|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ar|
+|Size:|406.4 MB|
+
+## References
+
+https://huggingface.co/CAMeL-Lab/camelbert-msa-qalb14-ged-13
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline_en.md
new file mode 100644
index 00000000000000..0711277f133aa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline pipeline DistilBertForSequenceClassification from chuuhtetnaing
+author: John Snow Labs
+name: category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline` is a English model originally trained by chuuhtetnaing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline_en_5.5.0_3.0_1725507694971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline_en_5.5.0_3.0_1725507694971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|category_1_delivery_cancellation_distilbert_base_cased_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/chuuhtetnaing/category-1-delivery-cancellation-distilbert-base-cased-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-clip_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-clip_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..5fc0311dce26df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-clip_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_finetuned_pipeline pipeline CLIPForZeroShotClassification from vinluvie
+author: John Snow Labs
+name: clip_finetuned_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_finetuned_pipeline` is a English model originally trained by vinluvie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_finetuned_pipeline_en_5.5.0_3.0_1725522333623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_finetuned_pipeline_en_5.5.0_3.0_1725522333623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|567.3 MB|
+
+## References
+
+https://huggingface.co/vinluvie/clip-finetuned
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-clip_large_fp16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-clip_large_fp16_pipeline_en.md
new file mode 100644
index 00000000000000..3bb86f316e44cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-clip_large_fp16_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_large_fp16_pipeline pipeline CLIPForZeroShotClassification from dahwinsingularity
+author: John Snow Labs
+name: clip_large_fp16_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_large_fp16_pipeline` is a English model originally trained by dahwinsingularity.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_large_fp16_pipeline_en_5.5.0_3.0_1725523747363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_large_fp16_pipeline_en_5.5.0_3.0_1725523747363.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_large_fp16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_large_fp16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_large_fp16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/dahwinsingularity/clip_large_fp16
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-clip_seed_vit_8_en.md b/docs/_posts/ahmedlone127/2024-09-05-clip_seed_vit_8_en.md
new file mode 100644
index 00000000000000..33b5bc9d566c30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-clip_seed_vit_8_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_seed_vit_8 CLIPForZeroShotClassification from zabir735
+author: John Snow Labs
+name: clip_seed_vit_8
+date: 2024-09-05
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_seed_vit_8` is a English model originally trained by zabir735.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_seed_vit_8_en_5.5.0_3.0_1725522607449.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_seed_vit_8_en_5.5.0_3.0_1725522607449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_seed_vit_8","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_seed_vit_8","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_seed_vit_8|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|561.2 MB|
+
+## References
+
+https://huggingface.co/zabir735/clip-seed-vit-8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-clip_vit_base_patch32_demo_xiaoliy2_en.md b/docs/_posts/ahmedlone127/2024-09-05-clip_vit_base_patch32_demo_xiaoliy2_en.md
new file mode 100644
index 00000000000000..a60422fceaa633
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-clip_vit_base_patch32_demo_xiaoliy2_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_base_patch32_demo_xiaoliy2 CLIPForZeroShotClassification from xiaoliy2
+author: John Snow Labs
+name: clip_vit_base_patch32_demo_xiaoliy2
+date: 2024-09-05
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_xiaoliy2` is a English model originally trained by xiaoliy2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_xiaoliy2_en_5.5.0_3.0_1725523473171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_xiaoliy2_en_5.5.0_3.0_1725523473171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_xiaoliy2","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_xiaoliy2","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_demo_xiaoliy2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/xiaoliy2/clip-vit-base-patch32-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-context_tracking_en.md b/docs/_posts/ahmedlone127/2024-09-05-context_tracking_en.md
new file mode 100644
index 00000000000000..c8aff32555cb11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-context_tracking_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English context_tracking DistilBertForTokenClassification from cleopatro
+author: John Snow Labs
+name: context_tracking
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`context_tracking` is a English model originally trained by cleopatro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/context_tracking_en_5.5.0_3.0_1725518605739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/context_tracking_en_5.5.0_3.0_1725518605739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("context_tracking","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("context_tracking", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|context_tracking|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cleopatro/context_tracking
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-context_tracking_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-context_tracking_pipeline_en.md
new file mode 100644
index 00000000000000..8e8bb65fd1781b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-context_tracking_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English context_tracking_pipeline pipeline DistilBertForTokenClassification from cleopatro
+author: John Snow Labs
+name: context_tracking_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`context_tracking_pipeline` is a English model originally trained by cleopatro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/context_tracking_pipeline_en_5.5.0_3.0_1725518617741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/context_tracking_pipeline_en_5.5.0_3.0_1725518617741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("context_tracking_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("context_tracking_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|context_tracking_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cleopatro/context_tracking
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-context_two_en.md b/docs/_posts/ahmedlone127/2024-09-05-context_two_en.md
new file mode 100644
index 00000000000000..c61f773f3adb85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-context_two_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English context_two DistilBertForSequenceClassification from SharonTudi
+author: John Snow Labs
+name: context_two
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`context_two` is a English model originally trained by SharonTudi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/context_two_en_5.5.0_3.0_1725507109548.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/context_two_en_5.5.0_3.0_1725507109548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("context_two","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("context_two", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|context_two|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/SharonTudi/CONTEXT_two
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-convbert_base_turkish_mc4_uncased_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-05-convbert_base_turkish_mc4_uncased_pipeline_tr.md
new file mode 100644
index 00000000000000..b62317a817576b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-convbert_base_turkish_mc4_uncased_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish convbert_base_turkish_mc4_uncased_pipeline pipeline BertEmbeddings from dbmdz
+author: John Snow Labs
+name: convbert_base_turkish_mc4_uncased_pipeline
+date: 2024-09-05
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_uncased_pipeline` is a Turkish model originally trained by dbmdz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_uncased_pipeline_tr_5.5.0_3.0_1725519911887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_uncased_pipeline_tr_5.5.0_3.0_1725519911887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("convbert_base_turkish_mc4_uncased_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("convbert_base_turkish_mc4_uncased_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convbert_base_turkish_mc4_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/dbmdz/convbert-base-turkish-mc4-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-cryptocurrency_intent_search_detection_en.md b/docs/_posts/ahmedlone127/2024-09-05-cryptocurrency_intent_search_detection_en.md
new file mode 100644
index 00000000000000..13e158d1a1a3f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-cryptocurrency_intent_search_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cryptocurrency_intent_search_detection XlmRoBertaForSequenceClassification from dadashzadeh
+author: John Snow Labs
+name: cryptocurrency_intent_search_detection
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cryptocurrency_intent_search_detection` is a English model originally trained by dadashzadeh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cryptocurrency_intent_search_detection_en_5.5.0_3.0_1725514332830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cryptocurrency_intent_search_detection_en_5.5.0_3.0_1725514332830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("cryptocurrency_intent_search_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("cryptocurrency_intent_search_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cryptocurrency_intent_search_detection|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|813.8 MB|
+
+## References
+
+https://huggingface.co/dadashzadeh/cryptocurrency-intent-search-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ct_cos_xlmr_20230814_en.md b/docs/_posts/ahmedlone127/2024-09-05-ct_cos_xlmr_20230814_en.md
new file mode 100644
index 00000000000000..7d25c7db45b89c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ct_cos_xlmr_20230814_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ct_cos_xlmr_20230814 XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_cos_xlmr_20230814
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_xlmr_20230814` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_20230814_en_5.5.0_3.0_1725500023364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_20230814_en_5.5.0_3.0_1725500023364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_cos_xlmr_20230814","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_cos_xlmr_20230814", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_cos_xlmr_20230814|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|875.2 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-cos-xlmr-20230814
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ct_cos_xlmr_20230923_1_en.md b/docs/_posts/ahmedlone127/2024-09-05-ct_cos_xlmr_20230923_1_en.md
new file mode 100644
index 00000000000000..84bb6a2465ed8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ct_cos_xlmr_20230923_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ct_cos_xlmr_20230923_1 XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_cos_xlmr_20230923_1
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_cos_xlmr_20230923_1` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_20230923_1_en_5.5.0_3.0_1725500060098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_cos_xlmr_20230923_1_en_5.5.0_3.0_1725500060098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_cos_xlmr_20230923_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_cos_xlmr_20230923_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_cos_xlmr_20230923_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|876.0 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-cos-xlmr-20230923-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ct_kld_xlmr_20230923_1_en.md b/docs/_posts/ahmedlone127/2024-09-05-ct_kld_xlmr_20230923_1_en.md
new file mode 100644
index 00000000000000..4af0354b618d8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ct_kld_xlmr_20230923_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ct_kld_xlmr_20230923_1 XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_kld_xlmr_20230923_1
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_xlmr_20230923_1` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_xlmr_20230923_1_en_5.5.0_3.0_1725498038031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_xlmr_20230923_1_en_5.5.0_3.0_1725498038031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_kld_xlmr_20230923_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_kld_xlmr_20230923_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_kld_xlmr_20230923_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|876.0 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-kld-xlmr-20230923-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ct_mse_xlmr_idkmrc_en.md b/docs/_posts/ahmedlone127/2024-09-05-ct_mse_xlmr_idkmrc_en.md
new file mode 100644
index 00000000000000..61ecf39bbf3d85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ct_mse_xlmr_idkmrc_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ct_mse_xlmr_idkmrc XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_mse_xlmr_idkmrc
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_xlmr_idkmrc` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_idkmrc_en_5.5.0_3.0_1725499710534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_idkmrc_en_5.5.0_3.0_1725499710534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_mse_xlmr_idkmrc","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("ct_mse_xlmr_idkmrc", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_mse_xlmr_idkmrc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|834.0 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-mse-xlmr-idkmrc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ct_mse_xlmr_idkmrc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-ct_mse_xlmr_idkmrc_pipeline_en.md
new file mode 100644
index 00000000000000..6ea46553de742f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ct_mse_xlmr_idkmrc_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ct_mse_xlmr_idkmrc_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_mse_xlmr_idkmrc_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_xlmr_idkmrc_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_idkmrc_pipeline_en_5.5.0_3.0_1725499824108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_xlmr_idkmrc_pipeline_en_5.5.0_3.0_1725499824108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ct_mse_xlmr_idkmrc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ct_mse_xlmr_idkmrc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_mse_xlmr_idkmrc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|834.0 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-mse-xlmr-idkmrc
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ct_qa_002_9june23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-ct_qa_002_9june23_pipeline_en.md
new file mode 100644
index 00000000000000..cdc3b59ba8ad7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ct_qa_002_9june23_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ct_qa_002_9june23_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_qa_002_9june23_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_qa_002_9june23_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_qa_002_9june23_pipeline_en_5.5.0_3.0_1725497091927.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_qa_002_9june23_pipeline_en_5.5.0_3.0_1725497091927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ct_qa_002_9june23_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ct_qa_002_9june23_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_qa_002_9june23_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|874.5 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-qa-002-9june23
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-darijabert_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-05-darijabert_pipeline_ar.md
new file mode 100644
index 00000000000000..f6c87bf52005be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-darijabert_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic darijabert_pipeline pipeline BertEmbeddings from SI2M-Lab
+author: John Snow Labs
+name: darijabert_pipeline
+date: 2024-09-05
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darijabert_pipeline` is a Arabic model originally trained by SI2M-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darijabert_pipeline_ar_5.5.0_3.0_1725520114759.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darijabert_pipeline_ar_5.5.0_3.0_1725520114759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("darijabert_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("darijabert_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darijabert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|551.5 MB|
+
+## References
+
+https://huggingface.co/SI2M-Lab/DarijaBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-dataequity_opus_maltese_tagalog_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-dataequity_opus_maltese_tagalog_english_pipeline_en.md
new file mode 100644
index 00000000000000..7a50e2d4fbe540
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-dataequity_opus_maltese_tagalog_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dataequity_opus_maltese_tagalog_english_pipeline pipeline MarianTransformer from dataequity
+author: John Snow Labs
+name: dataequity_opus_maltese_tagalog_english_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dataequity_opus_maltese_tagalog_english_pipeline` is a English model originally trained by dataequity.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dataequity_opus_maltese_tagalog_english_pipeline_en_5.5.0_3.0_1725494565988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dataequity_opus_maltese_tagalog_english_pipeline_en_5.5.0_3.0_1725494565988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dataequity_opus_maltese_tagalog_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dataequity_opus_maltese_tagalog_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dataequity_opus_maltese_tagalog_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|497.1 MB|
+
+## References
+
+https://huggingface.co/dataequity/dataequity-opus-mt-tl-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-dbert_pii_detection_model_omshikhare_en.md b/docs/_posts/ahmedlone127/2024-09-05-dbert_pii_detection_model_omshikhare_en.md
new file mode 100644
index 00000000000000..cf39f195503d1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-dbert_pii_detection_model_omshikhare_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dbert_pii_detection_model_omshikhare DistilBertForTokenClassification from omshikhare
+author: John Snow Labs
+name: dbert_pii_detection_model_omshikhare
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbert_pii_detection_model_omshikhare` is a English model originally trained by omshikhare.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbert_pii_detection_model_omshikhare_en_5.5.0_3.0_1725506367369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbert_pii_detection_model_omshikhare_en_5.5.0_3.0_1725506367369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("dbert_pii_detection_model_omshikhare","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("dbert_pii_detection_model_omshikhare", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbert_pii_detection_model_omshikhare|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/omshikhare/dbert-pii-detection-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-disorbert_en.md b/docs/_posts/ahmedlone127/2024-09-05-disorbert_en.md
new file mode 100644
index 00000000000000..6638c31c485ec0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-disorbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English disorbert BertEmbeddings from citiusLTL
+author: John Snow Labs
+name: disorbert
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disorbert` is a English model originally trained by citiusLTL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disorbert_en_5.5.0_3.0_1725519867493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disorbert_en_5.5.0_3.0_1725519867493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("disorbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("disorbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disorbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/citiusLTL/DisorBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_cased_ner_dumiiii_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_cased_ner_dumiiii_pipeline_en.md
new file mode 100644
index 00000000000000..a1a4345e57b3f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_cased_ner_dumiiii_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_cased_ner_dumiiii_pipeline pipeline DistilBertForTokenClassification from Dumiiii
+author: John Snow Labs
+name: distilbert_base_cased_ner_dumiiii_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_ner_dumiiii_pipeline` is a English model originally trained by Dumiiii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_ner_dumiiii_pipeline_en_5.5.0_3.0_1725505827677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_ner_dumiiii_pipeline_en_5.5.0_3.0_1725505827677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_cased_ner_dumiiii_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_cased_ner_dumiiii_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_ner_dumiiii_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Dumiiii/distilbert-base-cased-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_cased_ner_tunahangokcimen_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_cased_ner_tunahangokcimen_en.md
new file mode 100644
index 00000000000000..477515ae6c5abc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_cased_ner_tunahangokcimen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_cased_ner_tunahangokcimen DistilBertForTokenClassification from TunahanGokcimen
+author: John Snow Labs
+name: distilbert_base_cased_ner_tunahangokcimen
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_ner_tunahangokcimen` is a English model originally trained by TunahanGokcimen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_ner_tunahangokcimen_en_5.5.0_3.0_1725495661196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_ner_tunahangokcimen_en_5.5.0_3.0_1725495661196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_cased_ner_tunahangokcimen","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_cased_ner_tunahangokcimen", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_ner_tunahangokcimen|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/TunahanGokcimen/distilbert-base-cased-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_celinalopga_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_celinalopga_en.md
new file mode 100644
index 00000000000000..2cc60b3f80c08d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_celinalopga_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_celinalopga DistilBertForTokenClassification from CelinaLopGa
+author: John Snow Labs
+name: distilbert_base_uncased_celinalopga
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_celinalopga` is a English model originally trained by CelinaLopGa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_celinalopga_en_5.5.0_3.0_1725518534518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_celinalopga_en_5.5.0_3.0_1725518534518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_celinalopga","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_celinalopga", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_celinalopga|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/CelinaLopGa/distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_celinalopga_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_celinalopga_pipeline_en.md
new file mode 100644
index 00000000000000..416cd26dc543d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_celinalopga_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_celinalopga_pipeline pipeline DistilBertForTokenClassification from CelinaLopGa
+author: John Snow Labs
+name: distilbert_base_uncased_celinalopga_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_celinalopga_pipeline` is a English model originally trained by CelinaLopGa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_celinalopga_pipeline_en_5.5.0_3.0_1725518546991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_celinalopga_pipeline_en_5.5.0_3.0_1725518546991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_celinalopga_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_celinalopga_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_celinalopga_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/CelinaLopGa/distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_clinc_mrwetsnow_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_clinc_mrwetsnow_en.md
new file mode 100644
index 00000000000000..ec636472bb995c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_clinc_mrwetsnow_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_clinc_mrwetsnow DistilBertForSequenceClassification from MrWetsnow
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_clinc_mrwetsnow
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_clinc_mrwetsnow` is a English model originally trained by MrWetsnow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_clinc_mrwetsnow_en_5.5.0_3.0_1725507248432.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_clinc_mrwetsnow_en_5.5.0_3.0_1725507248432.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_clinc_mrwetsnow","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_clinc_mrwetsnow", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_clinc_mrwetsnow|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/MrWetsnow/distilbert-base-uncased-finetuned-clinc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline_en.md
new file mode 100644
index 00000000000000..f87f1431b73ea2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline pipeline DistilBertForSequenceClassification from elshehawy
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline` is a English model originally trained by elshehawy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline_en_5.5.0_3.0_1725507362211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline_en_5.5.0_3.0_1725507362211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_elshehawy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/elshehawy/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_temp2_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_temp2_en.md
new file mode 100644
index 00000000000000..00c56e73227ea4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_temp2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_temp2 DistilBertForSequenceClassification from mayankkeshari
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_temp2
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_temp2` is a English model originally trained by mayankkeshari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_temp2_en_5.5.0_3.0_1725507114173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_temp2_en_5.5.0_3.0_1725507114173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_temp2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_temp2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_temp2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mayankkeshari/distilbert-base-uncased-finetuned-emotion-temp2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_temp2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_temp2_pipeline_en.md
new file mode 100644
index 00000000000000..a2a2ea3e9b810d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_emotion_temp2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_temp2_pipeline pipeline DistilBertForSequenceClassification from mayankkeshari
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_temp2_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_temp2_pipeline` is a English model originally trained by mayankkeshari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_temp2_pipeline_en_5.5.0_3.0_1725507126319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_temp2_pipeline_en_5.5.0_3.0_1725507126319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_temp2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_temp2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_temp2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mayankkeshari/distilbert-base-uncased-finetuned-emotion-temp2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_imdb_abh1na5_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_imdb_abh1na5_en.md
new file mode 100644
index 00000000000000..181e8959b16395
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_imdb_abh1na5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_abh1na5 DistilBertEmbeddings from abh1na5
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_abh1na5
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_abh1na5` is a English model originally trained by abh1na5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_abh1na5_en_5.5.0_3.0_1725524093199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_abh1na5_en_5.5.0_3.0_1725524093199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_abh1na5","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_abh1na5","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_abh1na5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/abh1na5/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_imdb_zhenchuan_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_imdb_zhenchuan_en.md
new file mode 100644
index 00000000000000..88b4ecd7fa3e67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_imdb_zhenchuan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_zhenchuan DistilBertEmbeddings from zhenchuan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_zhenchuan
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_zhenchuan` is a English model originally trained by zhenchuan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_zhenchuan_en_5.5.0_3.0_1725524097916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_zhenchuan_en_5.5.0_3.0_1725524097916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_zhenchuan","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_zhenchuan","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_zhenchuan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/zhenchuan/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_neg_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_neg_en.md
new file mode 100644
index 00000000000000..5b1e7deee2426a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_neg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_neg DistilBertForTokenClassification from tqoyiwcvwkephzdgsp
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_neg
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_neg` is a English model originally trained by tqoyiwcvwkephzdgsp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_neg_en_5.5.0_3.0_1725518089742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_neg_en_5.5.0_3.0_1725518089742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_neg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_neg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_neg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/tqoyiwcvwkephzdgsp/distilbert-base-uncased-finetuned-neg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_artem1981_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_artem1981_en.md
new file mode 100644
index 00000000000000..817de887d26395
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_artem1981_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_artem1981 DistilBertForTokenClassification from Artem1981
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_artem1981
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_artem1981` is a English model originally trained by Artem1981.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_artem1981_en_5.5.0_3.0_1725518832391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_artem1981_en_5.5.0_3.0_1725518832391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_artem1981","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_artem1981", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_artem1981|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Artem1981/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_bennb_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_bennb_en.md
new file mode 100644
index 00000000000000..f4f21fed1e462d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_bennb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_bennb DistilBertForTokenClassification from BennB
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_bennb
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_bennb` is a English model originally trained by BennB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_bennb_en_5.5.0_3.0_1725500597267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_bennb_en_5.5.0_3.0_1725500597267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_bennb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_bennb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_bennb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/BennB/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_bennb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_bennb_pipeline_en.md
new file mode 100644
index 00000000000000..a510be7476275d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_bennb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_bennb_pipeline pipeline DistilBertForTokenClassification from BennB
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_bennb_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_bennb_pipeline` is a English model originally trained by BennB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_bennb_pipeline_en_5.5.0_3.0_1725500609734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_bennb_pipeline_en_5.5.0_3.0_1725500609734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_bennb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_bennb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_bennb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/BennB/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_ceciliafu_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_ceciliafu_en.md
new file mode 100644
index 00000000000000..c5c6b260fbc3ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_ceciliafu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_ceciliafu DistilBertForTokenClassification from CeciliaFu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_ceciliafu
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_ceciliafu` is a English model originally trained by CeciliaFu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_ceciliafu_en_5.5.0_3.0_1725500525715.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_ceciliafu_en_5.5.0_3.0_1725500525715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_ceciliafu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_ceciliafu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_ceciliafu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/CeciliaFu/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_digidix28_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_digidix28_en.md
new file mode 100644
index 00000000000000..65be55ce31de76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_digidix28_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_digidix28 DistilBertForTokenClassification from Digidix28
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_digidix28
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_digidix28` is a English model originally trained by Digidix28.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_digidix28_en_5.5.0_3.0_1725500682018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_digidix28_en_5.5.0_3.0_1725500682018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_digidix28","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_digidix28", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_digidix28|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Digidix28/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline_en.md
new file mode 100644
index 00000000000000..b1f0289537fb6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline pipeline DistilBertForTokenClassification from douglasadams11
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline` is a English model originally trained by douglasadams11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline_en_5.5.0_3.0_1725500412893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline_en_5.5.0_3.0_1725500412893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_douglasadams11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/douglasadams11/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_giladh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_giladh_pipeline_en.md
new file mode 100644
index 00000000000000..d4e7b7610971fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_giladh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_giladh_pipeline pipeline DistilBertForTokenClassification from GiladH
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_giladh_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_giladh_pipeline` is a English model originally trained by GiladH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_giladh_pipeline_en_5.5.0_3.0_1725500951119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_giladh_pipeline_en_5.5.0_3.0_1725500951119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_giladh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_giladh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_giladh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/GiladH/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_lum4yx_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_lum4yx_pipeline_en.md
new file mode 100644
index 00000000000000..b0a0bc3ae2e72d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_lum4yx_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_lum4yx_pipeline pipeline DistilBertForTokenClassification from Lum4yx
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_lum4yx_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_lum4yx_pipeline` is a English model originally trained by Lum4yx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_lum4yx_pipeline_en_5.5.0_3.0_1725501008330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_lum4yx_pipeline_en_5.5.0_3.0_1725501008330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_lum4yx_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_lum4yx_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_lum4yx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Lum4yx/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_shuvayanti_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_shuvayanti_en.md
new file mode 100644
index 00000000000000..abfd77eebc5ccf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_shuvayanti_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_shuvayanti DistilBertForTokenClassification from shuvayanti
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_shuvayanti
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_shuvayanti` is a English model originally trained by shuvayanti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_shuvayanti_en_5.5.0_3.0_1725506261671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_shuvayanti_en_5.5.0_3.0_1725506261671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_shuvayanti","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_shuvayanti", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_shuvayanti|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/shuvayanti/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_sindhujag26_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_sindhujag26_en.md
new file mode 100644
index 00000000000000..9ac0a51011c109
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_sindhujag26_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_sindhujag26 DistilBertForTokenClassification from sindhujag26
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_sindhujag26
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_sindhujag26` is a English model originally trained by sindhujag26.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_sindhujag26_en_5.5.0_3.0_1725500372410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_sindhujag26_en_5.5.0_3.0_1725500372410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_sindhujag26","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_sindhujag26", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_sindhujag26|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sindhujag26/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_ugrozkr_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_ugrozkr_en.md
new file mode 100644
index 00000000000000..ba589a90eff937
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_ugrozkr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_ugrozkr DistilBertForTokenClassification from ugrozkr
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_ugrozkr
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_ugrozkr` is a English model originally trained by ugrozkr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_ugrozkr_en_5.5.0_3.0_1725495649649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_ugrozkr_en_5.5.0_3.0_1725495649649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_ugrozkr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_ugrozkr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_ugrozkr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ugrozkr/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline_en.md
new file mode 100644
index 00000000000000..909e018e810e92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline pipeline DistilBertForTokenClassification from Justice0893
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline` is a English model originally trained by Justice0893.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline_en_5.5.0_3.0_1725518177773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline_en_5.5.0_3.0_1725518177773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_sayula_popoluca_kazakh_3080_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|181.4 MB|
+
+## References
+
+https://huggingface.co/Justice0893/distilbert-base-uncased-finetuned-pos-kk-3080
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_qqp_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_qqp_en.md
new file mode 100644
index 00000000000000..302c7397a4f9af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_qqp_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English distilbert_base_uncased_qqp DistilBertForSequenceClassification from assemblyai
+author: John Snow Labs
+name: distilbert_base_uncased_qqp
+date: 2024-09-05
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_qqp` is a English model originally trained by assemblyai.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_qqp_en_5.5.0_3.0_1725507424125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_qqp_en_5.5.0_3.0_1725507424125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_qqp","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_qqp","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_qqp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/assemblyai/distilbert-base-uncased-qqp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_tokenclassification_yeji_seong_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_tokenclassification_yeji_seong_pipeline_en.md
new file mode 100644
index 00000000000000..dde03ab9e4ec9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_tokenclassification_yeji_seong_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_tokenclassification_yeji_seong_pipeline pipeline DistilBertForTokenClassification from Yeji-Seong
+author: John Snow Labs
+name: distilbert_base_uncased_tokenclassification_yeji_seong_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_tokenclassification_yeji_seong_pipeline` is a English model originally trained by Yeji-Seong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_tokenclassification_yeji_seong_pipeline_en_5.5.0_3.0_1725500286765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_tokenclassification_yeji_seong_pipeline_en_5.5.0_3.0_1725500286765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_tokenclassification_yeji_seong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_tokenclassification_yeji_seong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_tokenclassification_yeji_seong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Yeji-Seong/distilbert-base-uncased-tokenclassification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_lolchamps_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_lolchamps_en.md
new file mode 100644
index 00000000000000..ce348f6b6f0efc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_lolchamps_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_lolchamps DistilBertEmbeddings from avinot
+author: John Snow Labs
+name: distilbert_lolchamps
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lolchamps` is a English model originally trained by avinot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lolchamps_en_5.5.0_3.0_1725524041066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lolchamps_en_5.5.0_3.0_1725524041066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_lolchamps","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_lolchamps","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lolchamps|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/avinot/distilbert-lolchamps
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_augmented_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_augmented_en.md
new file mode 100644
index 00000000000000..f964d72af1bdc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_augmented_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_augmented DistilBertForTokenClassification from Azure-Heights
+author: John Snow Labs
+name: distilbert_ner_augmented
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_augmented` is a English model originally trained by Azure-Heights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_augmented_en_5.5.0_3.0_1725518441614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_augmented_en_5.5.0_3.0_1725518441614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_augmented","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_augmented", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_augmented|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Azure-Heights/distilbert-ner-augmented
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_japanese_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_japanese_en.md
new file mode 100644
index 00000000000000..3df3be18093bb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_japanese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_japanese DistilBertForTokenClassification from rizkyfoxcale
+author: John Snow Labs
+name: distilbert_ner_japanese
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_japanese` is a English model originally trained by rizkyfoxcale.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_japanese_en_5.5.0_3.0_1725506481137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_japanese_en_5.5.0_3.0_1725506481137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_japanese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_japanese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_japanese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/rizkyfoxcale/distilbert-ner-ja
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_sahuh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_sahuh_pipeline_en.md
new file mode 100644
index 00000000000000..25106dd2195619
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_ner_sahuh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_sahuh_pipeline pipeline DistilBertForTokenClassification from SahuH
+author: John Snow Labs
+name: distilbert_ner_sahuh_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_sahuh_pipeline` is a English model originally trained by SahuH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_sahuh_pipeline_en_5.5.0_3.0_1725505829012.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_sahuh_pipeline_en_5.5.0_3.0_1725505829012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_sahuh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_sahuh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_sahuh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/SahuH/distilbert-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_sentiment_classifier_kiel1_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_sentiment_classifier_kiel1_en.md
new file mode 100644
index 00000000000000..36c909253c9b18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_sentiment_classifier_kiel1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_sentiment_classifier_kiel1 DistilBertForSequenceClassification from kieltraining
+author: John Snow Labs
+name: distilbert_sentiment_classifier_kiel1
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sentiment_classifier_kiel1` is a English model originally trained by kieltraining.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_classifier_kiel1_en_5.5.0_3.0_1725507420159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_classifier_kiel1_en_5.5.0_3.0_1725507420159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_sentiment_classifier_kiel1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sentiment_classifier_kiel1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sentiment_classifier_kiel1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kieltraining/distilbert-sentiment-classifier_kiel1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_turkish_ner_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_turkish_ner_en.md
new file mode 100644
index 00000000000000..8569d5ec500990
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_turkish_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_turkish_ner DistilBertForTokenClassification from pnr-svc
+author: John Snow Labs
+name: distilbert_turkish_ner
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_turkish_ner` is a English model originally trained by pnr-svc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_turkish_ner_en_5.5.0_3.0_1725506001949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_turkish_ner_en_5.5.0_3.0_1725506001949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_turkish_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_turkish_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_turkish_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|251.9 MB|
+
+## References
+
+https://huggingface.co/pnr-svc/distilbert-turkish-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distillbert_finetuned_ner_btc_en.md b/docs/_posts/ahmedlone127/2024-09-05-distillbert_finetuned_ner_btc_en.md
new file mode 100644
index 00000000000000..df19f97c1680ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distillbert_finetuned_ner_btc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distillbert_finetuned_ner_btc DistilBertForTokenClassification from farrukhrasool112
+author: John Snow Labs
+name: distillbert_finetuned_ner_btc
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_finetuned_ner_btc` is a English model originally trained by farrukhrasool112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_finetuned_ner_btc_en_5.5.0_3.0_1725518255698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_finetuned_ner_btc_en_5.5.0_3.0_1725518255698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distillbert_finetuned_ner_btc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distillbert_finetuned_ner_btc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_finetuned_ner_btc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/farrukhrasool112/distillbert-finetuned-ner-btc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilled_xlm_roberta_base_squad2_qa_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilled_xlm_roberta_base_squad2_qa_en.md
new file mode 100644
index 00000000000000..7476e6533a8991
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilled_xlm_roberta_base_squad2_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilled_xlm_roberta_base_squad2_qa XlmRoBertaForQuestionAnswering from Shobhank-iiitdwd
+author: John Snow Labs
+name: distilled_xlm_roberta_base_squad2_qa
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_xlm_roberta_base_squad2_qa` is a English model originally trained by Shobhank-iiitdwd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilled_xlm_roberta_base_squad2_qa_en_5.5.0_3.0_1725498290671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_xlm_roberta_base_squad2_qa_en_5.5.0_3.0_1725498290671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("distilled_xlm_roberta_base_squad2_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("distilled_xlm_roberta_base_squad2_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_xlm_roberta_base_squad2_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Shobhank-iiitdwd/Distilled-xlm-RoBERTa-base-squad2-QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilled_xlm_roberta_base_squad2_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilled_xlm_roberta_base_squad2_qa_pipeline_en.md
new file mode 100644
index 00000000000000..473e7d837df932
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilled_xlm_roberta_base_squad2_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilled_xlm_roberta_base_squad2_qa_pipeline pipeline XlmRoBertaForQuestionAnswering from Shobhank-iiitdwd
+author: John Snow Labs
+name: distilled_xlm_roberta_base_squad2_qa_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_xlm_roberta_base_squad2_qa_pipeline` is a English model originally trained by Shobhank-iiitdwd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilled_xlm_roberta_base_squad2_qa_pipeline_en_5.5.0_3.0_1725498377895.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_xlm_roberta_base_squad2_qa_pipeline_en_5.5.0_3.0_1725498377895.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilled_xlm_roberta_base_squad2_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilled_xlm_roberta_base_squad2_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_xlm_roberta_base_squad2_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Shobhank-iiitdwd/Distilled-xlm-RoBERTa-base-squad2-QA
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_arabic_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_arabic_v2_pipeline_en.md
new file mode 100644
index 00000000000000..7d27571b3b327b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_arabic_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_arabic_v2_pipeline pipeline MarianTransformer from wingo-dz
+author: John Snow Labs
+name: english_tonga_tonga_islands_arabic_v2_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_arabic_v2_pipeline` is a English model originally trained by wingo-dz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_arabic_v2_pipeline_en_5.5.0_3.0_1725494692808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_arabic_v2_pipeline_en_5.5.0_3.0_1725494692808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_arabic_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_arabic_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_arabic_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.8 MB|
+
+## References
+
+https://huggingface.co/wingo-dz/en-to-ar-v2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_darija_3_en.md b/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_darija_3_en.md
new file mode 100644
index 00000000000000..ba46cd96cdb76a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_darija_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_darija_3 MarianTransformer from ychafiqui
+author: John Snow Labs
+name: english_tonga_tonga_islands_darija_3
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_darija_3` is a English model originally trained by ychafiqui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_darija_3_en_5.5.0_3.0_1725495236311.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_darija_3_en_5.5.0_3.0_1725495236311.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_tonga_tonga_islands_darija_3","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_darija_3","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_darija_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/ychafiqui/english-to-darija-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_darija_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_darija_3_pipeline_en.md
new file mode 100644
index 00000000000000..4dc130a13f236e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-english_tonga_tonga_islands_darija_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_darija_3_pipeline pipeline MarianTransformer from ychafiqui
+author: John Snow Labs
+name: english_tonga_tonga_islands_darija_3_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_darija_3_pipeline` is a English model originally trained by ychafiqui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_darija_3_pipeline_en_5.5.0_3.0_1725495304209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_darija_3_pipeline_en_5.5.0_3.0_1725495304209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_darija_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_darija_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_darija_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/ychafiqui/english-to-darija-3
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-esg_classification_french_english_fr.md b/docs/_posts/ahmedlone127/2024-09-05-esg_classification_french_english_fr.md
new file mode 100644
index 00000000000000..dd69cc274b2d3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-esg_classification_french_english_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French esg_classification_french_english DistilBertForSequenceClassification from cea-list-lasti
+author: John Snow Labs
+name: esg_classification_french_english
+date: 2024-09-05
+tags: [fr, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esg_classification_french_english` is a French model originally trained by cea-list-lasti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esg_classification_french_english_fr_5.5.0_3.0_1725506955357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esg_classification_french_english_fr_5.5.0_3.0_1725506955357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("esg_classification_french_english","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("esg_classification_french_english", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esg_classification_french_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|508.0 MB|
+
+## References
+
+https://huggingface.co/cea-list-lasti/ESG-classification-fr-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-experiment_foreign_language_en.md b/docs/_posts/ahmedlone127/2024-09-05-experiment_foreign_language_en.md
new file mode 100644
index 00000000000000..d0aaa4e4ed15bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-experiment_foreign_language_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English experiment_foreign_language DistilBertForTokenClassification from sophiestein
+author: John Snow Labs
+name: experiment_foreign_language
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`experiment_foreign_language` is a English model originally trained by sophiestein.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/experiment_foreign_language_en_5.5.0_3.0_1725495786469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/experiment_foreign_language_en_5.5.0_3.0_1725495786469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("experiment_foreign_language","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("experiment_foreign_language", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|experiment_foreign_language|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/sophiestein/experiment_foreign_language
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finance_news_classifier_kanuri_v7_ko.md b/docs/_posts/ahmedlone127/2024-09-05-finance_news_classifier_kanuri_v7_ko.md
new file mode 100644
index 00000000000000..e11ae6f75ac8ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finance_news_classifier_kanuri_v7_ko.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Korean finance_news_classifier_kanuri_v7 XlmRoBertaForSequenceClassification from gabrielyang
+author: John Snow Labs
+name: finance_news_classifier_kanuri_v7
+date: 2024-09-05
+tags: [ko, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finance_news_classifier_kanuri_v7` is a Korean model originally trained by gabrielyang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finance_news_classifier_kanuri_v7_ko_5.5.0_3.0_1725513480807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finance_news_classifier_kanuri_v7_ko_5.5.0_3.0_1725513480807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("finance_news_classifier_kanuri_v7","ko") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("finance_news_classifier_kanuri_v7", "ko")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finance_news_classifier_kanuri_v7|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ko|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/gabrielyang/finance_news_classifier-KR_v7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline_en.md
new file mode 100644
index 00000000000000..46f6f3be80151d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline pipeline MarianTransformer from HugginJake
+author: John Snow Labs
+name: finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline` is a English model originally trained by HugginJake.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline_en_5.5.0_3.0_1725495241945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline_en_5.5.0_3.0_1725495241945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_marianmtmodel_v2_specialfrom_ccmatrix77k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|510.1 MB|
+
+## References
+
+https://huggingface.co/HugginJake/Finetuned_MarianMTModel_v2_specialFrom_ccmatrix77k
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuned_ner_sarthak7777_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuned_ner_sarthak7777_pipeline_en.md
new file mode 100644
index 00000000000000..6006b6326819af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuned_ner_sarthak7777_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_ner_sarthak7777_pipeline pipeline DistilBertForTokenClassification from Sarthak7777
+author: John Snow Labs
+name: finetuned_ner_sarthak7777_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ner_sarthak7777_pipeline` is a English model originally trained by Sarthak7777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ner_sarthak7777_pipeline_en_5.5.0_3.0_1725500479663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ner_sarthak7777_pipeline_en_5.5.0_3.0_1725500479663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_ner_sarthak7777_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_ner_sarthak7777_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_ner_sarthak7777_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Sarthak7777/finetuned-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_emotion_model_purushothama_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_emotion_model_purushothama_en.md
new file mode 100644
index 00000000000000..451c156158ceac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_emotion_model_purushothama_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_emotion_model_purushothama DistilBertForSequenceClassification from Purushothama
+author: John Snow Labs
+name: finetuning_emotion_model_purushothama
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_emotion_model_purushothama` is a English model originally trained by Purushothama.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_purushothama_en_5.5.0_3.0_1725507690677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_purushothama_en_5.5.0_3.0_1725507690677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_emotion_model_purushothama","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_emotion_model_purushothama", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_emotion_model_purushothama|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Purushothama/finetuning-emotion-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_ift6758_hw6_sentiment_model_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_ift6758_hw6_sentiment_model_en.md
new file mode 100644
index 00000000000000..3c562bbbbd3067
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_ift6758_hw6_sentiment_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_ift6758_hw6_sentiment_model DistilBertForSequenceClassification from ucmp137538
+author: John Snow Labs
+name: finetuning_ift6758_hw6_sentiment_model
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_ift6758_hw6_sentiment_model` is a English model originally trained by ucmp137538.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_ift6758_hw6_sentiment_model_en_5.5.0_3.0_1725507421346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_ift6758_hw6_sentiment_model_en_5.5.0_3.0_1725507421346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_ift6758_hw6_sentiment_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_ift6758_hw6_sentiment_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_ift6758_hw6_sentiment_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/ucmp137538/finetuning-ift6758-hw6-sentiment-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_movie_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_movie_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..80460cba91f0cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_movie_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_movie_sentiment_analysis_pipeline pipeline DistilBertForSequenceClassification from MrPudge
+author: John Snow Labs
+name: finetuning_movie_sentiment_analysis_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_movie_sentiment_analysis_pipeline` is a English model originally trained by MrPudge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_movie_sentiment_analysis_pipeline_en_5.5.0_3.0_1725507150858.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_movie_sentiment_analysis_pipeline_en_5.5.0_3.0_1725507150858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_movie_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_movie_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_movie_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MrPudge/finetuning-movie-sentiment-analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_ditilbert_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_ditilbert_en.md
new file mode 100644
index 00000000000000..06301a1518d12c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_ditilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_ditilbert DistilBertForSequenceClassification from Neo111x
+author: John Snow Labs
+name: finetuning_sentiment_ditilbert
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_ditilbert` is a English model originally trained by Neo111x.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_ditilbert_en_5.5.0_3.0_1725507303915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_ditilbert_en_5.5.0_3.0_1725507303915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_ditilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_ditilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_ditilbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Neo111x/finetuning-sentiment_ditilBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_ditilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_ditilbert_pipeline_en.md
new file mode 100644
index 00000000000000..4da01359721007
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_ditilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_ditilbert_pipeline pipeline DistilBertForSequenceClassification from Neo111x
+author: John Snow Labs
+name: finetuning_sentiment_ditilbert_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_ditilbert_pipeline` is a English model originally trained by Neo111x.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_ditilbert_pipeline_en_5.5.0_3.0_1725507316652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_ditilbert_pipeline_en_5.5.0_3.0_1725507316652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_ditilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_ditilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_ditilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Neo111x/finetuning-sentiment_ditilBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_gaurimm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_gaurimm_pipeline_en.md
new file mode 100644
index 00000000000000..ceb191eeda08ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_gaurimm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_gaurimm_pipeline pipeline DistilBertForSequenceClassification from gaurimm
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_gaurimm_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_gaurimm_pipeline` is a English model originally trained by gaurimm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_gaurimm_pipeline_en_5.5.0_3.0_1725507299848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_gaurimm_pipeline_en_5.5.0_3.0_1725507299848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_gaurimm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_gaurimm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_gaurimm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gaurimm/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_prajvaladhav_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_prajvaladhav_en.md
new file mode 100644
index 00000000000000..06fb0749dc1036
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_prajvaladhav_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_prajvaladhav DistilBertForSequenceClassification from prajvaladhav
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_prajvaladhav
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_prajvaladhav` is a English model originally trained by prajvaladhav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_prajvaladhav_en_5.5.0_3.0_1725506932501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_prajvaladhav_en_5.5.0_3.0_1725506932501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_prajvaladhav","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_prajvaladhav", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_prajvaladhav|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/prajvaladhav/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline_en.md
new file mode 100644
index 00000000000000..ac06f60b36a520
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline pipeline DistilBertForSequenceClassification from prajvaladhav
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline` is a English model originally trained by prajvaladhav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline_en_5.5.0_3.0_1725506944962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline_en_5.5.0_3.0_1725506944962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_prajvaladhav_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/prajvaladhav/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline_en.md
new file mode 100644
index 00000000000000..ef8153a1749679
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline pipeline DistilBertForSequenceClassification from Yuezhangjoslin
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline` is a English model originally trained by Yuezhangjoslin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline_en_5.5.0_3.0_1725507338089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline_en_5.5.0_3.0_1725507338089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_yuezhangjoslin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Yuezhangjoslin/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ft_distilbert_gest_pred_seqeval_partialmatch_en.md b/docs/_posts/ahmedlone127/2024-09-05-ft_distilbert_gest_pred_seqeval_partialmatch_en.md
new file mode 100644
index 00000000000000..2ec99be04166d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ft_distilbert_gest_pred_seqeval_partialmatch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ft_distilbert_gest_pred_seqeval_partialmatch DistilBertForTokenClassification from Jsevisal
+author: John Snow Labs
+name: ft_distilbert_gest_pred_seqeval_partialmatch
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_distilbert_gest_pred_seqeval_partialmatch` is a English model originally trained by Jsevisal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_distilbert_gest_pred_seqeval_partialmatch_en_5.5.0_3.0_1725500826807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_distilbert_gest_pred_seqeval_partialmatch_en_5.5.0_3.0_1725500826807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ft_distilbert_gest_pred_seqeval_partialmatch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ft_distilbert_gest_pred_seqeval_partialmatch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_distilbert_gest_pred_seqeval_partialmatch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/Jsevisal/ft-distilbert-gest-pred-seqeval-partialmatch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-gec_turkish_seq_tagger_tr.md b/docs/_posts/ahmedlone127/2024-09-05-gec_turkish_seq_tagger_tr.md
new file mode 100644
index 00000000000000..adcf782b06c763
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-gec_turkish_seq_tagger_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish gec_turkish_seq_tagger BertForTokenClassification from GGLab
+author: John Snow Labs
+name: gec_turkish_seq_tagger
+date: 2024-09-05
+tags: [tr, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gec_turkish_seq_tagger` is a Turkish model originally trained by GGLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gec_turkish_seq_tagger_tr_5.5.0_3.0_1725516389714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gec_turkish_seq_tagger_tr_5.5.0_3.0_1725516389714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("gec_turkish_seq_tagger","tr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("gec_turkish_seq_tagger", "tr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gec_turkish_seq_tagger|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|tr|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/GGLab/gec-tr-seq-tagger
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-glot500_with_transliteration_average_en.md b/docs/_posts/ahmedlone127/2024-09-05-glot500_with_transliteration_average_en.md
new file mode 100644
index 00000000000000..ea823513a869dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-glot500_with_transliteration_average_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English glot500_with_transliteration_average XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: glot500_with_transliteration_average
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glot500_with_transliteration_average` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_average_en_5.5.0_3.0_1725508504520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_average_en_5.5.0_3.0_1725508504520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("glot500_with_transliteration_average","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("glot500_with_transliteration_average","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|glot500_with_transliteration_average|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/glot500-with-transliteration-average
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-glot500_with_transliteration_average_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-glot500_with_transliteration_average_pipeline_en.md
new file mode 100644
index 00000000000000..8fa9f211a25de8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-glot500_with_transliteration_average_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English glot500_with_transliteration_average_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: glot500_with_transliteration_average_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glot500_with_transliteration_average_pipeline` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_average_pipeline_en_5.5.0_3.0_1725508589066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glot500_with_transliteration_average_pipeline_en_5.5.0_3.0_1725508589066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("glot500_with_transliteration_average_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("glot500_with_transliteration_average_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|glot500_with_transliteration_average_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/glot500-with-transliteration-average
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-hf_nmt_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-05-hf_nmt_finetuned_en.md
new file mode 100644
index 00000000000000..2b5fb2c3f9795d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-hf_nmt_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hf_nmt_finetuned MarianTransformer from machinelearningzuu
+author: John Snow Labs
+name: hf_nmt_finetuned
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_nmt_finetuned` is a English model originally trained by machinelearningzuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_nmt_finetuned_en_5.5.0_3.0_1725494485147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_nmt_finetuned_en_5.5.0_3.0_1725494485147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("hf_nmt_finetuned","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("hf_nmt_finetuned","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_nmt_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.9 MB|
+
+## References
+
+https://huggingface.co/machinelearningzuu/HF_NMT_FINETUNED
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-hf_nmt_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-hf_nmt_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..4e78f53f1aff6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-hf_nmt_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hf_nmt_finetuned_pipeline pipeline MarianTransformer from machinelearningzuu
+author: John Snow Labs
+name: hf_nmt_finetuned_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_nmt_finetuned_pipeline` is a English model originally trained by machinelearningzuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_nmt_finetuned_pipeline_en_5.5.0_3.0_1725494513030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_nmt_finetuned_pipeline_en_5.5.0_3.0_1725494513030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hf_nmt_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hf_nmt_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_nmt_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.4 MB|
+
+## References
+
+https://huggingface.co/machinelearningzuu/HF_NMT_FINETUNED
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ibert_roberta_base_finetuned_wikineural_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-ibert_roberta_base_finetuned_wikineural_pipeline_en.md
new file mode 100644
index 00000000000000..d38eb1f28a3d7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ibert_roberta_base_finetuned_wikineural_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ibert_roberta_base_finetuned_wikineural_pipeline pipeline RoBertaForTokenClassification from DunnBC22
+author: John Snow Labs
+name: ibert_roberta_base_finetuned_wikineural_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ibert_roberta_base_finetuned_wikineural_pipeline` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ibert_roberta_base_finetuned_wikineural_pipeline_en_5.5.0_3.0_1725512336086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ibert_roberta_base_finetuned_wikineural_pipeline_en_5.5.0_3.0_1725512336086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ibert_roberta_base_finetuned_wikineural_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ibert_roberta_base_finetuned_wikineural_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ibert_roberta_base_finetuned_wikineural_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.0 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/ibert-roberta-base-finetuned-WikiNeural
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-imdb_spoiler_distilbertorigdatasetlr3_en.md b/docs/_posts/ahmedlone127/2024-09-05-imdb_spoiler_distilbertorigdatasetlr3_en.md
new file mode 100644
index 00000000000000..86d87032bd18dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-imdb_spoiler_distilbertorigdatasetlr3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imdb_spoiler_distilbertorigdatasetlr3 DistilBertForSequenceClassification from Zritze
+author: John Snow Labs
+name: imdb_spoiler_distilbertorigdatasetlr3
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_spoiler_distilbertorigdatasetlr3` is a English model originally trained by Zritze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_spoiler_distilbertorigdatasetlr3_en_5.5.0_3.0_1725506973893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_spoiler_distilbertorigdatasetlr3_en_5.5.0_3.0_1725506973893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("imdb_spoiler_distilbertorigdatasetlr3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdb_spoiler_distilbertorigdatasetlr3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdb_spoiler_distilbertorigdatasetlr3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Zritze/imdb-spoiler-distilbertOrigDatasetLR3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-imdb_spoiler_distilbertorigdatasetlr3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-imdb_spoiler_distilbertorigdatasetlr3_pipeline_en.md
new file mode 100644
index 00000000000000..856e88361d5d34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-imdb_spoiler_distilbertorigdatasetlr3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English imdb_spoiler_distilbertorigdatasetlr3_pipeline pipeline DistilBertForSequenceClassification from Zritze
+author: John Snow Labs
+name: imdb_spoiler_distilbertorigdatasetlr3_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_spoiler_distilbertorigdatasetlr3_pipeline` is a English model originally trained by Zritze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_spoiler_distilbertorigdatasetlr3_pipeline_en_5.5.0_3.0_1725506985870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_spoiler_distilbertorigdatasetlr3_pipeline_en_5.5.0_3.0_1725506985870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("imdb_spoiler_distilbertorigdatasetlr3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("imdb_spoiler_distilbertorigdatasetlr3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdb_spoiler_distilbertorigdatasetlr3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Zritze/imdb-spoiler-distilbertOrigDatasetLR3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-imdbreviews_classification_distilbert_v02_sebasr0_en.md b/docs/_posts/ahmedlone127/2024-09-05-imdbreviews_classification_distilbert_v02_sebasr0_en.md
new file mode 100644
index 00000000000000..be84a1fdd59b6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-imdbreviews_classification_distilbert_v02_sebasr0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imdbreviews_classification_distilbert_v02_sebasr0 DistilBertForSequenceClassification from sebasr0
+author: John Snow Labs
+name: imdbreviews_classification_distilbert_v02_sebasr0
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_sebasr0` is a English model originally trained by sebasr0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_sebasr0_en_5.5.0_3.0_1725507188934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_sebasr0_en_5.5.0_3.0_1725507188934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("imdbreviews_classification_distilbert_v02_sebasr0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdbreviews_classification_distilbert_v02_sebasr0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdbreviews_classification_distilbert_v02_sebasr0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sebasr0/imdbreviews_classification_distilbert_v02
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-indic_bert_finetuned_legal_try0_en.md b/docs/_posts/ahmedlone127/2024-09-05-indic_bert_finetuned_legal_try0_en.md
new file mode 100644
index 00000000000000..80c3908a4a9072
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-indic_bert_finetuned_legal_try0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_finetuned_legal_try0 AlbertForSequenceClassification from PoptropicaSahil
+author: John Snow Labs
+name: indic_bert_finetuned_legal_try0
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_finetuned_legal_try0` is a English model originally trained by PoptropicaSahil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_legal_try0_en_5.5.0_3.0_1725510000947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_finetuned_legal_try0_en_5.5.0_3.0_1725510000947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_finetuned_legal_try0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_finetuned_legal_try0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_finetuned_legal_try0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.7 MB|
+
+## References
+
+https://huggingface.co/PoptropicaSahil/indic-bert-finetuned-legal_try0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-indonesian_bert_base_ner_indonlu_en.md b/docs/_posts/ahmedlone127/2024-09-05-indonesian_bert_base_ner_indonlu_en.md
new file mode 100644
index 00000000000000..d70ebeabfe0f65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-indonesian_bert_base_ner_indonlu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indonesian_bert_base_ner_indonlu BertForTokenClassification from AptaArkana
+author: John Snow Labs
+name: indonesian_bert_base_ner_indonlu
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_bert_base_ner_indonlu` is a English model originally trained by AptaArkana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_bert_base_ner_indonlu_en_5.5.0_3.0_1725511812841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_bert_base_ner_indonlu_en_5.5.0_3.0_1725511812841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("indonesian_bert_base_ner_indonlu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("indonesian_bert_base_ner_indonlu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_bert_base_ner_indonlu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|412.6 MB|
+
+## References
+
+https://huggingface.co/AptaArkana/indonesian_bert_base_NER_indoNLU
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-indonesian_multi_id.md b/docs/_posts/ahmedlone127/2024-09-05-indonesian_multi_id.md
new file mode 100644
index 00000000000000..b81377b63b7d9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-indonesian_multi_id.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Indonesian indonesian_multi XlmRoBertaForQuestionAnswering from simoneZethof
+author: John Snow Labs
+name: indonesian_multi
+date: 2024-09-05
+tags: [id, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_multi` is a Indonesian model originally trained by simoneZethof.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_multi_id_5.5.0_3.0_1725497779965.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_multi_id_5.5.0_3.0_1725497779965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("indonesian_multi","id") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("indonesian_multi", "id")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_multi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|id|
+|Size:|864.5 MB|
+
+## References
+
+https://huggingface.co/simoneZethof/Indonesian_multi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-inproceedings_recognizer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-inproceedings_recognizer_pipeline_en.md
new file mode 100644
index 00000000000000..788e1d5a47a4e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-inproceedings_recognizer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English inproceedings_recognizer_pipeline pipeline DistilBertForSequenceClassification from LaLaf93
+author: John Snow Labs
+name: inproceedings_recognizer_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`inproceedings_recognizer_pipeline` is a English model originally trained by LaLaf93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/inproceedings_recognizer_pipeline_en_5.5.0_3.0_1725507215189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inproceedings_recognizer_pipeline_en_5.5.0_3.0_1725507215189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("inproceedings_recognizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("inproceedings_recognizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|inproceedings_recognizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LaLaf93/inproceedings_recognizer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-iwslt17_marian_big_ctx4_cwd4_english_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-iwslt17_marian_big_ctx4_cwd4_english_french_pipeline_en.md
new file mode 100644
index 00000000000000..903e129d79ecaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-iwslt17_marian_big_ctx4_cwd4_english_french_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English iwslt17_marian_big_ctx4_cwd4_english_french_pipeline pipeline MarianTransformer from context-mt
+author: John Snow Labs
+name: iwslt17_marian_big_ctx4_cwd4_english_french_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iwslt17_marian_big_ctx4_cwd4_english_french_pipeline` is a English model originally trained by context-mt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iwslt17_marian_big_ctx4_cwd4_english_french_pipeline_en_5.5.0_3.0_1725494645860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iwslt17_marian_big_ctx4_cwd4_english_french_pipeline_en_5.5.0_3.0_1725494645860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("iwslt17_marian_big_ctx4_cwd4_english_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("iwslt17_marian_big_ctx4_cwd4_english_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iwslt17_marian_big_ctx4_cwd4_english_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/context-mt/iwslt17-marian-big-ctx4-cwd4-en-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-lab1_true_random_en.md b/docs/_posts/ahmedlone127/2024-09-05-lab1_true_random_en.md
new file mode 100644
index 00000000000000..a96e2cc5cde443
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-lab1_true_random_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab1_true_random MarianTransformer from cheyannelam
+author: John Snow Labs
+name: lab1_true_random
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_true_random` is a English model originally trained by cheyannelam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lab1_true_random_en_5.5.0_3.0_1725494764779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_true_random_en_5.5.0_3.0_1725494764779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab1_true_random","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab1_true_random","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_true_random|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/cheyannelam/lab1_true_random
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-linkbert_en.md b/docs/_posts/ahmedlone127/2024-09-05-linkbert_en.md
new file mode 100644
index 00000000000000..26a24d4e8c2c3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-linkbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English linkbert BertForTokenClassification from dejanseo
+author: John Snow Labs
+name: linkbert
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`linkbert` is a English model originally trained by dejanseo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/linkbert_en_5.5.0_3.0_1725516074997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/linkbert_en_5.5.0_3.0_1725516074997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("linkbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("linkbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|linkbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/dejanseo/LinkBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-low_level_training_en.md b/docs/_posts/ahmedlone127/2024-09-05-low_level_training_en.md
new file mode 100644
index 00000000000000..dd7fc7dedc5706
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-low_level_training_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English low_level_training DistilBertForTokenClassification from Gkumi
+author: John Snow Labs
+name: low_level_training
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`low_level_training` is a English model originally trained by Gkumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/low_level_training_en_5.5.0_3.0_1725500436159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/low_level_training_en_5.5.0_3.0_1725500436159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("low_level_training","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("low_level_training", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|low_level_training|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/Gkumi/low-level-training
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-low_level_training_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-low_level_training_pipeline_en.md
new file mode 100644
index 00000000000000..f20b340cb56dd9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-low_level_training_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English low_level_training_pipeline pipeline DistilBertForTokenClassification from Gkumi
+author: John Snow Labs
+name: low_level_training_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`low_level_training_pipeline` is a English model originally trained by Gkumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/low_level_training_pipeline_en_5.5.0_3.0_1725500447520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/low_level_training_pipeline_en_5.5.0_3.0_1725500447520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("low_level_training_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("low_level_training_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|low_level_training_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/Gkumi/low-level-training
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline_en.md
new file mode 100644
index 00000000000000..3756d9f27e9ea6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline pipeline MarianTransformer from Jingyi28
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline` is a English model originally trained by Jingyi28.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline_en_5.5.0_3.0_1725494871156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline_en_5.5.0_3.0_1725494871156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.8 MB|
+
+## References
+
+https://huggingface.co/Jingyi28/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-model_arebmann_en.md b/docs/_posts/ahmedlone127/2024-09-05-model_arebmann_en.md
new file mode 100644
index 00000000000000..9373f93a9f1d60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-model_arebmann_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_arebmann DistilBertForTokenClassification from arebmann
+author: John Snow Labs
+name: model_arebmann
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_arebmann` is a English model originally trained by arebmann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_arebmann_en_5.5.0_3.0_1725506127099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_arebmann_en_5.5.0_3.0_1725506127099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("model_arebmann","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("model_arebmann", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_arebmann|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/arebmann/model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-multi_balanced_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-multi_balanced_model_pipeline_en.md
new file mode 100644
index 00000000000000..42332cbc136565
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-multi_balanced_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English multi_balanced_model_pipeline pipeline DistilBertForTokenClassification from SiriusW
+author: John Snow Labs
+name: multi_balanced_model_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_balanced_model_pipeline` is a English model originally trained by SiriusW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_balanced_model_pipeline_en_5.5.0_3.0_1725505950286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_balanced_model_pipeline_en_5.5.0_3.0_1725505950286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multi_balanced_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multi_balanced_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multi_balanced_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/SiriusW/multi_balanced_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-multilingual_e5_language_detection_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-05-multilingual_e5_language_detection_pipeline_xx.md
new file mode 100644
index 00000000000000..c4fd2ded5c094a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-multilingual_e5_language_detection_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_e5_language_detection_pipeline pipeline XlmRoBertaForSequenceClassification from Mike0307
+author: John Snow Labs
+name: multilingual_e5_language_detection_pipeline
+date: 2024-09-05
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_e5_language_detection_pipeline` is a Multilingual model originally trained by Mike0307.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_e5_language_detection_pipeline_xx_5.5.0_3.0_1725515245765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_e5_language_detection_pipeline_xx_5.5.0_3.0_1725515245765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_e5_language_detection_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_e5_language_detection_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_e5_language_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|887.2 MB|
+
+## References
+
+https://huggingface.co/Mike0307/multilingual-e5-language-detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-multilingual_e5_language_detection_xx.md b/docs/_posts/ahmedlone127/2024-09-05-multilingual_e5_language_detection_xx.md
new file mode 100644
index 00000000000000..8183d45a9ff2c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-multilingual_e5_language_detection_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_e5_language_detection XlmRoBertaForSequenceClassification from Mike0307
+author: John Snow Labs
+name: multilingual_e5_language_detection
+date: 2024-09-05
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_e5_language_detection` is a Multilingual model originally trained by Mike0307.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_e5_language_detection_xx_5.5.0_3.0_1725515165660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_e5_language_detection_xx_5.5.0_3.0_1725515165660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("multilingual_e5_language_detection","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("multilingual_e5_language_detection", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_e5_language_detection|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|887.2 MB|
+
+## References
+
+https://huggingface.co/Mike0307/multilingual-e5-language-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-multilingual_sentiment_covid19_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-05-multilingual_sentiment_covid19_pipeline_xx.md
new file mode 100644
index 00000000000000..a6bc8a5de8213d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-multilingual_sentiment_covid19_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_sentiment_covid19_pipeline pipeline XlmRoBertaForSequenceClassification from clampert
+author: John Snow Labs
+name: multilingual_sentiment_covid19_pipeline
+date: 2024-09-05
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_sentiment_covid19_pipeline` is a Multilingual model originally trained by clampert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_sentiment_covid19_pipeline_xx_5.5.0_3.0_1725513626526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_sentiment_covid19_pipeline_xx_5.5.0_3.0_1725513626526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_sentiment_covid19_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_sentiment_covid19_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_sentiment_covid19_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/clampert/multilingual-sentiment-covid19
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-n_distilbert_imdb_padding50model_en.md b/docs/_posts/ahmedlone127/2024-09-05-n_distilbert_imdb_padding50model_en.md
new file mode 100644
index 00000000000000..5ed3e96ed500ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-n_distilbert_imdb_padding50model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English n_distilbert_imdb_padding50model DistilBertForSequenceClassification from Realgon
+author: John Snow Labs
+name: n_distilbert_imdb_padding50model
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_distilbert_imdb_padding50model` is a English model originally trained by Realgon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding50model_en_5.5.0_3.0_1725507208723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding50model_en_5.5.0_3.0_1725507208723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("n_distilbert_imdb_padding50model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("n_distilbert_imdb_padding50model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|n_distilbert_imdb_padding50model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/Realgon/N_distilbert_imdb_padding50model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-n_distilbert_imdb_padding50model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-n_distilbert_imdb_padding50model_pipeline_en.md
new file mode 100644
index 00000000000000..468648a2ca0742
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-n_distilbert_imdb_padding50model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English n_distilbert_imdb_padding50model_pipeline pipeline DistilBertForSequenceClassification from Realgon
+author: John Snow Labs
+name: n_distilbert_imdb_padding50model_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_distilbert_imdb_padding50model_pipeline` is a English model originally trained by Realgon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding50model_pipeline_en_5.5.0_3.0_1725507220400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding50model_pipeline_en_5.5.0_3.0_1725507220400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("n_distilbert_imdb_padding50model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("n_distilbert_imdb_padding50model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|n_distilbert_imdb_padding50model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/Realgon/N_distilbert_imdb_padding50model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-naija_twitter_sentiment_afriberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-05-naija_twitter_sentiment_afriberta_large_en.md
new file mode 100644
index 00000000000000..14da44565ce9a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-naija_twitter_sentiment_afriberta_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English naija_twitter_sentiment_afriberta_large XlmRoBertaForSequenceClassification from Davlan
+author: John Snow Labs
+name: naija_twitter_sentiment_afriberta_large
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`naija_twitter_sentiment_afriberta_large` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/naija_twitter_sentiment_afriberta_large_en_5.5.0_3.0_1725514055535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/naija_twitter_sentiment_afriberta_large_en_5.5.0_3.0_1725514055535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("naija_twitter_sentiment_afriberta_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("naija_twitter_sentiment_afriberta_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|naija_twitter_sentiment_afriberta_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|470.5 MB|
+
+## References
+
+https://huggingface.co/Davlan/naija-twitter-sentiment-afriberta-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..3f74401fb0f35c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline pipeline BertForTokenClassification from bradoc
+author: John Snow Labs
+name: ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline` is a English model originally trained by bradoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline_en_5.5.0_3.0_1725516360982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline_en_5.5.0_3.0_1725516360982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_bert_large_cased_portuguese_lenerbr_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/bradoc/ner-bert-large-cased-pt-lenerbr-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ner_fine_tuned_beto_es.md b/docs/_posts/ahmedlone127/2024-09-05-ner_fine_tuned_beto_es.md
new file mode 100644
index 00000000000000..02b9d590214df4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ner_fine_tuned_beto_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish ner_fine_tuned_beto BertForTokenClassification from NazaGara
+author: John Snow Labs
+name: ner_fine_tuned_beto
+date: 2024-09-05
+tags: [es, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_fine_tuned_beto` is a Castilian, Spanish model originally trained by NazaGara.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_beto_es_5.5.0_3.0_1725516572752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_beto_es_5.5.0_3.0_1725516572752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_fine_tuned_beto","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_fine_tuned_beto", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_fine_tuned_beto|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/NazaGara/NER-fine-tuned-BETO
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ner_meddocan_es.md b/docs/_posts/ahmedlone127/2024-09-05-ner_meddocan_es.md
new file mode 100644
index 00000000000000..a0c21427a69019
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ner_meddocan_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish ner_meddocan RoBertaForTokenClassification from Dnidof
+author: John Snow Labs
+name: ner_meddocan
+date: 2024-09-05
+tags: [es, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_meddocan` is a Castilian, Spanish model originally trained by Dnidof.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_meddocan_es_5.5.0_3.0_1725512934617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_meddocan_es_5.5.0_3.0_1725512934617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("ner_meddocan","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("ner_meddocan", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_meddocan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|436.3 MB|
+
+## References
+
+https://huggingface.co/Dnidof/NER-MEDDOCAN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ner_model_onlyy_en.md b/docs/_posts/ahmedlone127/2024-09-05-ner_model_onlyy_en.md
new file mode 100644
index 00000000000000..3d0edc96f6cc14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ner_model_onlyy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_onlyy DistilBertForTokenClassification from ArshiaKarimian
+author: John Snow Labs
+name: ner_model_onlyy
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_onlyy` is a English model originally trained by ArshiaKarimian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_onlyy_en_5.5.0_3.0_1725500809192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_onlyy_en_5.5.0_3.0_1725500809192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_model_onlyy","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_model_onlyy", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_onlyy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ArshiaKarimian/ner_model_onlyy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-ner_totalamount_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-ner_totalamount_pipeline_en.md
new file mode 100644
index 00000000000000..9c81d2eacdf330
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-ner_totalamount_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_totalamount_pipeline pipeline DistilBertForTokenClassification from Pablito47
+author: John Snow Labs
+name: ner_totalamount_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_totalamount_pipeline` is a English model originally trained by Pablito47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_totalamount_pipeline_en_5.5.0_3.0_1725495829274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_totalamount_pipeline_en_5.5.0_3.0_1725495829274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_totalamount_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_totalamount_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_totalamount_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Pablito47/NER-TOTALAMOUNT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-nerde_base_en.md b/docs/_posts/ahmedlone127/2024-09-05-nerde_base_en.md
new file mode 100644
index 00000000000000..e2183d67dfed51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-nerde_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nerde_base BertForTokenClassification from Gpaiva
+author: John Snow Labs
+name: nerde_base
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nerde_base` is a English model originally trained by Gpaiva.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nerde_base_en_5.5.0_3.0_1725516244729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nerde_base_en_5.5.0_3.0_1725516244729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("nerde_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("nerde_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nerde_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/Gpaiva/NERDE-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-nli_conventional_fine_tuning_m4faisal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-nli_conventional_fine_tuning_m4faisal_pipeline_en.md
new file mode 100644
index 00000000000000..afb07787a60b25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-nli_conventional_fine_tuning_m4faisal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nli_conventional_fine_tuning_m4faisal_pipeline pipeline AlbertForSequenceClassification from m4faisal
+author: John Snow Labs
+name: nli_conventional_fine_tuning_m4faisal_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nli_conventional_fine_tuning_m4faisal_pipeline` is a English model originally trained by m4faisal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nli_conventional_fine_tuning_m4faisal_pipeline_en_5.5.0_3.0_1725509977575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nli_conventional_fine_tuning_m4faisal_pipeline_en_5.5.0_3.0_1725509977575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nli_conventional_fine_tuning_m4faisal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nli_conventional_fine_tuning_m4faisal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nli_conventional_fine_tuning_m4faisal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/m4faisal/NLI-Conventional-Fine-Tuning
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-norwegian_bokml_bert_large_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-05-norwegian_bokml_bert_large_pipeline_no.md
new file mode 100644
index 00000000000000..8f9bd7071a3b5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-norwegian_bokml_bert_large_pipeline_no.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Norwegian norwegian_bokml_bert_large_pipeline pipeline BertEmbeddings from NbAiLab
+author: John Snow Labs
+name: norwegian_bokml_bert_large_pipeline
+date: 2024-09-05
+tags: ["no", open_source, pipeline, onnx]
+task: Embeddings
+language: "no"
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_large_pipeline` is a Norwegian model originally trained by NbAiLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_large_pipeline_no_5.5.0_3.0_1725519702680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_large_pipeline_no_5.5.0_3.0_1725519702680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("norwegian_bokml_bert_large_pipeline", lang = "no")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("norwegian_bokml_bert_large_pipeline", lang = "no")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|norwegian_bokml_bert_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|no|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-bert-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-nuner_v0_1_en.md b/docs/_posts/ahmedlone127/2024-09-05-nuner_v0_1_en.md
new file mode 100644
index 00000000000000..a68ff9d0372b31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-nuner_v0_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nuner_v0_1 RoBertaForTokenClassification from numind
+author: John Snow Labs
+name: nuner_v0_1
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuner_v0_1` is a English model originally trained by numind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nuner_v0_1_en_5.5.0_3.0_1725502413165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuner_v0_1_en_5.5.0_3.0_1725502413165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("nuner_v0_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("nuner_v0_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuner_v0_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|346.2 MB|
+
+## References
+
+https://huggingface.co/numind/NuNER-v0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-nuner_v1_orgs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-nuner_v1_orgs_pipeline_en.md
new file mode 100644
index 00000000000000..6ee45b7d1e5eb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-nuner_v1_orgs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nuner_v1_orgs_pipeline pipeline RoBertaForTokenClassification from guishe
+author: John Snow Labs
+name: nuner_v1_orgs_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuner_v1_orgs_pipeline` is a English model originally trained by guishe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nuner_v1_orgs_pipeline_en_5.5.0_3.0_1725501680970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuner_v1_orgs_pipeline_en_5.5.0_3.0_1725501680970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nuner_v1_orgs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nuner_v1_orgs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuner_v1_orgs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.4 MB|
+
+## References
+
+https://huggingface.co/guishe/nuner-v1_orgs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-nuner_v2_fewnerd_fine_super_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-nuner_v2_fewnerd_fine_super_pipeline_en.md
new file mode 100644
index 00000000000000..1f848c5b9edd85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-nuner_v2_fewnerd_fine_super_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nuner_v2_fewnerd_fine_super_pipeline pipeline RoBertaForTokenClassification from guishe
+author: John Snow Labs
+name: nuner_v2_fewnerd_fine_super_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuner_v2_fewnerd_fine_super_pipeline` is a English model originally trained by guishe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nuner_v2_fewnerd_fine_super_pipeline_en_5.5.0_3.0_1725512693591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuner_v2_fewnerd_fine_super_pipeline_en_5.5.0_3.0_1725512693591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nuner_v2_fewnerd_fine_super_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nuner_v2_fewnerd_fine_super_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuner_v2_fewnerd_fine_super_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/guishe/nuner-v2_fewnerd_fine_super
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja_en.md b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja_en.md
new file mode 100644
index 00000000000000..05761e70dd4b67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja MarianTransformer from mekjr1
+author: John Snow Labs
+name: opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja` is a English model originally trained by mekjr1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja_en_5.5.0_3.0_1725494886584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja_en_5.5.0_3.0_1725494886584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_sja|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.9 MB|
+
+## References
+
+https://huggingface.co/mekjr1/opus-mt-en-es-finetuned-es-to-sja
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..d69ca5e4256f62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english MarianTransformer from PontifexMaximus
+author: John Snow Labs
+name: opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english` is a English model originally trained by PontifexMaximus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_en_5.5.0_3.0_1725495207768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_en_5.5.0_3.0_1725495207768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|523.1 MB|
+
+## References
+
+https://huggingface.co/PontifexMaximus/opus-mt-iir-en-finetuned-fa-to-en-finetuned-fa-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md
new file mode 100644
index 00000000000000..f114ecb09d4999
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from PontifexMaximus
+author: John Snow Labs
+name: opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline` is a English model originally trained by PontifexMaximus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725495232607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725495232607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_indoiranian_languages_english_finetuned_persian_farsi_tonga_tonga_islands_english_finetuned_persian_farsi_tonga_tonga_islands_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.7 MB|
+
+## References
+
+https://huggingface.co/PontifexMaximus/opus-mt-iir-en-finetuned-fa-to-en-finetuned-fa-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk_en.md b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk_en.md
new file mode 100644
index 00000000000000..ab1c5e4b1ce336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk MarianTransformer from obokkkk
+author: John Snow Labs
+name: opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk` is a English model originally trained by obokkkk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk_en_5.5.0_3.0_1725494630977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk_en_5.5.0_3.0_1725494630977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_obokkkk|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|540.5 MB|
+
+## References
+
+https://huggingface.co/obokkkk/opus-mt-ko-en-finetuned-en-to-ko
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier_en.md b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier_en.md
new file mode 100644
index 00000000000000..9d12ea33d00a95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier MarianTransformer from Galucier
+author: John Snow Labs
+name: opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier` is a English model originally trained by Galucier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier_en_5.5.0_3.0_1725494834277.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier_en_5.5.0_3.0_1725494834277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_thai_english_finetuned_english_tonga_tonga_islands_thai_galucier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|524.3 MB|
+
+## References
+
+https://huggingface.co/Galucier/opus-mt-th-en-finetuned-en-to-th
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-our_awesome_bert_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-our_awesome_bert_model_pipeline_en.md
new file mode 100644
index 00000000000000..44cacba064d0f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-our_awesome_bert_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English our_awesome_bert_model_pipeline pipeline DistilBertForTokenClassification from PetyaPetrova
+author: John Snow Labs
+name: our_awesome_bert_model_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`our_awesome_bert_model_pipeline` is a English model originally trained by PetyaPetrova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/our_awesome_bert_model_pipeline_en_5.5.0_3.0_1725500508265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/our_awesome_bert_model_pipeline_en_5.5.0_3.0_1725500508265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("our_awesome_bert_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("our_awesome_bert_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|our_awesome_bert_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/PetyaPetrova/our_awesome_BERT_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-philai_bge_2et_f_again_en.md b/docs/_posts/ahmedlone127/2024-09-05-philai_bge_2et_f_again_en.md
new file mode 100644
index 00000000000000..a899bc47afa496
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-philai_bge_2et_f_again_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English philai_bge_2et_f_again BGEEmbeddings from dbourget
+author: John Snow Labs
+name: philai_bge_2et_f_again
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`philai_bge_2et_f_again` is a English model originally trained by dbourget.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/philai_bge_2et_f_again_en_5.5.0_3.0_1725517119840.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/philai_bge_2et_f_again_en_5.5.0_3.0_1725517119840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("philai_bge_2et_f_again","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("philai_bge_2et_f_again","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|philai_bge_2et_f_again|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/dbourget/philai-bge-2et-f-again
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-philai_bge_2et_f_again_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-philai_bge_2et_f_again_pipeline_en.md
new file mode 100644
index 00000000000000..c4b0c39b93b5b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-philai_bge_2et_f_again_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English philai_bge_2et_f_again_pipeline pipeline BGEEmbeddings from dbourget
+author: John Snow Labs
+name: philai_bge_2et_f_again_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`philai_bge_2et_f_again_pipeline` is a English model originally trained by dbourget.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/philai_bge_2et_f_again_pipeline_en_5.5.0_3.0_1725517178289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/philai_bge_2et_f_again_pipeline_en_5.5.0_3.0_1725517178289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("philai_bge_2et_f_again_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("philai_bge_2et_f_again_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|philai_bge_2et_f_again_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/dbourget/philai-bge-2et-f-again
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-pii_model_ankitcodes_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-pii_model_ankitcodes_pipeline_en.md
new file mode 100644
index 00000000000000..69cd98617b8016
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-pii_model_ankitcodes_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pii_model_ankitcodes_pipeline pipeline BertForTokenClassification from ankitcodes
+author: John Snow Labs
+name: pii_model_ankitcodes_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_model_ankitcodes_pipeline` is a English model originally trained by ankitcodes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pii_model_ankitcodes_pipeline_en_5.5.0_3.0_1725510950122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_model_ankitcodes_pipeline_en_5.5.0_3.0_1725510950122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pii_model_ankitcodes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pii_model_ankitcodes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pii_model_ankitcodes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.5 MB|
+
+## References
+
+https://huggingface.co/ankitcodes/pii_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-portuguese_capitalization_punctuation_restoration_sanivert_pt.md b/docs/_posts/ahmedlone127/2024-09-05-portuguese_capitalization_punctuation_restoration_sanivert_pt.md
new file mode 100644
index 00000000000000..a0b49ef35eba8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-portuguese_capitalization_punctuation_restoration_sanivert_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese portuguese_capitalization_punctuation_restoration_sanivert BertForTokenClassification from VOCALINLP
+author: John Snow Labs
+name: portuguese_capitalization_punctuation_restoration_sanivert
+date: 2024-09-05
+tags: [pt, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_capitalization_punctuation_restoration_sanivert` is a Portuguese model originally trained by VOCALINLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/portuguese_capitalization_punctuation_restoration_sanivert_pt_5.5.0_3.0_1725515646135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_capitalization_punctuation_restoration_sanivert_pt_5.5.0_3.0_1725515646135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("portuguese_capitalization_punctuation_restoration_sanivert","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("portuguese_capitalization_punctuation_restoration_sanivert", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_capitalization_punctuation_restoration_sanivert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|pt|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/VOCALINLP/portuguese_capitalization_punctuation_restoration_sanivert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-pp_wnut_model_en.md b/docs/_posts/ahmedlone127/2024-09-05-pp_wnut_model_en.md
new file mode 100644
index 00000000000000..82763c603f59b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-pp_wnut_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pp_wnut_model DistilBertForTokenClassification from PradhyumnaPoralla
+author: John Snow Labs
+name: pp_wnut_model
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pp_wnut_model` is a English model originally trained by PradhyumnaPoralla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pp_wnut_model_en_5.5.0_3.0_1725506250165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pp_wnut_model_en_5.5.0_3.0_1725506250165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("pp_wnut_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("pp_wnut_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pp_wnut_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/PradhyumnaPoralla/pp_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-pp_wnut_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-pp_wnut_model_pipeline_en.md
new file mode 100644
index 00000000000000..3123314e76d230
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-pp_wnut_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pp_wnut_model_pipeline pipeline DistilBertForTokenClassification from PradhyumnaPoralla
+author: John Snow Labs
+name: pp_wnut_model_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pp_wnut_model_pipeline` is a English model originally trained by PradhyumnaPoralla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pp_wnut_model_pipeline_en_5.5.0_3.0_1725506262503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pp_wnut_model_pipeline_en_5.5.0_3.0_1725506262503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pp_wnut_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pp_wnut_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pp_wnut_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/PradhyumnaPoralla/pp_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-preprocessed_english_turkish_en.md b/docs/_posts/ahmedlone127/2024-09-05-preprocessed_english_turkish_en.md
new file mode 100644
index 00000000000000..e11a58c06d8246
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-preprocessed_english_turkish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English preprocessed_english_turkish MarianTransformer from ckartal
+author: John Snow Labs
+name: preprocessed_english_turkish
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`preprocessed_english_turkish` is a English model originally trained by ckartal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/preprocessed_english_turkish_en_5.5.0_3.0_1725495112064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/preprocessed_english_turkish_en_5.5.0_3.0_1725495112064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("preprocessed_english_turkish","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("preprocessed_english_turkish","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|preprocessed_english_turkish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ckartal/preprocessed-en-tr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-preprocessed_english_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-preprocessed_english_turkish_pipeline_en.md
new file mode 100644
index 00000000000000..64d8e3f0cc902d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-preprocessed_english_turkish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English preprocessed_english_turkish_pipeline pipeline MarianTransformer from ckartal
+author: John Snow Labs
+name: preprocessed_english_turkish_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`preprocessed_english_turkish_pipeline` is a English model originally trained by ckartal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/preprocessed_english_turkish_pipeline_en_5.5.0_3.0_1725495172128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/preprocessed_english_turkish_pipeline_en_5.5.0_3.0_1725495172128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("preprocessed_english_turkish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("preprocessed_english_turkish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|preprocessed_english_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ckartal/preprocessed-en-tr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-privacy_200k_masking_en.md b/docs/_posts/ahmedlone127/2024-09-05-privacy_200k_masking_en.md
new file mode 100644
index 00000000000000..19db29327c58d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-privacy_200k_masking_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English privacy_200k_masking DistilBertForTokenClassification from taro-pudding
+author: John Snow Labs
+name: privacy_200k_masking
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`privacy_200k_masking` is a English model originally trained by taro-pudding.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/privacy_200k_masking_en_5.5.0_3.0_1725500492423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/privacy_200k_masking_en_5.5.0_3.0_1725500492423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("privacy_200k_masking","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("privacy_200k_masking", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|privacy_200k_masking|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.7 MB|
+
+## References
+
+https://huggingface.co/taro-pudding/privacy-200k-masking
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-qa_synth_02_oct_with_finetune_1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-qa_synth_02_oct_with_finetune_1_1_pipeline_en.md
new file mode 100644
index 00000000000000..c109696047a227
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-qa_synth_02_oct_with_finetune_1_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_synth_02_oct_with_finetune_1_1_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synth_02_oct_with_finetune_1_1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_02_oct_with_finetune_1_1_pipeline` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synth_02_oct_with_finetune_1_1_pipeline_en_5.5.0_3.0_1725497599361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_02_oct_with_finetune_1_1_pipeline_en_5.5.0_3.0_1725497599361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_synth_02_oct_with_finetune_1_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_synth_02_oct_with_finetune_1_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synth_02_oct_with_finetune_1_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|805.1 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTH_02_OCT_WITH_FINETUNE_1.1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline_en.md
new file mode 100644
index 00000000000000..908c85e3f0d9b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline pipeline XlmRoBertaForQuestionAnswering from anuragsingh28
+author: John Snow Labs
+name: qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline` is a English model originally trained by anuragsingh28.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline_en_5.5.0_3.0_1725497047544.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline_en_5.5.0_3.0_1725497047544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synthetic_data_only_17_aug_base_nepal_bhasa_finetuned_anuragsingh28_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|800.2 MB|
+
+## References
+
+https://huggingface.co/anuragsingh28/QA_SYNTHETIC_DATA_ONLY_17_AUG_BASE_NEW_FINETUNED
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_19jan_5i_v1_en.md b/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_19jan_5i_v1_en.md
new file mode 100644
index 00000000000000..270f8ce3f139b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_19jan_5i_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English rap_phase2_19jan_5i_v1 XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: rap_phase2_19jan_5i_v1
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rap_phase2_19jan_5i_v1` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rap_phase2_19jan_5i_v1_en_5.5.0_3.0_1725498177356.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rap_phase2_19jan_5i_v1_en_5.5.0_3.0_1725498177356.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("rap_phase2_19jan_5i_v1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("rap_phase2_19jan_5i_v1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rap_phase2_19jan_5i_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|847.0 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/rap_phase2_19jan_5i_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_19jan_5i_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_19jan_5i_v1_pipeline_en.md
new file mode 100644
index 00000000000000..bee259d3f86513
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_19jan_5i_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rap_phase2_19jan_5i_v1_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: rap_phase2_19jan_5i_v1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rap_phase2_19jan_5i_v1_pipeline` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rap_phase2_19jan_5i_v1_pipeline_en_5.5.0_3.0_1725498243009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rap_phase2_19jan_5i_v1_pipeline_en_5.5.0_3.0_1725498243009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rap_phase2_19jan_5i_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rap_phase2_19jan_5i_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rap_phase2_19jan_5i_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|847.0 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/rap_phase2_19jan_5i_v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_22jan_8i_v1_en.md b/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_22jan_8i_v1_en.md
new file mode 100644
index 00000000000000..8a5745784f54e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_22jan_8i_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English rap_phase2_22jan_8i_v1 XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: rap_phase2_22jan_8i_v1
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rap_phase2_22jan_8i_v1` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rap_phase2_22jan_8i_v1_en_5.5.0_3.0_1725498750210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rap_phase2_22jan_8i_v1_en_5.5.0_3.0_1725498750210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("rap_phase2_22jan_8i_v1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("rap_phase2_22jan_8i_v1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rap_phase2_22jan_8i_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|847.8 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/rap_phase2_22jan_8i_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_22jan_8i_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_22jan_8i_v1_pipeline_en.md
new file mode 100644
index 00000000000000..592a7978053eca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rap_phase2_22jan_8i_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rap_phase2_22jan_8i_v1_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: rap_phase2_22jan_8i_v1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rap_phase2_22jan_8i_v1_pipeline` is a English model originally trained by am-infoweb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rap_phase2_22jan_8i_v1_pipeline_en_5.5.0_3.0_1725498808221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rap_phase2_22jan_8i_v1_pipeline_en_5.5.0_3.0_1725498808221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rap_phase2_22jan_8i_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rap_phase2_22jan_8i_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rap_phase2_22jan_8i_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|847.8 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/rap_phase2_22jan_8i_v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_base_exp_32_xx.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_exp_32_xx.md
new file mode 100644
index 00000000000000..c406638d637d54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_exp_32_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual roberta_base_exp_32 XlmRoBertaEmbeddings from pere
+author: John Snow Labs
+name: roberta_base_exp_32
+date: 2024-09-05
+tags: [xx, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_exp_32` is a Multilingual model originally trained by pere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_exp_32_xx_5.5.0_3.0_1725508124226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_exp_32_xx_5.5.0_3.0_1725508124226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("roberta_base_exp_32","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("roberta_base_exp_32","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_exp_32|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/pere/roberta-base-exp-32
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_base_finetuned_ner_lobrien001_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_finetuned_ner_lobrien001_pipeline_en.md
new file mode 100644
index 00000000000000..7831766df23cf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_finetuned_ner_lobrien001_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_finetuned_ner_lobrien001_pipeline pipeline RoBertaForTokenClassification from lobrien001
+author: John Snow Labs
+name: roberta_base_finetuned_ner_lobrien001_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_ner_lobrien001_pipeline` is a English model originally trained by lobrien001.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_lobrien001_pipeline_en_5.5.0_3.0_1725512932168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_lobrien001_pipeline_en_5.5.0_3.0_1725512932168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_finetuned_ner_lobrien001_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_finetuned_ner_lobrien001_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_ner_lobrien001_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|358.5 MB|
+
+## References
+
+https://huggingface.co/lobrien001/roberta-base-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_base_finetuned_ner_sevixdd_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_finetuned_ner_sevixdd_en.md
new file mode 100644
index 00000000000000..961cc5fbe27ae6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_finetuned_ner_sevixdd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_finetuned_ner_sevixdd RoBertaForTokenClassification from Sevixdd
+author: John Snow Labs
+name: roberta_base_finetuned_ner_sevixdd
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_ner_sevixdd` is a English model originally trained by Sevixdd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_sevixdd_en_5.5.0_3.0_1725512410967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_sevixdd_en_5.5.0_3.0_1725512410967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_finetuned_ner_sevixdd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_finetuned_ner_sevixdd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_ner_sevixdd|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|453.3 MB|
+
+## References
+
+https://huggingface.co/Sevixdd/roberta-base-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_demo_sanchirjav_mn.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_demo_sanchirjav_mn.md
new file mode 100644
index 00000000000000..1f1490417c7046
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_demo_sanchirjav_mn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Mongolian roberta_base_ner_demo_sanchirjav RoBertaForTokenClassification from sanchirjav
+author: John Snow Labs
+name: roberta_base_ner_demo_sanchirjav
+date: 2024-09-05
+tags: [mn, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_demo_sanchirjav` is a Mongolian model originally trained by sanchirjav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_sanchirjav_mn_5.5.0_3.0_1725512564104.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_sanchirjav_mn_5.5.0_3.0_1725512564104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_ner_demo_sanchirjav","mn") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_ner_demo_sanchirjav", "mn")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_demo_sanchirjav|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|mn|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/sanchirjav/roberta-base-ner-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_demo_sanchirjav_pipeline_mn.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_demo_sanchirjav_pipeline_mn.md
new file mode 100644
index 00000000000000..6c7dd490006091
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_demo_sanchirjav_pipeline_mn.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Mongolian roberta_base_ner_demo_sanchirjav_pipeline pipeline RoBertaForTokenClassification from sanchirjav
+author: John Snow Labs
+name: roberta_base_ner_demo_sanchirjav_pipeline
+date: 2024-09-05
+tags: [mn, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_demo_sanchirjav_pipeline` is a Mongolian model originally trained by sanchirjav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_sanchirjav_pipeline_mn_5.5.0_3.0_1725512585892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_sanchirjav_pipeline_mn_5.5.0_3.0_1725512585892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_ner_demo_sanchirjav_pipeline", lang = "mn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_ner_demo_sanchirjav_pipeline", lang = "mn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_demo_sanchirjav_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|mn|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/sanchirjav/roberta-base-ner-demo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_updated_mn.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_updated_mn.md
new file mode 100644
index 00000000000000..14c7457ccb5401
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_ner_updated_mn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Mongolian roberta_base_ner_updated RoBertaForTokenClassification from Bachi06
+author: John Snow Labs
+name: roberta_base_ner_updated
+date: 2024-09-05
+tags: [mn, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_updated` is a Mongolian model originally trained by Bachi06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_updated_mn_5.5.0_3.0_1725512476622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_updated_mn_5.5.0_3.0_1725512476622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_ner_updated","mn") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_ner_updated", "mn")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_updated|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|mn|
+|Size:|465.6 MB|
+
+## References
+
+https://huggingface.co/Bachi06/roberta-base-ner-updated
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_large_full_finetuned_ner_pablo_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_large_full_finetuned_ner_pablo_en.md
new file mode 100644
index 00000000000000..2b4740b621eaeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_large_full_finetuned_ner_pablo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_full_finetuned_ner_pablo RoBertaForTokenClassification from pabRomero
+author: John Snow Labs
+name: roberta_large_full_finetuned_ner_pablo
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_full_finetuned_ner_pablo` is a English model originally trained by pabRomero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_full_finetuned_ner_pablo_en_5.5.0_3.0_1725501988349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_full_finetuned_ner_pablo_en_5.5.0_3.0_1725501988349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_full_finetuned_ner_pablo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_full_finetuned_ner_pablo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_full_finetuned_ner_pablo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/pabRomero/RoBERTa-Large-full-finetuned-ner-pablo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_large_full_finetuned_ner_pablo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_large_full_finetuned_ner_pablo_pipeline_en.md
new file mode 100644
index 00000000000000..a5141d4ecd6eae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_large_full_finetuned_ner_pablo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_full_finetuned_ner_pablo_pipeline pipeline RoBertaForTokenClassification from pabRomero
+author: John Snow Labs
+name: roberta_large_full_finetuned_ner_pablo_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_full_finetuned_ner_pablo_pipeline` is a English model originally trained by pabRomero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_full_finetuned_ner_pablo_pipeline_en_5.5.0_3.0_1725502052113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_full_finetuned_ner_pablo_pipeline_en_5.5.0_3.0_1725502052113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_full_finetuned_ner_pablo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_full_finetuned_ner_pablo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_full_finetuned_ner_pablo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/pabRomero/RoBERTa-Large-full-finetuned-ner-pablo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..c9044e504fd895
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline pipeline RoBertaForTokenClassification from StivenLancheros
+author: John Snow Labs
+name: roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline
+date: 2024-09-05
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline` is a Castilian, Spanish model originally trained by StivenLancheros.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline_es_5.5.0_3.0_1725501682111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline_es_5.5.0_3.0_1725501682111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmentedtransfer_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|448.9 MB|
+
+## References
+
+https://huggingface.co/StivenLancheros/roberta-base-biomedical-clinical-es-finetuned-ner-CRAFT_AugmentedTransfer_ES
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_skills_ner_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_skills_ner_en.md
new file mode 100644
index 00000000000000..949000fe19425c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_skills_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_skills_ner RoBertaForTokenClassification from azrai99
+author: John Snow Labs
+name: roberta_skills_ner
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_skills_ner` is a English model originally trained by azrai99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_skills_ner_en_5.5.0_3.0_1725512878170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_skills_ner_en_5.5.0_3.0_1725512878170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_skills_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_skills_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_skills_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|431.7 MB|
+
+## References
+
+https://huggingface.co/azrai99/roberta-skills-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_skills_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_skills_ner_pipeline_en.md
new file mode 100644
index 00000000000000..6a53b844a3c632
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_skills_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_skills_ner_pipeline pipeline RoBertaForTokenClassification from azrai99
+author: John Snow Labs
+name: roberta_skills_ner_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_skills_ner_pipeline` is a English model originally trained by azrai99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_skills_ner_pipeline_en_5.5.0_3.0_1725512912698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_skills_ner_pipeline_en_5.5.0_3.0_1725512912698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_skills_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_skills_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_skills_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|431.7 MB|
+
+## References
+
+https://huggingface.co/azrai99/roberta-skills-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rogec_robert_large_en.md b/docs/_posts/ahmedlone127/2024-09-05-rogec_robert_large_en.md
new file mode 100644
index 00000000000000..dbf072033e19e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rogec_robert_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rogec_robert_large BertForTokenClassification from readerbench
+author: John Snow Labs
+name: rogec_robert_large
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rogec_robert_large` is a English model originally trained by readerbench.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rogec_robert_large_en_5.5.0_3.0_1725516427515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rogec_robert_large_en_5.5.0_3.0_1725516427515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rogec_robert_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rogec_robert_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rogec_robert_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/readerbench/RoGEC-robert-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rogec_robert_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-rogec_robert_large_pipeline_en.md
new file mode 100644
index 00000000000000..0ab35c61265be0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rogec_robert_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rogec_robert_large_pipeline pipeline BertForTokenClassification from readerbench
+author: John Snow Labs
+name: rogec_robert_large_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rogec_robert_large_pipeline` is a English model originally trained by readerbench.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rogec_robert_large_pipeline_en_5.5.0_3.0_1725516485863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rogec_robert_large_pipeline_en_5.5.0_3.0_1725516485863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rogec_robert_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rogec_robert_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rogec_robert_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/readerbench/RoGEC-robert-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rtmex23_pol4_cardif_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-rtmex23_pol4_cardif_pipeline_en.md
new file mode 100644
index 00000000000000..539dc47937cef8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rtmex23_pol4_cardif_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rtmex23_pol4_cardif_pipeline pipeline XlmRoBertaForSequenceClassification from javilonso
+author: John Snow Labs
+name: rtmex23_pol4_cardif_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rtmex23_pol4_cardif_pipeline` is a English model originally trained by javilonso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rtmex23_pol4_cardif_pipeline_en_5.5.0_3.0_1725514615560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rtmex23_pol4_cardif_pipeline_en_5.5.0_3.0_1725514615560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rtmex23_pol4_cardif_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rtmex23_pol4_cardif_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rtmex23_pol4_cardif_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/javilonso/rtmex23-pol4-cardif
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rubert_base_cased_conversational_ner_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-rubert_base_cased_conversational_ner_v3_pipeline_en.md
new file mode 100644
index 00000000000000..6155a8159470b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rubert_base_cased_conversational_ner_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_base_cased_conversational_ner_v3_pipeline pipeline BertForTokenClassification from Data-Lab
+author: John Snow Labs
+name: rubert_base_cased_conversational_ner_v3_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_conversational_ner_v3_pipeline` is a English model originally trained by Data-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_conversational_ner_v3_pipeline_en_5.5.0_3.0_1725511505366.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_conversational_ner_v3_pipeline_en_5.5.0_3.0_1725511505366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_base_cased_conversational_ner_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_base_cased_conversational_ner_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_cased_conversational_ner_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|662.3 MB|
+
+## References
+
+https://huggingface.co/Data-Lab/rubert-base-cased-conversational_ner-v3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rubert_base_massive_ner_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-05-rubert_base_massive_ner_pipeline_ru.md
new file mode 100644
index 00000000000000..3dde33431d741a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rubert_base_massive_ner_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian rubert_base_massive_ner_pipeline pipeline BertForTokenClassification from 0x7o
+author: John Snow Labs
+name: rubert_base_massive_ner_pipeline
+date: 2024-09-05
+tags: [ru, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_massive_ner_pipeline` is a Russian model originally trained by 0x7o.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_massive_ner_pipeline_ru_5.5.0_3.0_1725515727825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_massive_ner_pipeline_ru_5.5.0_3.0_1725515727825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_base_massive_ner_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_base_massive_ner_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_massive_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|664.6 MB|
+
+## References
+
+https://huggingface.co/0x7o/rubert-base-massive-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-rubert_base_massive_ner_ru.md b/docs/_posts/ahmedlone127/2024-09-05-rubert_base_massive_ner_ru.md
new file mode 100644
index 00000000000000..d8116523c51c9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-rubert_base_massive_ner_ru.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: Russian rubert_base_massive_ner BertForTokenClassification from 0x7194633
+author: John Snow Labs
+name: rubert_base_massive_ner
+date: 2024-09-05
+tags: [bert, ru, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_massive_ner` is a Russian model originally trained by 0x7194633.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_massive_ner_ru_5.5.0_3.0_1725515696890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_massive_ner_ru_5.5.0_3.0_1725515696890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = BertForTokenClassification.pretrained("rubert_base_massive_ner","ru") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = BertForTokenClassification  
+    .pretrained("rubert_base_massive_ner", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_massive_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ru|
+|Size:|664.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/0x7194633/rubert-base-massive-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-screenshot_fashion_clip_finetuned_v2_t1_en.md b/docs/_posts/ahmedlone127/2024-09-05-screenshot_fashion_clip_finetuned_v2_t1_en.md
new file mode 100644
index 00000000000000..cf77d7dc48c715
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-screenshot_fashion_clip_finetuned_v2_t1_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English screenshot_fashion_clip_finetuned_v2_t1 CLIPForZeroShotClassification from justin-shopcapsule
+author: John Snow Labs
+name: screenshot_fashion_clip_finetuned_v2_t1
+date: 2024-09-05
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`screenshot_fashion_clip_finetuned_v2_t1` is a English model originally trained by justin-shopcapsule.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/screenshot_fashion_clip_finetuned_v2_t1_en_5.5.0_3.0_1725522534693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/screenshot_fashion_clip_finetuned_v2_t1_en_5.5.0_3.0_1725522534693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("screenshot_fashion_clip_finetuned_v2_t1","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("screenshot_fashion_clip_finetuned_v2_t1","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|screenshot_fashion_clip_finetuned_v2_t1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|567.5 MB|
+
+## References
+
+https://huggingface.co/justin-shopcapsule/screenshot-fashion-clip-finetuned-v2-t1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-screenshot_fashion_clip_finetuned_v2_t1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-screenshot_fashion_clip_finetuned_v2_t1_pipeline_en.md
new file mode 100644
index 00000000000000..190412210cbe6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-screenshot_fashion_clip_finetuned_v2_t1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English screenshot_fashion_clip_finetuned_v2_t1_pipeline pipeline CLIPForZeroShotClassification from justin-shopcapsule
+author: John Snow Labs
+name: screenshot_fashion_clip_finetuned_v2_t1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`screenshot_fashion_clip_finetuned_v2_t1_pipeline` is a English model originally trained by justin-shopcapsule.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/screenshot_fashion_clip_finetuned_v2_t1_pipeline_en_5.5.0_3.0_1725522561269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/screenshot_fashion_clip_finetuned_v2_t1_pipeline_en_5.5.0_3.0_1725522561269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("screenshot_fashion_clip_finetuned_v2_t1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("screenshot_fashion_clip_finetuned_v2_t1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|screenshot_fashion_clip_finetuned_v2_t1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|567.6 MB|
+
+## References
+
+https://huggingface.co/justin-shopcapsule/screenshot-fashion-clip-finetuned-v2-t1
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sembr2023_distilbert_base_multilingual_cased_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-05-sembr2023_distilbert_base_multilingual_cased_pipeline_xx.md
new file mode 100644
index 00000000000000..89f072d86f4d95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sembr2023_distilbert_base_multilingual_cased_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual sembr2023_distilbert_base_multilingual_cased_pipeline pipeline DistilBertForTokenClassification from admko
+author: John Snow Labs
+name: sembr2023_distilbert_base_multilingual_cased_pipeline
+date: 2024-09-05
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sembr2023_distilbert_base_multilingual_cased_pipeline` is a Multilingual model originally trained by admko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sembr2023_distilbert_base_multilingual_cased_pipeline_xx_5.5.0_3.0_1725518792166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sembr2023_distilbert_base_multilingual_cased_pipeline_xx_5.5.0_3.0_1725518792166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sembr2023_distilbert_base_multilingual_cased_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sembr2023_distilbert_base_multilingual_cased_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sembr2023_distilbert_base_multilingual_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|505.5 MB|
+
+## References
+
+https://huggingface.co/admko/sembr2023-distilbert-base-multilingual-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sembr2023_distilbert_base_multilingual_cased_xx.md b/docs/_posts/ahmedlone127/2024-09-05-sembr2023_distilbert_base_multilingual_cased_xx.md
new file mode 100644
index 00000000000000..13c122707a7606
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sembr2023_distilbert_base_multilingual_cased_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sembr2023_distilbert_base_multilingual_cased DistilBertForTokenClassification from admko
+author: John Snow Labs
+name: sembr2023_distilbert_base_multilingual_cased
+date: 2024-09-05
+tags: [xx, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sembr2023_distilbert_base_multilingual_cased` is a Multilingual model originally trained by admko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sembr2023_distilbert_base_multilingual_cased_xx_5.5.0_3.0_1725518768654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sembr2023_distilbert_base_multilingual_cased_xx_5.5.0_3.0_1725518768654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("sembr2023_distilbert_base_multilingual_cased","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("sembr2023_distilbert_base_multilingual_cased", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sembr2023_distilbert_base_multilingual_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/admko/sembr2023-distilbert-base-multilingual-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_ancient_greek_to_1453_alignment_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_ancient_greek_to_1453_alignment_en.md
new file mode 100644
index 00000000000000..2d96091f8ddc61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_ancient_greek_to_1453_alignment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_ancient_greek_to_1453_alignment XlmRoBertaSentenceEmbeddings from UGARIT
+author: John Snow Labs
+name: sent_ancient_greek_to_1453_alignment
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ancient_greek_to_1453_alignment` is a English model originally trained by UGARIT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ancient_greek_to_1453_alignment_en_5.5.0_3.0_1725505559403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ancient_greek_to_1453_alignment_en_5.5.0_3.0_1725505559403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_ancient_greek_to_1453_alignment","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_ancient_greek_to_1453_alignment","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ancient_greek_to_1453_alignment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/UGARIT/grc-alignment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_ancient_greek_to_1453_alignment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_ancient_greek_to_1453_alignment_pipeline_en.md
new file mode 100644
index 00000000000000..7b457bdfc8361d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_ancient_greek_to_1453_alignment_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_ancient_greek_to_1453_alignment_pipeline pipeline XlmRoBertaSentenceEmbeddings from UGARIT
+author: John Snow Labs
+name: sent_ancient_greek_to_1453_alignment_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ancient_greek_to_1453_alignment_pipeline` is a English model originally trained by UGARIT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ancient_greek_to_1453_alignment_pipeline_en_5.5.0_3.0_1725505606246.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ancient_greek_to_1453_alignment_pipeline_en_5.5.0_3.0_1725505606246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_ancient_greek_to_1453_alignment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_ancient_greek_to_1453_alignment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ancient_greek_to_1453_alignment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/UGARIT/grc-alignment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_arbertv2_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-05-sent_arbertv2_pipeline_ar.md
new file mode 100644
index 00000000000000..213584dfb9e7b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_arbertv2_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_arbertv2_pipeline pipeline BertSentenceEmbeddings from UBC-NLP
+author: John Snow Labs
+name: sent_arbertv2_pipeline
+date: 2024-09-05
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_arbertv2_pipeline` is a Arabic model originally trained by UBC-NLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_arbertv2_pipeline_ar_5.5.0_3.0_1725520753169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_arbertv2_pipeline_ar_5.5.0_3.0_1725520753169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_arbertv2_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_arbertv2_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_arbertv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|607.7 MB|
+
+## References
+
+https://huggingface.co/UBC-NLP/ARBERTv2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_berel_finetuned_dss_maskedlm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_berel_finetuned_dss_maskedlm_pipeline_en.md
new file mode 100644
index 00000000000000..b14bb1471b3018
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_berel_finetuned_dss_maskedlm_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_berel_finetuned_dss_maskedlm_pipeline pipeline BertSentenceEmbeddings from yonatanlou
+author: John Snow Labs
+name: sent_berel_finetuned_dss_maskedlm_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berel_finetuned_dss_maskedlm_pipeline` is a English model originally trained by yonatanlou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berel_finetuned_dss_maskedlm_pipeline_en_5.5.0_3.0_1725521258294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berel_finetuned_dss_maskedlm_pipeline_en_5.5.0_3.0_1725521258294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_berel_finetuned_dss_maskedlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_berel_finetuned_dss_maskedlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berel_finetuned_dss_maskedlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|690.7 MB|
+
+## References
+
+https://huggingface.co/yonatanlou/BEREL-finetuned-DSS-maskedLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_bert_base_qarib_ar.md b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_base_qarib_ar.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_bert_base_qarib BertSentenceEmbeddings from qarib
+author: John Snow Labs
+name: sent_bert_base_qarib
+date: 2024-09-05
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_qarib` is a Arabic model originally trained by qarib.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_qarib_ar_5.5.0_3.0_1725521420119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_qarib_ar_5.5.0_3.0_1725521420119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_qarib","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_qarib","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_qarib|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|504.0 MB|
+
+## References
+
+https://huggingface.co/qarib/bert-base-qarib
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_bert_base_uncased_echr_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_base_uncased_echr_en.md
new file mode 100644
index 00000000000000..72866213685ed8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_base_uncased_echr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_echr BertSentenceEmbeddings from nlpaueb
+author: John Snow Labs
+name: sent_bert_base_uncased_echr
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_echr` is a English model originally trained by nlpaueb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_echr_en_5.5.0_3.0_1725520943671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_echr_en_5.5.0_3.0_1725520943671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_echr","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_echr","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_echr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/nlpaueb/bert-base-uncased-echr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_bert_base_uncased_echr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_base_uncased_echr_pipeline_en.md
new file mode 100644
index 00000000000000..a3fb412f572f5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_base_uncased_echr_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_echr_pipeline pipeline BertSentenceEmbeddings from nlpaueb
+author: John Snow Labs
+name: sent_bert_base_uncased_echr_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_echr_pipeline` is a English model originally trained by nlpaueb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_echr_pipeline_en_5.5.0_3.0_1725520963743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_echr_pipeline_en_5.5.0_3.0_1725520963743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_echr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_echr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_echr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/nlpaueb/bert-base-uncased-echr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline_pt.md
new file mode 100644
index 00000000000000..3437dfd18cee88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline_pt.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Portuguese sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline pipeline BertSentenceEmbeddings from stjiris
+author: John Snow Labs
+name: sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline
+date: 2024-09-05
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline` is a Portuguese model originally trained by stjiris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline_pt_5.5.0_3.0_1725521091402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline_pt_5.5.0_3.0_1725521091402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_MetaKD_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-mlm-gpl-nli-sts-MetaKD-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1_pt.md b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1_pt.md
new file mode 100644
index 00000000000000..5165810f4eb136
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1_pt.md
@@ -0,0 +1,79 @@
+---
+layout: model
+title: Portuguese Legal BERT Sentence Embedding Large Cased model
+author: John Snow Labs
+name: sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1
+date: 2024-09-05
+tags: [bert, pt, embeddings, sentence, open_source, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Legal BERT Sentence Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-portuguese-cased-legal-mlm-gpl-nli-sts-v1` is a Portuguese model originally trained by `stjiris`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1_pt_5.5.0_3.0_1725521687539.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1_pt_5.5.0_3.0_1725521687539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1", "pt") \
+.setInputCols("sentence") \
+.setOutputCol("bert_sentence")
+
+nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, sent_embeddings ])
+  result = pipeline.fit(data).transform(data)
+```
+```scala
+vval sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1", "pt")
+.setInputCols("sentence")
+.setOutputCol("bert_sentence")
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, sent_embeddings ))
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_bert_large_portuguese_cased_legal_mlm_gpl_nli_sts_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+References
+
+- https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-mlm-gpl-nli-sts-v1
+- https://rufimelo99.github.io/SemanticSearchSystemForSTJ/
+- https://www.SBERT.net
+- https://github.com/rufimelo99
+- https://www.inesc-id.pt/projects/PR07005/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_bert_large_uncased_whole_word_masking_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_large_uncased_whole_word_masking_en.md
new file mode 100644
index 00000000000000..ea0377ec3108e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_large_uncased_whole_word_masking_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_large_uncased_whole_word_masking BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_large_uncased_whole_word_masking
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_uncased_whole_word_masking` is a English model originally trained by google-bert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_uncased_whole_word_masking_en_5.5.0_3.0_1725520751019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_uncased_whole_word_masking_en_5.5.0_3.0_1725520751019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_uncased_whole_word_masking","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_uncased_whole_word_masking","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_uncased_whole_word_masking|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/google-bert/bert-large-uncased-whole-word-masking
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_10600_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_10600_en.md
new file mode 100644
index 00000000000000..dc1b2f87495215
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_10600_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_checkpoint_10600 XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_checkpoint_10600
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_10600` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_10600_en_5.5.0_3.0_1725505370653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_10600_en_5.5.0_3.0_1725505370653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_checkpoint_10600","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_checkpoint_10600","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_checkpoint_10600|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-10600
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_10600_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_10600_pipeline_en.md
new file mode 100644
index 00000000000000..775a682d44bf35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_10600_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_checkpoint_10600_pipeline pipeline XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_checkpoint_10600_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_10600_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_10600_pipeline_en_5.5.0_3.0_1725505418880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_10600_pipeline_en_5.5.0_3.0_1725505418880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_checkpoint_10600_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_checkpoint_10600_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_checkpoint_10600_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-10600
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_21200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_21200_pipeline_en.md
new file mode 100644
index 00000000000000..19ca7e41b2057b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_checkpoint_21200_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_checkpoint_21200_pipeline pipeline XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_checkpoint_21200_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_checkpoint_21200_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_checkpoint_21200_pipeline_en_5.5.0_3.0_1725504325955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_checkpoint_21200_pipeline_en_5.5.0_3.0_1725504325955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_checkpoint_21200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_checkpoint_21200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_checkpoint_21200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/checkpoint-21200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_corsican_condenser_marco_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_corsican_condenser_marco_en.md
new file mode 100644
index 00000000000000..e0cf11fbf6549d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_corsican_condenser_marco_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_corsican_condenser_marco BertSentenceEmbeddings from Luyu
+author: John Snow Labs
+name: sent_corsican_condenser_marco
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_corsican_condenser_marco` is a English model originally trained by Luyu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_corsican_condenser_marco_en_5.5.0_3.0_1725520813084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_corsican_condenser_marco_en_5.5.0_3.0_1725520813084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_corsican_condenser_marco","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_corsican_condenser_marco","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_corsican_condenser_marco|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/Luyu/co-condenser-marco
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_furina_indic_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_furina_indic_en.md
new file mode 100644
index 00000000000000..8d1710ec7103bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_furina_indic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_furina_indic XlmRoBertaSentenceEmbeddings from yihongLiu
+author: John Snow Labs
+name: sent_furina_indic
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_furina_indic` is a English model originally trained by yihongLiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_furina_indic_en_5.5.0_3.0_1725505112137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_furina_indic_en_5.5.0_3.0_1725505112137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_furina_indic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_furina_indic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_furina_indic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/yihongLiu/furina-indic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_less_100000_xlm_roberta_mmar_recipe_10_base_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_less_100000_xlm_roberta_mmar_recipe_10_base_en.md
new file mode 100644
index 00000000000000..bb88f269234263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_less_100000_xlm_roberta_mmar_recipe_10_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_less_100000_xlm_roberta_mmar_recipe_10_base XlmRoBertaSentenceEmbeddings from CennetOguz
+author: John Snow Labs
+name: sent_less_100000_xlm_roberta_mmar_recipe_10_base
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_less_100000_xlm_roberta_mmar_recipe_10_base` is a English model originally trained by CennetOguz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_less_100000_xlm_roberta_mmar_recipe_10_base_en_5.5.0_3.0_1725505180574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_less_100000_xlm_roberta_mmar_recipe_10_base_en_5.5.0_3.0_1725505180574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_less_100000_xlm_roberta_mmar_recipe_10_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_less_100000_xlm_roberta_mmar_recipe_10_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_less_100000_xlm_roberta_mmar_recipe_10_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/CennetOguz/less_100000_xlm_roberta_mmar_recipe_10_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_bert_base_no.md b/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_bert_base_no.md
new file mode 100644
index 00000000000000..90479e2cc56cf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_bert_base_no.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Norwegian sent_norwegian_bokml_bert_base BertSentenceEmbeddings from NbAiLab
+author: John Snow Labs
+name: sent_norwegian_bokml_bert_base
+date: 2024-09-05
+tags: ["no", open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: "no"
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norwegian_bokml_bert_base` is a Norwegian model originally trained by NbAiLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_bert_base_no_5.5.0_3.0_1725521480077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_bert_base_no_5.5.0_3.0_1725521480077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_norwegian_bokml_bert_base","no") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_norwegian_bokml_bert_base","no") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_norwegian_bokml_bert_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|no|
+|Size:|666.2 MB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-bert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_bert_base_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_bert_base_pipeline_no.md
new file mode 100644
index 00000000000000..aad5e8e4d45bb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_bert_base_pipeline_no.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Norwegian sent_norwegian_bokml_bert_base_pipeline pipeline BertSentenceEmbeddings from NbAiLab
+author: John Snow Labs
+name: sent_norwegian_bokml_bert_base_pipeline
+date: 2024-09-05
+tags: ["no", open_source, pipeline, onnx]
+task: Embeddings
+language: "no"
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norwegian_bokml_bert_base_pipeline` is a Norwegian model originally trained by NbAiLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_bert_base_pipeline_no_5.5.0_3.0_1725521510916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_bert_base_pipeline_no_5.5.0_3.0_1725521510916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_norwegian_bokml_bert_base_pipeline", lang = "no")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_norwegian_bokml_bert_base_pipeline", lang = "no")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_norwegian_bokml_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|no|
+|Size:|666.8 MB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-bert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_en.md
new file mode 100644
index 00000000000000..f76d2f2eef754e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4 XlmRoBertaSentenceEmbeddings from NbAiLab
+author: John Snow Labs
+name: sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4` is a English model originally trained by NbAiLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_en_5.5.0_3.0_1725504444156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_en_5.5.0_3.0_1725504444156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline_en.md
new file mode 100644
index 00000000000000..470d4e5bfbff59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline pipeline XlmRoBertaSentenceEmbeddings from NbAiLab
+author: John Snow Labs
+name: sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline` is a English model originally trained by NbAiLab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline_en_5.5.0_3.0_1725504494810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline_en_5.5.0_3.0_1725504494810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_norwegian_bokml_roberta_base_ncc_plus_scandi_2e4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_subsec_xlm_roberta_norwegian_catalan_galician_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_subsec_xlm_roberta_norwegian_catalan_galician_en.md
new file mode 100644
index 00000000000000..48095083f5bb13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_subsec_xlm_roberta_norwegian_catalan_galician_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_subsec_xlm_roberta_norwegian_catalan_galician XlmRoBertaSentenceEmbeddings from homersimpson
+author: John Snow Labs
+name: sent_subsec_xlm_roberta_norwegian_catalan_galician
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_subsec_xlm_roberta_norwegian_catalan_galician` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_subsec_xlm_roberta_norwegian_catalan_galician_en_5.5.0_3.0_1725504925365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_subsec_xlm_roberta_norwegian_catalan_galician_en_5.5.0_3.0_1725504925365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_subsec_xlm_roberta_norwegian_catalan_galician","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_subsec_xlm_roberta_norwegian_catalan_galician","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_subsec_xlm_roberta_norwegian_catalan_galician|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|642.5 MB|
+
+## References
+
+https://huggingface.co/homersimpson/subsec-xlm-roberta-no-ca-gl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en.md
new file mode 100644
index 00000000000000..e38ef408b10310
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline pipeline XlmRoBertaSentenceEmbeddings from homersimpson
+author: John Snow Labs
+name: sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en_5.5.0_3.0_1725505112451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline_en_5.5.0_3.0_1725505112451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_subsec_xlm_roberta_norwegian_catalan_galician_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|643.1 MB|
+
+## References
+
+https://huggingface.co/homersimpson/subsec-xlm-roberta-no-ca-gl
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_align_base_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_align_base_en.md
new file mode 100644
index 00000000000000..7a88cef4514220
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_align_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_align_base XlmRoBertaSentenceEmbeddings from microsoft
+author: John Snow Labs
+name: sent_xlm_align_base
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_align_base` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_align_base_en_5.5.0_3.0_1725504779836.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_align_base_en_5.5.0_3.0_1725504779836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_align_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_align_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_align_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|659.6 MB|
+
+## References
+
+https://huggingface.co/microsoft/xlm-align-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_align_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_align_base_pipeline_en.md
new file mode 100644
index 00000000000000..b885c7af94ec30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_align_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_align_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from microsoft
+author: John Snow Labs
+name: sent_xlm_align_base_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_align_base_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_align_base_pipeline_en_5.5.0_3.0_1725504978655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_align_base_pipeline_en_5.5.0_3.0_1725504978655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_align_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_align_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_align_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|660.1 MB|
+
+## References
+
+https://huggingface.co/microsoft/xlm-align-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_chichewa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_chichewa_pipeline_en.md
new file mode 100644
index 00000000000000..1b97a2eb49d101
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_chichewa_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_chichewa_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_chichewa_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_chichewa_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_chichewa_pipeline_en_5.5.0_3.0_1725504416003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_chichewa_pipeline_en_5.5.0_3.0_1725504416003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_chichewa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_chichewa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_chichewa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-chichewa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_naija_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_naija_en.md
new file mode 100644
index 00000000000000..263acf45c66119
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_naija_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_naija XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_naija
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_naija` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_naija_en_5.5.0_3.0_1725505293640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_naija_en_5.5.0_3.0_1725505293640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_naija","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_naija","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_naija|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-naija
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_naija_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_naija_pipeline_en.md
new file mode 100644
index 00000000000000..30b489c0c4de76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_naija_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_naija_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_naija_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_naija_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_naija_pipeline_en_5.5.0_3.0_1725505344444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_naija_pipeline_en_5.5.0_3.0_1725505344444.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_naija_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_naija_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_naija_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-naija
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_ft_cstwitter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_ft_cstwitter_pipeline_en.md
new file mode 100644
index 00000000000000..051cd31bf5f1c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_ft_cstwitter_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_ft_cstwitter_pipeline pipeline XlmRoBertaSentenceEmbeddings from hadifar
+author: John Snow Labs
+name: sent_xlm_roberta_base_ft_cstwitter_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_ft_cstwitter_pipeline` is a English model originally trained by hadifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_ft_cstwitter_pipeline_en_5.5.0_3.0_1725504993512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_ft_cstwitter_pipeline_en_5.5.0_3.0_1725504993512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_ft_cstwitter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_ft_cstwitter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_ft_cstwitter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hadifar/xlm-roberta-base-ft-CSTwitter
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_pretrained_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_pretrained_pipeline_en.md
new file mode 100644
index 00000000000000..6699f9f236ff09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_pretrained_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_pretrained_pipeline pipeline XlmRoBertaSentenceEmbeddings from am-shb
+author: John Snow Labs
+name: sent_xlm_roberta_base_pretrained_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_pretrained_pipeline` is a English model originally trained by am-shb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_pretrained_pipeline_en_5.5.0_3.0_1725504899653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_pretrained_pipeline_en_5.5.0_3.0_1725504899653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_pretrained_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_pretrained_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_pretrained_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/am-shb/xlm-roberta-base-pretrained
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-shopee_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-shopee_ner_pipeline_en.md
new file mode 100644
index 00000000000000..11b8765740c001
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-shopee_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English shopee_ner_pipeline pipeline DistilBertForTokenClassification from yzzhu
+author: John Snow Labs
+name: shopee_ner_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shopee_ner_pipeline` is a English model originally trained by yzzhu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shopee_ner_pipeline_en_5.5.0_3.0_1725518422629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shopee_ner_pipeline_en_5.5.0_3.0_1725518422629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("shopee_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("shopee_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|shopee_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/yzzhu/shopee-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-t2t_gun_nlth_from_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-t2t_gun_nlth_from_base_pipeline_en.md
new file mode 100644
index 00000000000000..ac98052ad23a5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-t2t_gun_nlth_from_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English t2t_gun_nlth_from_base_pipeline pipeline MarianTransformer from tiagoblima
+author: John Snow Labs
+name: t2t_gun_nlth_from_base_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t2t_gun_nlth_from_base_pipeline` is a English model originally trained by tiagoblima.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t2t_gun_nlth_from_base_pipeline_en_5.5.0_3.0_1725494445080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t2t_gun_nlth_from_base_pipeline_en_5.5.0_3.0_1725494445080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t2t_gun_nlth_from_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t2t_gun_nlth_from_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t2t_gun_nlth_from_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|220.9 MB|
+
+## References
+
+https://huggingface.co/tiagoblima/t2t-gun-nlth-from-base
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-t2t_gun_nlth_from_stratch_en.md b/docs/_posts/ahmedlone127/2024-09-05-t2t_gun_nlth_from_stratch_en.md
new file mode 100644
index 00000000000000..ea06a48b2b4b2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-t2t_gun_nlth_from_stratch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English t2t_gun_nlth_from_stratch MarianTransformer from tiagoblima
+author: John Snow Labs
+name: t2t_gun_nlth_from_stratch
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t2t_gun_nlth_from_stratch` is a English model originally trained by tiagoblima.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t2t_gun_nlth_from_stratch_en_5.5.0_3.0_1725494969247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t2t_gun_nlth_from_stratch_en_5.5.0_3.0_1725494969247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("t2t_gun_nlth_from_stratch","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("t2t_gun_nlth_from_stratch","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t2t_gun_nlth_from_stratch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|220.4 MB|
+
+## References
+
+https://huggingface.co/tiagoblima/t2t-gun-nlth-from-stratch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-test_ner_en.md b/docs/_posts/ahmedlone127/2024-09-05-test_ner_en.md
new file mode 100644
index 00000000000000..e335e4a7556f31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-test_ner_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English test_ner DistilBertForTokenClassification from Falah
+author: John Snow Labs
+name: test_ner
+date: 2024-09-05
+tags: [bert, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ner` is a English model originally trained by Falah.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ner_en_5.5.0_3.0_1725512753214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ner_en_5.5.0_3.0_1725512753214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = DistilBertForTokenClassification.pretrained("test_ner","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = DistilBertForTokenClassification  
+    .pretrained("test_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|298.4 MB|
+
+## References
+
+References
+
+https://huggingface.co/Falah/test-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-test_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-test_ner_pipeline_en.md
new file mode 100644
index 00000000000000..5d1ad751990d0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-test_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_ner_pipeline pipeline RoBertaForTokenClassification from jimypbr
+author: John Snow Labs
+name: test_ner_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ner_pipeline` is a English model originally trained by jimypbr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ner_pipeline_en_5.5.0_3.0_1725512841665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ner_pipeline_en_5.5.0_3.0_1725512841665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.4 MB|
+
+## References
+
+https://huggingface.co/jimypbr/test-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-timeset_ifm_en.md b/docs/_posts/ahmedlone127/2024-09-05-timeset_ifm_en.md
new file mode 100644
index 00000000000000..8ceaf90dab0e0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-timeset_ifm_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English timeset_ifm CLIPForZeroShotClassification from Timeset
+author: John Snow Labs
+name: timeset_ifm
+date: 2024-09-05
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`timeset_ifm` is a English model originally trained by Timeset.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/timeset_ifm_en_5.5.0_3.0_1725523071081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/timeset_ifm_en_5.5.0_3.0_1725523071081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("timeset_ifm","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("timeset_ifm","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|timeset_ifm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/Timeset/timeset-ifm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-trained_baseline_en.md b/docs/_posts/ahmedlone127/2024-09-05-trained_baseline_en.md
new file mode 100644
index 00000000000000..1086c6349e9d31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-trained_baseline_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trained_baseline DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: trained_baseline
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_baseline` is a English model originally trained by annamariagnat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_baseline_en_5.5.0_3.0_1725506014661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_baseline_en_5.5.0_3.0_1725506014661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("trained_baseline","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("trained_baseline", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_baseline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/trained_baseline
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-trained_slovak_en.md b/docs/_posts/ahmedlone127/2024-09-05-trained_slovak_en.md
new file mode 100644
index 00000000000000..b5800f1bf95108
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-trained_slovak_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trained_slovak DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: trained_slovak
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_slovak` is a English model originally trained by annamariagnat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_slovak_en_5.5.0_3.0_1725518903632.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_slovak_en_5.5.0_3.0_1725518903632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("trained_slovak","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("trained_slovak", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_slovak|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/trained_slovak
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-translation_english_korean_en.md b/docs/_posts/ahmedlone127/2024-09-05-translation_english_korean_en.md
new file mode 100644
index 00000000000000..6c22833c4691a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-translation_english_korean_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translation_english_korean MarianTransformer from halee9
+author: John Snow Labs
+name: translation_english_korean
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_english_korean` is a English model originally trained by halee9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_english_korean_en_5.5.0_3.0_1725495007486.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_english_korean_en_5.5.0_3.0_1725495007486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translation_english_korean","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translation_english_korean","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_english_korean|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|540.7 MB|
+
+## References
+
+https://huggingface.co/halee9/translation_en_ko
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-translation_english_korean_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-translation_english_korean_pipeline_en.md
new file mode 100644
index 00000000000000..1e4eb284be52a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-translation_english_korean_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English translation_english_korean_pipeline pipeline MarianTransformer from halee9
+author: John Snow Labs
+name: translation_english_korean_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_english_korean_pipeline` is a English model originally trained by halee9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_english_korean_pipeline_en_5.5.0_3.0_1725495033250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_english_korean_pipeline_en_5.5.0_3.0_1725495033250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("translation_english_korean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translation_english_korean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_english_korean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|541.2 MB|
+
+## References
+
+https://huggingface.co/halee9/translation_en_ko
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-tsc_classification_model_en.md b/docs/_posts/ahmedlone127/2024-09-05-tsc_classification_model_en.md
new file mode 100644
index 00000000000000..b10e7c41359ada
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-tsc_classification_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tsc_classification_model DistilBertForTokenClassification from SiriusW
+author: John Snow Labs
+name: tsc_classification_model
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tsc_classification_model` is a English model originally trained by SiriusW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tsc_classification_model_en_5.5.0_3.0_1725500616828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tsc_classification_model_en_5.5.0_3.0_1725500616828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("tsc_classification_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("tsc_classification_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tsc_classification_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/SiriusW/TSC_classification_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-tsc_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-tsc_classification_model_pipeline_en.md
new file mode 100644
index 00000000000000..90ac904255593f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-tsc_classification_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tsc_classification_model_pipeline pipeline DistilBertForTokenClassification from SiriusW
+author: John Snow Labs
+name: tsc_classification_model_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tsc_classification_model_pipeline` is a English model originally trained by SiriusW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tsc_classification_model_pipeline_en_5.5.0_3.0_1725500629351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tsc_classification_model_pipeline_en_5.5.0_3.0_1725500629351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tsc_classification_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tsc_classification_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tsc_classification_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/SiriusW/TSC_classification_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_ner7_latest_en.md b/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_ner7_latest_en.md
new file mode 100644
index 00000000000000..ea0564e75b80e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_ner7_latest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_ner7_latest RoBertaForTokenClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_ner7_latest
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_ner7_latest` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_ner7_latest_en_5.5.0_3.0_1725502127133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_ner7_latest_en_5.5.0_3.0_1725502127133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("twitter_roberta_base_ner7_latest","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("twitter_roberta_base_ner7_latest", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_ner7_latest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|443.6 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-ner7-latest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_ner7_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_ner7_latest_pipeline_en.md
new file mode 100644
index 00000000000000..42cb366362aaab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_ner7_latest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_ner7_latest_pipeline pipeline RoBertaForTokenClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_ner7_latest_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_ner7_latest_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_ner7_latest_pipeline_en_5.5.0_3.0_1725502156845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_ner7_latest_pipeline_en_5.5.0_3.0_1725502156845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_base_ner7_latest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_ner7_latest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_ner7_latest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|443.6 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-ner7-latest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-wg_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-wg_bert_pipeline_en.md
new file mode 100644
index 00000000000000..26bb7ce5e49b28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-wg_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English wg_bert_pipeline pipeline BertForTokenClassification from lukasweber
+author: John Snow Labs
+name: wg_bert_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wg_bert_pipeline` is a English model originally trained by lukasweber.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wg_bert_pipeline_en_5.5.0_3.0_1725516307137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wg_bert_pipeline_en_5.5.0_3.0_1725516307137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("wg_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("wg_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wg_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/lukasweber/WG_BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline_en.md
new file mode 100644
index 00000000000000..ec51059c4ad9f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline pipeline XlmRoBertaForQuestionAnswering from jluckyboyj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline` is a English model originally trained by jluckyboyj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline_en_5.5.0_3.0_1725499273948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline_en_5.5.0_3.0_1725499273948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_augument_visquad2_15_3_2023_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.0 MB|
+
+## References
+
+https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-augument-visquad2-15-3-2023-3
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_lingala_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_lingala_en.md
new file mode 100644
index 00000000000000..7389cf331a13e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_lingala_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_lingala XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_lingala
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_lingala` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_lingala_en_5.5.0_3.0_1725509095052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_lingala_en_5.5.0_3.0_1725509095052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_lingala","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_lingala","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_lingala|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-lingala
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_lingala_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_lingala_pipeline_en.md
new file mode 100644
index 00000000000000..64e413e918a20f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_lingala_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_lingala_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_lingala_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_lingala_pipeline` is a English model originally trained by Davlan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_lingala_pipeline_en_5.5.0_3.0_1725509144001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_lingala_pipeline_en_5.5.0_3.0_1725509144001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_lingala_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_lingala_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_lingala_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-lingala
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline_en.md
new file mode 100644
index 00000000000000..ff761d7e23c6ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline pipeline XlmRoBertaForSequenceClassification from danwilbury
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline` is a English model originally trained by danwilbury.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline_en_5.5.0_3.0_1725513608039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline_en_5.5.0_3.0_1725513608039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_english_danwilbury_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.5 MB|
+
+## References
+
+https://huggingface.co/danwilbury/xlm-roberta-base-finetuned-marc-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_nace_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_nace_en.md
new file mode 100644
index 00000000000000..7a08d5fd30a204
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_nace_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_nace XlmRoBertaForSequenceClassification from erst
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_nace
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_nace` is a English model originally trained by erst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_nace_en_5.5.0_3.0_1725514136109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_nace_en_5.5.0_3.0_1725514136109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_nace","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_nace", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_nace|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|857.3 MB|
+
+## References
+
+https://huggingface.co/erst/xlm-roberta-base-finetuned-nace
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_squad_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_squad_1_pipeline_en.md
new file mode 100644
index 00000000000000..12db35d9c15c31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_finetuned_squad_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_squad_1_pipeline pipeline XlmRoBertaForQuestionAnswering from kianshokraneh
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_squad_1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_squad_1_pipeline` is a English model originally trained by kianshokraneh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squad_1_pipeline_en_5.5.0_3.0_1725499142583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_squad_1_pipeline_en_5.5.0_3.0_1725499142583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_squad_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_squad_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_squad_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|812.2 MB|
+
+## References
+
+https://huggingface.co/kianshokraneh/xlm-roberta-base-finetuned-squad-1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline_en.md
new file mode 100644
index 00000000000000..e4987454befc6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline pipeline XlmRoBertaForQuestionAnswering from Nadav
+author: John Snow Labs
+name: xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline` is a English model originally trained by Nadav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline_en_5.5.0_3.0_1725499415044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline_en_5.5.0_3.0_1725499415044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_squad_finetuned_on_runaways_dutch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Nadav/xlm-roberta-base-squad-finetuned-on-runaways-nl
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_tweet_sentiment_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_tweet_sentiment_french_pipeline_en.md
new file mode 100644
index 00000000000000..62ab6a7f7307fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_base_tweet_sentiment_french_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_tweet_sentiment_french_pipeline pipeline XlmRoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: xlm_roberta_base_tweet_sentiment_french_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_tweet_sentiment_french_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tweet_sentiment_french_pipeline_en_5.5.0_3.0_1725514284611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tweet_sentiment_french_pipeline_en_5.5.0_3.0_1725514284611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_tweet_sentiment_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_tweet_sentiment_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_tweet_sentiment_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|780.6 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/xlm-roberta-base-tweet-sentiment-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_heq_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_heq_v1_pipeline_en.md
new file mode 100644
index 00000000000000..66f2a987274247
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_heq_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_heq_v1_pipeline pipeline XlmRoBertaForQuestionAnswering from pig4431
+author: John Snow Labs
+name: xlm_roberta_heq_v1_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_heq_v1_pipeline` is a English model originally trained by pig4431.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_heq_v1_pipeline_en_5.5.0_3.0_1725497608841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_heq_v1_pipeline_en_5.5.0_3.0_1725497608841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_heq_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_heq_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_heq_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|811.7 MB|
+
+## References
+
+https://huggingface.co/pig4431/xlm-roberta-HeQ-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_addi_italian_xlm_r_it.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_addi_italian_xlm_r_it.md
new file mode 100644
index 00000000000000..cb0827e32f7227
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_addi_italian_xlm_r_it.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Italian xlm_roberta_qa_addi_italian_xlm_r XlmRoBertaForQuestionAnswering from Gantenbein
+author: John Snow Labs
+name: xlm_roberta_qa_addi_italian_xlm_r
+date: 2024-09-05
+tags: [it, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_addi_italian_xlm_r` is a Italian model originally trained by Gantenbein.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_italian_xlm_r_it_5.5.0_3.0_1725498143876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_italian_xlm_r_it_5.5.0_3.0_1725498143876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_addi_italian_xlm_r","it") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_addi_italian_xlm_r", "it")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_addi_italian_xlm_r|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|it|
+|Size:|778.3 MB|
+
+## References
+
+https://huggingface.co/Gantenbein/ADDI-IT-XLM-R
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_addi_italian_xlm_r_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_addi_italian_xlm_r_pipeline_it.md
new file mode 100644
index 00000000000000..48bf7a2908ea2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_addi_italian_xlm_r_pipeline_it.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Italian xlm_roberta_qa_addi_italian_xlm_r_pipeline pipeline XlmRoBertaForQuestionAnswering from Gantenbein
+author: John Snow Labs
+name: xlm_roberta_qa_addi_italian_xlm_r_pipeline
+date: 2024-09-05
+tags: [it, open_source, pipeline, onnx]
+task: Question Answering
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_addi_italian_xlm_r_pipeline` is a Italian model originally trained by Gantenbein.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_italian_xlm_r_pipeline_it_5.5.0_3.0_1725498282219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_italian_xlm_r_pipeline_it_5.5.0_3.0_1725498282219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_addi_italian_xlm_r_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_addi_italian_xlm_r_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_addi_italian_xlm_r_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|778.3 MB|
+
+## References
+
+https://huggingface.co/Gantenbein/ADDI-IT-XLM-R
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_en.md
new file mode 100644
index 00000000000000..291e3bf8cd2339
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from teacookies)
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897
+date: 2024-09-05
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-more_fine_tune_24465520-26265897` is a English model originally trained by `teacookies`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_en_5.5.0_3.0_1725499516217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_en_5.5.0_3.0_1725499516217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.xlm_roberta.fine_tune_24465520_26265897").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|888.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265897
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909_en.md
new file mode 100644
index 00000000000000..d9ce5e77772c48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from teacookies)
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909
+date: 2024-09-05
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-more_fine_tune_24465520-26265909` is a English model originally trained by `teacookies`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909_en_5.5.0_3.0_1725499075296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909_en_5.5.0_3.0_1725499075296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.xlm_roberta.fine_tune_24465520_26265909").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265909|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|887.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265909
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_en.md
new file mode 100644
index 00000000000000..6fcd48837e1f93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English XlmRoBertaForQuestionAnswering (from teacookies)
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465515
+date: 2024-09-05
+tags: [en, open_source, question_answering, xlmroberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autonlp-roberta-base-squad2-24465515` is a English model originally trained by `teacookies`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_en_5.5.0_3.0_1725499882020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_en_5.5.0_3.0_1725499882020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465515","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifier = XlmRoBertaForQuestionAnswering
+.pretrained("xlm_roberta_qa_autonlp_roberta_base_squad2_24465515","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.xlm_roberta.base_24465515.by_teacookies").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465515|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|887.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465515
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline_en.md
new file mode 100644
index 00000000000000..e29f9fbe15f6ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline` is a English model originally trained by teacookies.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline_en_5.5.0_3.0_1725499947235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline_en_5.5.0_3.0_1725499947235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465515_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|887.3 MB|
+
+## References
+
+https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465515
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_xlm_roberta_base_chaii_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_xlm_roberta_base_chaii_pipeline_en.md
new file mode 100644
index 00000000000000..d2cd9bbcda10a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_xlm_roberta_base_chaii_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_xlm_roberta_base_chaii_pipeline pipeline XlmRoBertaForQuestionAnswering from SauravMaheshkar
+author: John Snow Labs
+name: xlm_roberta_qa_xlm_roberta_base_chaii_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_xlm_roberta_base_chaii_pipeline` is a English model originally trained by SauravMaheshkar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_chaii_pipeline_en_5.5.0_3.0_1725498684073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_xlm_roberta_base_chaii_pipeline_en_5.5.0_3.0_1725498684073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_chaii_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_xlm_roberta_base_chaii_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_xlm_roberta_base_chaii_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|888.3 MB|
+
+## References
+
+https://huggingface.co/SauravMaheshkar/xlm-roberta-base-chaii
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlmr_chatgptdetect_noisy_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlmr_chatgptdetect_noisy_en.md
new file mode 100644
index 00000000000000..3d589e8c7eb567
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlmr_chatgptdetect_noisy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_chatgptdetect_noisy XlmRoBertaForSequenceClassification from almanach
+author: John Snow Labs
+name: xlmr_chatgptdetect_noisy
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_chatgptdetect_noisy` is a English model originally trained by almanach.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_chatgptdetect_noisy_en_5.5.0_3.0_1725513947460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_chatgptdetect_noisy_en_5.5.0_3.0_1725513947460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_chatgptdetect_noisy","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_chatgptdetect_noisy", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_chatgptdetect_noisy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|822.5 MB|
+
+## References
+
+https://huggingface.co/almanach/xlmr-chatgptdetect-noisy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlmroberta_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlmroberta_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..0b4209f9e38614
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlmroberta_finetuned_squadv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlmroberta_finetuned_squadv2 XlmRoBertaForQuestionAnswering from quocviethere
+author: John Snow Labs
+name: xlmroberta_finetuned_squadv2
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_finetuned_squadv2` is a English model originally trained by quocviethere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_squadv2_en_5.5.0_3.0_1725497728185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_squadv2_en_5.5.0_3.0_1725497728185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_finetuned_squadv2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_finetuned_squadv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|839.9 MB|
+
+## References
+
+https://huggingface.co/quocviethere/xlmroberta-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlmroberta_finetuned_tydiqa_tel_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlmroberta_finetuned_tydiqa_tel_en.md
new file mode 100644
index 00000000000000..35c157adccdb74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlmroberta_finetuned_tydiqa_tel_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlmroberta_finetuned_tydiqa_tel XlmRoBertaForQuestionAnswering from Auracle7
+author: John Snow Labs
+name: xlmroberta_finetuned_tydiqa_tel
+date: 2024-09-05
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_finetuned_tydiqa_tel` is a English model originally trained by Auracle7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_tel_en_5.5.0_3.0_1725498104044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_finetuned_tydiqa_tel_en_5.5.0_3.0_1725498104044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_finetuned_tydiqa_tel","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlmroberta_finetuned_tydiqa_tel", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_finetuned_tydiqa_tel|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|842.1 MB|
+
+## References
+
+https://huggingface.co/Auracle7/XLMRoberta-finetuned-TyDIQA-Tel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_climate_change_explicit_v01_en.md b/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_climate_change_explicit_v01_en.md
new file mode 100644
index 00000000000000..ef0d4895493237
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_climate_change_explicit_v01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xml_roberta_climate_change_explicit_v01 XlmRoBertaForSequenceClassification from liserman
+author: John Snow Labs
+name: xml_roberta_climate_change_explicit_v01
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xml_roberta_climate_change_explicit_v01` is a English model originally trained by liserman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xml_roberta_climate_change_explicit_v01_en_5.5.0_3.0_1725514330349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xml_roberta_climate_change_explicit_v01_en_5.5.0_3.0_1725514330349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xml_roberta_climate_change_explicit_v01","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xml_roberta_climate_change_explicit_v01", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xml_roberta_climate_change_explicit_v01|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|852.5 MB|
+
+## References
+
+https://huggingface.co/liserman/xml-roberta-climate-change-explicit-v01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_climate_change_explicit_v01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_climate_change_explicit_v01_pipeline_en.md
new file mode 100644
index 00000000000000..1ba5fe67a13fc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_climate_change_explicit_v01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xml_roberta_climate_change_explicit_v01_pipeline pipeline XlmRoBertaForSequenceClassification from liserman
+author: John Snow Labs
+name: xml_roberta_climate_change_explicit_v01_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xml_roberta_climate_change_explicit_v01_pipeline` is a English model originally trained by liserman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xml_roberta_climate_change_explicit_v01_pipeline_en_5.5.0_3.0_1725514399712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xml_roberta_climate_change_explicit_v01_pipeline_en_5.5.0_3.0_1725514399712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xml_roberta_climate_change_explicit_v01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xml_roberta_climate_change_explicit_v01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xml_roberta_climate_change_explicit_v01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|852.5 MB|
+
+## References
+
+https://huggingface.co/liserman/xml-roberta-climate-change-explicit-v01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_science_subject_text_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_science_subject_text_classification_pipeline_en.md
new file mode 100644
index 00000000000000..ab923bb0262eb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xml_roberta_science_subject_text_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xml_roberta_science_subject_text_classification_pipeline pipeline XlmRoBertaForSequenceClassification from mominah
+author: John Snow Labs
+name: xml_roberta_science_subject_text_classification_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xml_roberta_science_subject_text_classification_pipeline` is a English model originally trained by mominah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xml_roberta_science_subject_text_classification_pipeline_en_5.5.0_3.0_1725515315368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xml_roberta_science_subject_text_classification_pipeline_en_5.5.0_3.0_1725515315368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xml_roberta_science_subject_text_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xml_roberta_science_subject_text_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xml_roberta_science_subject_text_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|655.2 MB|
+
+## References
+
+https://huggingface.co/mominah/xml-roberta-science-subject-text-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-yappychappy_en.md b/docs/_posts/ahmedlone127/2024-09-05-yappychappy_en.md
new file mode 100644
index 00000000000000..0f38741e2a5892
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-yappychappy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yappychappy DistilBertForTokenClassification from CoRGI-HF
+author: John Snow Labs
+name: yappychappy
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yappychappy` is a English model originally trained by CoRGI-HF.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yappychappy_en_5.5.0_3.0_1725500806342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yappychappy_en_5.5.0_3.0_1725500806342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("yappychappy","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("yappychappy", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yappychappy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/CoRGI-HF/YappyChappy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-zhenyin_awesome_model_en.md b/docs/_posts/ahmedlone127/2024-09-05-zhenyin_awesome_model_en.md
new file mode 100644
index 00000000000000..f091825841ec01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-zhenyin_awesome_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English zhenyin_awesome_model DistilBertForTokenClassification from johnsonZoom
+author: John Snow Labs
+name: zhenyin_awesome_model
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zhenyin_awesome_model` is a English model originally trained by johnsonZoom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zhenyin_awesome_model_en_5.5.0_3.0_1725505911792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zhenyin_awesome_model_en_5.5.0_3.0_1725505911792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("zhenyin_awesome_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("zhenyin_awesome_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zhenyin_awesome_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/johnsonZoom/zhenyin-awesome-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-zhenyin_awesome_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-zhenyin_awesome_model_pipeline_en.md
new file mode 100644
index 00000000000000..2138eb44f7db6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-zhenyin_awesome_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English zhenyin_awesome_model_pipeline pipeline DistilBertForTokenClassification from johnsonZoom
+author: John Snow Labs
+name: zhenyin_awesome_model_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zhenyin_awesome_model_pipeline` is a English model originally trained by johnsonZoom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zhenyin_awesome_model_pipeline_en_5.5.0_3.0_1725505923619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zhenyin_awesome_model_pipeline_en_5.5.0_3.0_1725505923619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("zhenyin_awesome_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("zhenyin_awesome_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zhenyin_awesome_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/johnsonZoom/zhenyin-awesome-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file